2012 SCIS Brochure

FIU School of Computing and Information Sciences

Florida International University (FIU), the state university of Florida in Miami, is ranked by

the Carnegie Foundation as a comprehensive doctoral research university with high research

activity. FIU offers more than 180 baccalaureate, masters, and professional and doctoral

degree programs to over 48,000 students. Miami is a diverse international city renowned for being the

business and IT hub for Latin America and is home for thousands of technology related businesses. As

one of South Florida’s anchor institutions, FIU is worlds ahead in its local and global engagement and

is committed to finding solutions to the most challenging problems of our times.

The School of Computing and Information Sciences (SCIS) is a rapidly growing program of

excellence at the University, with 35 faculty members and over 1,300 students, including 65 Ph.D.

students. SCIS offers B.S., M.S., and Ph.D. degrees in Computer Science, an M.S. degree in

Telecommunications and Networking, and B.S., B.A., and M.S. degrees in Information Technology.

SCIS has received approximately $19 million in the last four years in external research funding and

donations, has six research centers/clusters with first-class computing infrastructure and support, and

enjoys broad and dynamic industry and international partnerships.

FIU TERRAFLY See page 23

cis.fiu.edu

Florida International University • School of Computing and Information Sciences 1

Dr. Mark Rosenberg, FIU President Florida International University has embarked on a campaign to engage communities from around the world by demonstrating the impact of our distinguished faculty and our dedicated and enthusiastic students. We call this effort Worlds Ahead; you will find it throughout our campus, embodied in the spirit and effort that drives units like our School of Computing and Information Sciences to pursue outstanding achievements. The School is a great ambassador for this vision since computing and information technology is at the

heart of so much of our daily lives, is the engine for many innovations we enjoy today, and will be key for the development of the innovations to come.

The pursuit of innovation means going beyond what is expected - a tenant of Worlds Ahead. It means taking the opportunity you are given and doing something great with it. The words are as much a part of what you are today as what you aspire to be tomorrow. It is an attitude, one that commands us to think differently, exceed expectations and create new possibilities. I hope you will find in these pages many examples of that spirit, attitude and innovation, as we are very proud of the School’s accomplishments. We heartily invite you to work with the School, become a partner, and join our community as we realize this vision.

Dr. Amir Mirmiran, CEC Dean and ProfessorInformation Technology is a critical enabler for Engineering, Science and many Industries. Our School of Computing and Information Sciences provides the research infrastructure, faculty expertise and top students to pursue state-of-the-art research and technology development needed to solve the most challenging multi-disciplinary problems.

Dr. Ram Iyengar, SCIS Director and Ryder ProfessorOur 25 year-old-school is a well-respected computer science and information technology research and education program. Over the last 10 years we have built a highly engaged and focused multi-disciplinary research community at one of the largest state universities in the US. Our School has experienced tremendous growth in degree offerings, research funding, and enrollment. Our School is one of the largest degree awarding programs of its

kind. The success of our School is measured in the awards our faculty members have earned for their research and teaching excellence, the diverse, outstanding students our programs produce, the state of the art technologies and innovation our labs are developing, and our global collaborations with government, industry and academia.

We lead large-scale research consortia such as the Latin American Grid, a research and education partnership with leading international universities and IBM Research. Our faculty and students have engaged in many international scientific communities and publish in leading computing journals. Our highly competitive students work in top research labs throughout the world such as Barcelona Super Computing Center and IBM Research in China and India. We are eager to work with ambitious researchers and high-quality students with interest in international science and collaborations as we prepare the next generation of computer science and information technology professionals.

message

Florida International University • School of Computing and Information Sciences2

Undergraduate Degree Programs:• The Bachelor of Science in Computer Science degree presents a course of study that includes mathematics, science,

and computer science foundational topics necessary for the preparation of a successful computing professional. Students are taught skills in the art and science of computer programming that expose them to program design, logic, computing theory, software engineering, and validation. Students develop software in our state of the art labs that offer a variety of operating system and interactive development environments. Typical jobs obtained by recent graduates include; computer programmer, computer analyst, software engineer, and computer support specialist. Students who intend to pursue a software engineering career should select the Software Development Track.

• The Bachelor of Science in Information Technology degree presents a course of study that includes hands-on skill development in a broad array of subjects such as software development, databases, and networking. Students develop software in our state of the art labs that offer a variety of operating system and interactive development environments. Information Technology majors focus less on mathematical and theoretical concepts of computing than Computer Science majors and more on specific and state-of-the-art technologies. Students who want to add a strong theoretical foundation of Computer Science can pursue the Information Technology Software Major track. Typical jobs obtained by recent graduates include; systems administrator, applications support specialist, database administrator, computer programmer, computer analyst, and computer support specialist.

Graduate Degree Programs• The Master of Science in Telecommunications and Networking is intended to educate individuals seeking

employment with hardware and/or software companies, service providers, large user organizations, or telecommunications regulatory agencies as well as for those who are already employed by these companies/organizations and wish to obtain formal, higher-level, specialized degree in Telecommunications and Networking. Telecommunication and Networking students learn how to lead in the ever changing environment of real-time global information networking, telecommunications, wireless and optical strategies and how to amplify business value through communications, technologies and systems.

School of Computing and Information Sciences


Messages 1

from the FIU President, CEC Dean, and SCIS Director

Degree Programs 2

Research Areas 3

Points of Pride 4

Research Centers, Labs and Initiatives 4

Lectures and Symposiums 5

Faculty Profiles 6

Selected Research Activities

Systems 14

Software 18

Sensors and Networks 20

Cyberinfrastructure 22

Data 23

Theory 26

Community 27

Computational 32

Discovery Lab 35

Recent Contracts and Grants 36

Selected Awards and Honors 38

Selected Books by Faculty 40

Selected Research and Collaboration 42

Curriculum 44

Alumni Updates 45

Student Accomplishments and Outreach 45

PhD Graduate Employment Profile 46

Shared Computing Facilities and Laboratories 48

Industry Advisory Board 49

• The Master of Science in Information Technology is intended to educate students in the area of technical aspects of Information. It provides an emphasis on software technology, database technology, and security technology. The program is ideally suited for those who wish to obtain a higher level degree in Information Technology, and seek employment in the IT industry.

• The Master of Science in Computer Science degree provides study in state-of-the-art computer applications as well as an introduction to the theoretical foundations of computer science.

• The Doctor of Philosophy in Computer Science is designed to provide study in all major areas of computer science while leading to the frontiers of knowledge in a chosen field of concentration.

Areas of ResearchOur faculty embodies a broad range of computing interests and has built dynamic and innovative research centers and groups around several areas of specialization. These include:• Database Systems, including database design, database management and applications, database theory and implementation,

database machines, distributed databases, information retrieval in heterogeneous databases, multimedia databases, data mining and digital libraries.

• Software Engineering, including large-scale software design, programming language environments, software development and maintenance methodologies, object-oriented techniques, software reuse, and software quality assurance.

• Parallel and Distributed Systems, including formal specification methodologies, distributed file systems, distributed multimedia systems and operating systems, storage systems, high-performance systems, cloud computing systems, and security.

• Computer Networks, including network protocols, multimedia networking, and wireless communications.

• Theory, including algorithms and data structures, programming languages, computer security, program verification and logic.

• Artificial Intelligence, including neural networks, expert systems, automated reasoning, term rewriting systems and intelligent tutoring systems.

• Affective Social Computing, including knowledge representation, natural language processing, intelligent virtual characters, and multimodal user interfaces.

• Cognitive Science, with emphasis on the philosophical, psychological and linguistic underpinnings of artificial intelligence.

• Bioinformatics and Computational Biology.

content


NSF CREST Center for Innovative Information Systems Engineering

NSF I/UCRC: Center for Advanced Knowledge Enablement

NSF PIRE A Global Living Laboratory for Cyberinfrastructure Application Enablement

Latin American Grid and the IBM Center for Autonomic and Grid Computing

High Performance Database Research Center

Center for Advanced Distributed Software Engineering

Telecommunications and Information Technology Institute

Bioinformatics and Computational Biology Laboratory

Systems Research Laboratory

Discovery Lab

Distributed Multimedia & Information Systems Laboratory

Laboratory for Virtualized Infrastructure, Systems, and Applications

Affective Social Computing Laboratory

Disaster IT Research Group

Knowledge Discovery Research Group

Modeling and Networking Systems Research Group

Software Testing and Research Group

Research Centers, Institutes, Labs and Initiatives cis.fiu.edu/research

• Second largest Engineering College based Computer Science degree awarding program in the US.

• 1,300+ students

• 150+ degrees awarded/year

• Among the top 25 -36 Ph.D. granting Computer Sci-ence departments in the US on a per research faculty funding basis

• Over 20 percent of the State Universities’ undergradu-ates in Computer Science

• Our alumni are engineers at Apple, Citrix, Google, IBM, Microsoft, Oracle, etc.

• SCIS accounts for 13% of all Hispanic Ph.D. students

• Faculty external funding ratio is one of the best in the state for an academic department.

• Many faculty have earned NSF and DOE Career Awards, Research awards from Google, IBM, Xerox, and NetApp.

• Faculty recognized with Distinguished Awards such as IEEE Fellow, ACM Fellow, Kaufman Professor, and AAAI Nils Nilsson.

• Best Conference Paper Awards from IEEE, ACSAC and other Computer Societies.

• 157 Peer Reviewed Publications 2010-11

Points of Pride


Distinguished Lecture Series 2011-2012

At Florida International University

Computing and Information Science

Points of Pride Lectures and Symposiums

The School of Computing and Information Science at FIU is honored to recognize our prestigious

speakers; Jack Dongarra, Moshe Y. Vardi, Mary F. Wheeler, Vince McKoy and Edward Seidel who

participated in the 2011-12 Citrix Distinguished Lecture Series. The lectures presented exciting

topics such as the challenges of petascale computing, simulating quantum collisions, subsurface

modeling and simulation and Big Data science. We would like to thank our Industry Sponsor

Citrix for their support of this enriching lecture series.

You can find these lectures and materials at: cis.fiu.edu/citrixdls

School of Computing and Information Sciences

Celebrating the Success of our Students

Please Save the Date: November 9th - 10th, 2012

Join us for a celebration of computing research and education as we welcome distinguished

computing leaders, alumni, staff, and friends old and new. Be a part of the tradition

and help us build our future. Distinguished speakers include: Nancy Lynch, MIT; James

O’Brien, Berkeley; Bjarne Stroustrup, Texas A&M; and Jeffrey D. Ullman, Stanford.

Faculty Profiles: School Administration

Ram IyengarRyder Professor and Director, ECS 351Phone: 305-348-3947Email: [email protected]:.cis.fiu.edu/~iyengar

Dr. Iyengar is the director and Ryder professor of School of Computing and Information Sciences at Florida International Uni-versity, Miami, and is also the chaired professor at various institutions around the world. His publica-tions include 6 textbooks, 5 edited books and over 400 research papers. His research interests include high-performance algorithms, data structures, sensor fusion, data mining, and intelligent systems. He is a world-class expert in computational aspects of sensor networks, data structures, algorithms for various distributed applications. His techniques have been used by various federal agencies (NRL, ORNL, NASA) for their projects. His work has been cited very extensively by researchers and sci-entists around the world. Dr. Iyengar is an SIAM Distinguished Lecturer/ ACM National Lecturer/ IEEE Distinguished Scientist.

Dr. Iyengar is a Fellow of IEEE, Fellow of ACM, Fellow of AAAS and Fellow of SDPS. He is a recipient of IEEE awards, best paper awards, the Distinguished Alumnus award of the Indian Insti-tute of Science, Bangalore and other awards. He has served as the editor of several IEEE journals and is the founding editor-in-chief of the Interna-tional Journal of Distributed Sensor Networks.

His research has been funded by National Science Foundation (NSF), Defense Advanced Research Projects Agency (DARPA), Multi-University Re-search Initiative (MURI Program), Office of Naval Research (ONR), Department of Energy/Oak Ridge National Laboratory (DOE/ORNL), Naval Research Laboratory (NRL), National Aeronautics and Space Administration (NASA), US Army Research Office (URO) and various state agencies and companies. He has served on US National Sci-ence Foundation and National Institute of Health panels to review proposals in various aspects of computational science and has been involved as an external evaluator (ABET-accreditation) for several computer science and engineering departments.

Dr. Iyengar has supervised over 40 doctoral students, and the legacy of these students can be seen in prestigious laboratories (JPL, Oak Ridge National Lab, Los Alamos National Lab, Naval Research Lab) and universities round the world. He has been the program chairman of various international conferences and has given more than 50 keynote talks at international conferences.

Mark Allen Weiss Associate Director and Profes-sor, ECS 353Phone: 305-348-2036Email: [email protected]: cis.fiu.edu/~weiss

Mark Allen Weiss is professor and associate director for the School of Computing and Information Sciences at Florida Interna-tional University. He is also currently serving as director of undergraduate studies. He received his bachelor’s degree in electrical engineering from the Cooper Union in 1983, and his Ph.D. in computer science from Princeton University in

1987, working under Bob Sedgewick. He has been at FIU since 1987 and was promoted to professor in 1996. His interests include data structures, algorithms, and education. He is most well-known for his highly-acclaimed data structures textbooks, which have been used by a generation of students.

Professor Weiss is the author of numerous publica-tions in top-rated journals and was recipient of the University’s Excellence in Research Award in 1994. In 1996 at FIU he was the first in the world to teach data structures using the Java programming language, which is now the de facto standard. From 1997-2004 he served as a member of the Advanced Placement Computer Science Development Committee, chairing the committee from 2000-2004. The committee designed the cur-riculum and wrote the AP exams that were taken by 20,000 high school students annually.

In addition to his Research Award in 1994, Profes-sor Weiss is also the recipient of the University’s Excellence in Teaching Award in 1999, the School of Computing and Information Science Excel-lence in Teaching Award (2005) and Excellence in Service Award (2007), the FIU Top Scholar Award (2012). In 2011, he was honored as an ACM Distinguished Educator.

Research and Instructional Interests: algorithm design and analysis, computer science education

Selected Publications:

M. A. Weiss, Data Structures and Algorithm Analysis: twelve English-language editions in vari-ous programming languages published between 1992 and 2012 by Pearson.

M. A. Weiss, Data Structures and Problem Solv-ing: six English-language editions in C++ and Java published between 1996 and 2011 by Pearson.

M. A. Weiss, C++ for Java Programmers, 2004, Pearson.

Shu-Ching ChenGraduate Program Director and Professor, ECS 362Phone: 305-348-3480Email: [email protected]: cis.fiu.edu/~chens

Dr. Shu-Ching Chen is a professor in the School of Computing and Information Sciences, Florida International University, since August 2009. Prior to that, he was an assistant/associate professor in SCIS at FIU from 1999. He received Master’s degrees in computer science, electrical engineering, and civil engineering in 1992, 1995, and 1996, respectively, and the Ph.D. degree in electrical and computer engineering in 1998, all from Purdue University. He is the director of the Distributed Multimedia Information Systems Laboratory and associate director of The Center for Advanced Distributed System Engineering at SCIS. His main research in-terests include content-based image/video retrieval, distributed multimedia database management systems, multimedia data mining, multimedia systems, and disaster information management. Dr. Chen has authored and coauthored more than 240 research papers in journals, refereed conference/symposium/workshop proceedings, book chapters, and one book. Dr. Chen has been the PI/Co-PI of many research grants from NSF, National Oceanic and Atmospheric Administra-tion (NOAA), Department of Homeland Security,

Naval Research Laboratory (NRL), Florida Office of Insurance Regulation, and Florida Department of Transportation with a total amount of more than 17 million dollars.

Dr. Chen received the best paper award from 2006 IEEE International Symposium on Multimedia. He was awarded the IEEE Systems, Man, and Cybernetics (SMC) Society’s Outstanding Contri-bution Award in 2005 and was the co-recipient of the IEEE Most Active SMC Technical Committee Award in 2006. He was also awarded the Inaugural Excellence in Graduate Mentorship Award from FIU in 2006, the FIU Outstanding Faculty Research Award in 2004, the SCIS Excellence in Mentorship Award in 2010, the SCIS Outstanding Faculty Service Award in 2004, and the SCIS Out-standing Faculty Research Award in 2002. He has been a general chair and program chair for more than 35 conferences, symposiums, and workshops. He is the founding editor-in-chief of International Journal of Multimedia Data Engineering and Management and associate editor in 13 other jour-nals. He is the chair of IEEE Computer Society Technical Committee on Multimedia Computing and co-chair of IEEE Systems, Man, and Cyber-netics Society’s Technical Committee on Knowl-edge Acquisition in Intelligent Systems. Dr. Chen also has been a guest editor for more than ten journal special issues. He was a member of three steering committees (including IEEE Transactions on Multimedia) and several panels for conferences and NSF. He has also served as a member of the technical program committee for more than 200 professional meetings. He is a fellow of SIRI and an ACM Distinguished Scientist.

Research and Instructional Interests: distributed multimedia database systems, multimedia data mining, multimedia systems, GIS, disaster infor-mation management

Selected Publications:L. Lin, C. Chen, M.-L. Shyu, and S.-C. Chen. “Weighted Subspace Filtering and Ranking Algorithms for Video Concept Retrieval.” IEEE Multimedia, vol. 18, no. 3, pp. 32-43, July-Sep-tember 2011.

M.-L. Shyu, Z. Xie, M. Chen, and S.-C. Chen. “Video Semantic Event/Concept Detection Using a Subspace-based Multimedia Data Mining Frame-work.” IEEE Transactions on Multimedia, Special Issue on Multimedia Data Mining, vol. 10, no. 2, pp. 252-259, February 2008.

S.-C. Chen, S. H. Rubin, M.-L. Shyu, and C. Zhang. “A Dynamic User Concept Pattern Learning Framework for Content-Based Image Re-trieval.” IEEE Transactions on Systems, Man, and Cybernetics: Part C, vol. 36, issue 6, pp. 772-783, November 2006.

S.-C. Chen, M.-L. Shyu, S. Peeta, and C. Zhang. “Learning-Based Spatio-Temporal Vehicle Tracking and Indexing for Transportation Multimedia Da-tabase Systems.” IEEE Transactions on Intelligent Transportation Systems, vol. 4, no. 3, pp. 154-167, September 2003.

K. Zhang, S.-C. Chen, D. Whitman, M.-L. Shyu, J. Yan, and C. Zhang. “A Progressive Morphological Filter for Removing Non-Ground Measurements from Airborne LIDAR Data.” IEEE Transactions. on Geoscience and Remote Sensing, vol. 41, issue 4, pp. 872-882, April 2003.

faculty profiles

6 Florida International University • School of Computing and Information Sciences

Faculty Profiles: Tenure Track Professors

David Barton Professor, ECS 388Phone: 305-348-2032Email: [email protected]: cis.fiu.edu/~barton

Dr. Barton has worked in computer science related areas since 1963. In his early career, Dr. Barton began using the EDSAC 2 and more recently used the Blue Gene Computer. Dr. Barton began by de-veloping symbolic algebra systems for use in celestial mechanics and later worked on the operating system project for the Titan computer writing the command program for that machine which was a type of early Shell program.

Dr. Barton was awarded the Adams Prize at Cambridge University with J. P. Fitch in 1974. He worked on high speed data communication net-works for CERN in Geneva and later on numeri-cal techniques for stiff equations. Most recently Dr. Barton has been involved with F. K. Urban on the application of numerical and mathemati-cal techniques to the modeling of thin films for applications in microelectronics and possibly solar power technology.

After a distinguished thirty-year career at Florida In-ternational University, Prof. Barton announced his retirement at the end of the spring 2012 semester.

Bogdan CarbunarAssistant Professor, ECS 310Phone: 305-348-7566Email: [email protected]: cis.fiu.edu/~carbunar

Bogdan Carbunar is an assistant professor in the School of

Computing and Information Sciences at Florida International University. Before joining FIU he was a member of the technical staff in the Ap-plied Research Center at Motorola. His research interests include privacy and security in distributed systems, including online social networks and wireless networks. He has served on the program committee of conferences such as the Network and Distributed Systems Security Symposium (NDSS), the IEEE International Conference on Multimedia and Expo (ICME) and Financial Cryptography (FC). He holds a Ph.D. in computer science from Purdue University.

Research and Instructional Interests: security and privacy applied to distributed environments, including wireless and online social networks.

Selected Publications:B. Carbunar, Y. Yu, L. Shi, M. Pearce, and V. Vasudevan. “Query Privacy in Wireless Sensor Net-works.” ACM Transactions on Sensor Networks, vol. 6, issue 2, May 2010.

B. Carbunar, M. Pearce, S. Mohapatra, L. J. Rittle, and V. Vasudevan. “Byzantine Resilient Synchronization for Content and Presence Updates in MANETs.” in Proceedings of the 16th IEEE International Conference on Network Protocols, October 2008.

R. Sion, and B. Carbunar. “On the Compu-tational Practicality of Private Information Retrieval.” Proceedings of the 14th ISOC Network and Distributed Systems Security Symposium, February-March 2007.

Peter ClarkeAssociate Professor, ECS 212APhone: 305-348-2440Email: [email protected]: cis.fiu.edu/~clarkep

Dr. Peter J. Clarke received his B.S. in computer science

and mathematics in 1987 from the University of the West Indies, Cave Hill Campus, Barbados followed in 1993 by an Advanced Diploma in computer science. In 1996 Dr. Clarke earned his M.S. in Computer Science from Binghamton Uni-versity, SUNY and completed his formal education in 2003 with a Ph.D. in computer science from Clemson University, Clemson, South Carolina. In 2003, Dr. Clarke joined the School of Computing and Information Sciences at Florida International University, as an assistant professor and was pro-moted to associate professor in 2009.

Research and Instructional Interests: software testing, software metrics, software maintenance, model-driven software development

Selected Publications:Y. Wu, A. A. Allen, F. Hernandez, R. B. France, and P. J. Clarke. “A Domain-Specific Modeling Approach to Realizing User-Centric Communica-tion.” Journal of Software Practice and Experi-ence, doi: 10.1002/spe.1081, May 1, 2011.

P. J. Clarke, J. F. Power, D. Babich, and T. M. King. “A Testing Strategy for Abstract Classes.” Journal of Software Testing, Verification and Reli-ability, doi: 10.1002/stvr.429, March 11, 2010.

J. A. Morales, P. J. Clarke, and Y. Deng. “Identifi-cation of File Infecting Viruses through Detec-tion of Self-Reference Replication.” Journal in Computer Virology, Special Issue of EICAR, vol. 6, issue 2, pp. 161-180, May 2010.

P. J. Clarke, D. Babich, T. M. King, and B. M. G. Kibria. “Analyzing Clusters of Class Charac-teristics in OO Applications.” Journal of Systems and Software, vol.81, issue 12, pp. 2269-2286, December 2008.

P. J. Clarke, J. F. Power, D. Babich and T. M. King. “Intra-Class Testing of Abstract Class Features.” in Proceedings of the 18th IEEE International Symposium on Software Reliability Engineering, November, 2007, pp. 191-200.

Xudong HeProfessor, ECS 212BPhone: 305-348-1831Email: [email protected]: cis.fiu.edu/~hex

Xudong He received the B.S. and M.S. degrees in computer

science from Nanjing University, China, in 1982 and 1984, respectively. He received the Ph.D. in computer science from Virginia Tech in 1989. He joined the faculty in the School of Computing and Information Sciences at Florida International University in 2000, and is professor of SCIS and the director of the Center for Advanced Distributed System Engineering. Prior to joining FIU, he was an associate professor in the Depart-ment of Computer Science at North Dakota State University since 1989. His research interests include formal methods, especially Petri nets, and software testing techniques. He has published over 125 papers in the above areas. He was ranked among the top 15 scholars in systems and software engineering worldwide between 1999 and 2003 by

Journal of Systems and Software. His research has been funded by the NSF, ONR, NASA, and DOE. He has been the major advisor of 12 Ph.D. and 36 M.S. graduates. Dr. He is a senior member of the Association for Computing Machinery, and a senior member of the IEEE Computer Society.

Research and Instructional Interests: software engineering, software testing, formal specification and verification, Petri nets

Selected Publications:X. He, H. Yu, T. Shi, J. Ding, and Y. Deng. “Formally Analyzing Software Architectural Specifications Using SAM.” Journal of Systems and Software, vol.71, no.1-2, pp. 11-29, 2004.

H. Zhu and X. He. “A Methodology for Testing High-Level Petri Nets.” Information and Software Technology, vol. 44, pp. 473-489, 2002.

D. Xu, X. He, and Y. Deng. “Schedulability Analysis of Real-Time Systems Using Time Petri Nets.” IEEE Transaction on Software Engineering, vol. 28, no. 10, pp. 984-996, 2002.

X. He and Y. Deng. “A Framework for Developing and Analyzing Software Architecture Specifications in SAM.” The Computer Journal, vol. 45, no. 1, pp. 111-128, 2002.

X. He. “PZ Nets - A Formal Method Integrating Petri Nets with Z.” Information and Software Technology, vol. 43, no. 1, pp. 1-18, 2001.

Vagelis HristidisAssociate ProfessorEmail: [email protected]: cis.fiu.edu/~vagelis

Dr. Hristidis received his Ph.D. in computer science from University of California, San

Diego in 2004 and his areas of expertise are data-bases, information retrieval, and in particular, the intersection of these two areas. Dr. Hristidis has a vision to make the information in databases easily accessible and useful across various application domains. His research emphasizes interdisciplin-ary topics, mainly health informatics and disaster management. Dr. Hristidis is the recipient of the prestigious NSF CAREER Award, the Google Re-search Award, the IBM Scalable Data Analytics for A Smarter Planet Innovation Award, the FIU SCIS Excellence in Research Award, the FIU University Faculty Award and the Kauffmann Entrepreneur-ship Award. Recently, Dr. Hristidis founded PatentsSearcher.com, a patent search engine, to help faculty as they work to commercialize their research.

Research and Instructional Interests: informa-tion discovery, data sharing, disaster management, presentation and navigation of query results, XML storage and parsing

Jong-Hoon KimVisiting Assistant Professor, ECS 231Phone: 305-348-3751Email: [email protected]: cis.fiu.edu/~kimj

Dr. Kim is currently a visiting assistant professor in the School of Computing and Information Sciences, Florida International University. He received a B.S. from Seoul National University of Science and Technology, Seoul, South Korea in

7Florida International University • School of Computing and Information Sciences

2005. He received a M.S. and Ph.D. in com-puter science from the Department of Computer Science at Louisiana State University at Baton Rouge in 2008 and in 2011 respectively. His research interests are in mobile robotics, embedded systems, sensor networks, and intelligent systems. Currently, his research in intelligent home systems (IHS) focuses on the quality of life and security while providing solutions that increase comfort and entertainment. These systems will at the same time provide enhanced security and improved energy efficiency.

Tao LiAssociate Professor, ECS 318,Phone: 305-348-6036Email: [email protected]: cis.fiu.edu/~taoli

Dr. Tao Li is currently an as-sociate professor in the School

of Computing and Information Sciences at Florida International University. He received his Ph.D. in computer science from the Department of Computer Science, University of Rochester in July 2004. His research interests are in data mining, machine learning, information retrieval, and bioinformatics. He is the recipient of NSF CA-REER Award (2006-2011), multiple IBM Faculty Research Awards (2005, 2007 & 2008), and Xerox Research Awards (2005-2008 & 2011-2014). He has published prolifically in top journals and conferences and has served on the program com-mittees of many international conferences.

Research and Instructional Interests: data mining, machine learning, information retrieval, bioinfor-matics

Selected Publications:D. Wang, S. Zhu, T. Li, Y. Chi, and Y. Gong. “Integrating Document Clustering and Multi-Document Summarization.” ACM Transactions on Knowledge Discovery from Data, vol. 5, no. 3, article 14, 2011.

C. Ding, T. Li, and M. I. Jordan. “Convex and Semi-Nonnegative Matrix Factorizations.” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 1, pp. 45-55, 2010.

T. Li, C. Ding, Y. Zhang, and B. Shao. “Knowl-edge Transformation from Word Space to Docu-ment Space.” in Proceedings of the 31st Annual International ACM SIGIR Conference, 2008, pp. 187-194.

T. Li. “A Unified View on Clustering Binary Data.” Machine Learning, vol. 62, no. 3, pp. 199-215, 2006.

T. Li and M. Ogihara. “Towards Intelligent Music Retrieval.” IEEE Transactions on Multimedia, vol. 8, no. 3, pp. 564-574, 2006.

Christine LisettiAssociate Professor, ECS 361Phone: 305-348-6242Email: [email protected]: cis.fiu.edu/~lisetti

Dr. Christine Lætitia Lisetti is an associate professor in the

School of Computing and Information Sciences at Florida International University, and the director of the Affective Social Computing Laboratory (ascl.cs.fiu.edu). She received her Ph.D. in com-

puter science from Florida International University in 1995, and in 1996 she was awarded the Indi-vidual Research Award from the National Institute of Health (NIH) to conduct her Post-Doctoral Fellowship at Stanford University, jointly in com-puter science and psychology. She joined FIU from ENST/Sophia, France where she was a professor, and was previously an assistant professor in the Computer Science Department at the University of Central Florida.

Dr. Lisetti’s work on affective social computing aims at creating digital and engaging socially intelligent agents that can interact naturally with humans via expressive multi-modalities in a variety of contexts involving socio-emotional content. Her interests involve research on virtual characters for health communication and behavior change. While in Europe, her research was supported by grants from the European Commission (EC), EUREKA In-formation Technology for European Advancement (ITEA), the Provence-Alpes Cote d’Azur (PACA) Regional R&D Program, and ST Microelectron-ics. Dr. Lisetti has received funding from Interval Research Corporation, Intel Corporation, Vcom3D, as well as from Federal funding agencies including the Office of Naval Research (ONR), US Army STRICOM, NASA Ames, the National Institute of Health (NIH), and the National Science Founda-tion (NSF).

Christine Lisetti is on the Editorial Board of the IEEE Transactions on Affective Computing, the first journal in her field of research which launched in 2010. She is the recipient of the 2000 AAAI Nils Nilsson Award, and the author of numerous sci-entific articles. She has served on various program committees of international conferences, she has co-chaired several international events on affective computing, and has been an invited speaker at international conferences. Dr. Lisetti has served as a research expert for the National Science Foundation (USA), for the “Agence Nationale de la Recherche” (FRANCE), for the “Fonds de Recherche sur la Nature et les Technologies” (CANADA), and for the European Commission (BELGIUM).

Research and Instructional Interests: affective computing, human-computer interaction, artificial intelligence, health informatics

Selected Publications:F. Nasoz, C. L. Lisetti, and T. Vasilakos. “Affectively Intelligent and Adaptive Car Interfaces.” Informa-tion Sciences Journal, vol. 180, pp. 3817-3836, 2010.

C. L. Lisetti. “Features for Culturally Appropriate Avatars for Behavior-Change Promotion in At-Risk Population.” Studies in Health Technology and Informatics. vol. 144, pp. 22-26, 2009.

F. Nasoz and C. L. Lisetti. “MAUI Avatars: Mir-roring the User’s Sensed Emotions via Expressive Multi-ethnic Facial Avatars.” Journal of Visual Languages and Computing, vol. 17, issue 5, pp. 430-444, 2006.

C. L. Lisetti and F. Nasoz. “Using Noninvasive Wearable Computers to Recognize Human Emo-tions from Physiological Signals.” EURASIP Journal on Applied Signal Processing, vol. 11, pp. 1672-1687, 2004.

C. L. Lisetti, S. Brown, K. Alvarez, and A. Marpaung. “A Social Informatics Approach to Human-Robot Interaction with a Service Social Robot.” IEEE Transactions on Systems, Man, and Cybernetics, vol. 34, issue 2, pp. 195-209, 2004.

Jason LiuAssociate Professor, ECS 261BPhone: 305-348-1625Email: [email protected]: cis.fiu.edu/~liux

Jason Liu is currently an associ-ate professor at Florida Interna-

tional University. He received a B.A. in computer science from Beijing University of Technology in China in 1993, an M.S. in Computer Science from College of William and Mary in 2000, and a Ph.D. in Computer Science from Dartmouth Col-lege in 2003. His research interests include parallel discrete-event simulation, high-performance modeling and simulation of communication networks and computer systems. His current re-search focuses on applying real-time computation techniques for adaptive network simulation model-ing, designing and building scalable emulation infrastructure for large-scale network experiments. Dr. Liu currently serves as a steering commit-tee member for the PADS conference and as an associate editor for the SIMULATIONS journal. He was the general chair for MASCOTS’10 and SIMUTools’11, and the program chair for SIMU-Tools’10 and PADS’08. He served on the technical committees for many conferences. In 2006, he received an NSF CAREER Award.

Research and Instructional Interests: model-ing and simulation, computer networks, parallel computing, parallel discrete event simulation, high-performance simulation and modeling of large-scale communication networks

Selected Publications:N. Van Vorst, T. Li, and J. Liu. “How Low Can You Go? Spherical Routing for Scalable Network Simulations,” presented at the 19th Annual Meeting of the IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS’11), Singapore, July 25-27, 2011.

N. Van Vorst, M. Erazo, and J. Liu. “PrimoGENI: Integrating Real-Time Network Simulation and Emulation in GENI,” presented at the 25th Workshop on Principles of Advanced and Distrib-uted Simulation (PADS’11), Nice, France, June 14-17, 2011.

M. Erazo, Y. Li, and J. Liu. “ SVEET! A Scalable Virtualized Evaluation Environment for TCP,” presented at the 5th International Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities (Tri-dentCom’09), Washington, DC, April 6-8, 2009.

T. Li and J. Liu. “A Fluid Background Traffic Model,” presented at the IEEE International Con-ference on Communications (ICC’09), Dresden, Germany, June 14-18, 2009.

Y. Li, J. Liu, and R. Rangaswami. “Real-time network simulation support for scalable routing ex-periments.” in Proceedings of the 22nd Workshop on Principles of Advanced and Distributed Simula-tion, Rome, Italy, June 3-6, 2008, pp. 23-30.

Masoud MilaniAssociate Professor and Director for the Office of Student Access and Success, ECS 365Phone: 305-348-2925Email: [email protected]: cis.fiu.edu/~milani

faculty profiles


Dr. Milani joined Florida International University after receiving his Ph.D. in computer science from the University of Central Florida in 1985. In the last 25 years he has been a faculty at the School of Computing and Information Sciences and has served the University in different roles, including associate dean of the School of Computing and Information Sciences, director of the Information Technology Program, and director of External Programs.

Dr. Milani is currently the founding director of the Office of Student Access and Success. The mission of this new Office is to provide prospective and assistance to current students of the College of Engineering and Computing at FIU with value chain opportunities and services that will enhance their academic experiences and increase their rate of success in the school and their future careers. The Office supports students through recruit-ment, retention and enrichment programs, such as mentorship, undergraduate research opportunities, peer-to-peer tutoring, internship, and pre-college outreach activities.

Dr. Milani’s work in engaging students in research and providing scholarships and fellowships to undergraduate and graduate students has been supported by US Department of Education and the National Science Foundation.

Research and Instructional Interests: theory of computation, software engineering, computer science education

Selected Publication:M. Milani, S. M. Sadjadi, R. Rangaswami, P. J. Clarke and T. Li. “Research Experiences for Undergraduates: Autonomic Computing Research at FIU.” in Proceedings of the Fifth Richard Tapia Celebration of Diversity in Computing Confer-ence, April 1-4, 2009, pp. 93-97.

Giri NarasimhanProfessor and Associate Dean for Research and Graduate Studies ECS 254Phone: 305-348-3748Email: [email protected]: cis.fiu.edu/~giri

Dr. Narasimhan is currently professor in the School of Computing and Information Sciences at Florida International University and also serves as associate dean for Research and Graduate Studies for the College of Engineering. Dr. Narasimhan completed his undergraduate studies in 1982 with a Bachelor in Technology degree in electrical engineering from the Indian Institute of Technology in Bombay. In 1989 he was awarded a Ph.D. in computer science from the University of Wisconsin, Madison and from there accepted an associate professor position at the University of Memphis in the Department of Mathematical Sci-ences. Dr. Narasimhan joined Florida International University as an associate professor in 2001 and was promoted to full professor in 2004.

Research and Instructional Interests: bioinformat-ics, algorithms, computational geometry

Selected Publications:J. Gudmundsson, C. Levcopoulos, G. Narasim-han, and M. Smid. “Approximate Distance Oracles for Geometric Spanners,” ACM Transactions on Algorithms, vol. 4, issue 1, article 10, 2008.

K. Mathee, G. Narasimhan, C. Valdes, X. Qiu,

J. M. Matewish, M. Koehrsen, A. Rokas, C. N. Yandava, R. Engels, E. Zeng, R. Olavarietta, M. Doud, R. S. Smith, P. Montgomery, J. R. White, P. A. Godfrey, C. Kodira, B. Birren, J. E. Galagan, and S. Lory. “Dynamics of Pseudomonas aeruginosa genome evolution.” in Proceedings of the National Academy of Sciences, vol. 105, issue 8, pp. 3100-05, 2008. Reviews: (a) Highlighted by Genome Technology Online, Feb 20, 2008, Survival through genome shapeshifting, and (b) Reviewed by Faculty of 1000 Biology.

G. Narasimhan and Michiel Smid. Geometric Spanner Networks, Research Monograph. Cam-bridge University Press, 2007.

V. Renugopalakrishnan, R. Garduno-Juarez, G. Narasimhan, C. S. Verma, X. Wei, and P. Li. “Rational design of thermally stable proteins: Relevance to bionanotechnology.” Journal of Nanoscience and Nanotechnology, vol. 5, issue 11, pp. 1759-67, 2005.

Jainendra K. NavlakhaProfessor, ECS 384Phone: 305-348-2026Email: [email protected]: cis.fiu.edu/~navlakha

Dr. Jai Navlakha received his Ph.D. in computer engineering

and information sciences from Case Western Re-serve University in Cleveland, Ohio in December 1977. Since then, he has been employed at Florida International University, where he was promoted to the position of full professor in September 1987. He served as the director of the School of Computer Science in three stints: August 1988 to August 1992, August 1999 to August 2002, and July 2009 to August 2011. From July 2006 to June 2009, he was the associate dean of Graduate Studies and the Director of Corporate & Global Programs in the College of Engineering & Com-puting.

He has published more than 30 articles in national and international journals and has presented his work at major conferences in computer science.

Research and Educational Interests: expert systems and neural networks, software engineer-ing and software metrics, design and analysis of algorithms, software cost estimations, databases

Selected Publications:J. Navlakha, “Economic Prosperity through Education: Lessons to be learned from an Indian Experiment,” 5th Latin American and Caribbean Conference for Engineering and Technology, May 29-June 1, 2007.

J. Navlakha, “Research trends in computer science: a case for computing as an enabling force,” Invited paper presented at IPSI 2003 in Montenegro, October 2003.

Deng PanAssistant Professor, ECS 261APhone: 305-348-7567Email: [email protected]: cis.fiu.edu/~pand

Dr. Deng Pan received his Ph.D. degree in computer science from State University of New York at Stony Brook in 2007. His research interests are generally in high perfor-

mance switch design and high speed networking. His current research focuses on switch virtu-alization, data center networking, and energy efficient networking. He has published over thirty peer-reviewed papers in leading refereed journals and conferences, including the IEEE Transac-tions on Computers, IEEE INFOCOM, ACM/IEEE Symposium on Networking and Com-munications, and IEEE International Parallel and Distributed Processing Symposium. He has served as local arrangement co-chair or technical program committee member in many interna-tional conferences, including IEEE INFOCOM, IEEE GLOBECOM, and ICPP. He also had in-dustry experience in VoIP software development, Linux kernel module development, and advanced software testing.

Research and Instructional Interests: high performance routers and switches, high speed networking, quality of service, network processors, network security

Selected Publications:H. Jin, D. Pan, J. Liu, and N. Pissinou. “Open-Flow based flow level bandwidth provisioning for CICQ switches,’’ presented at the IEEE Interna-tional Conference on Computer Communications (INFOCOM 2011) Mini-Conference, Shanghai, China, Apr. 2011.

D. Pan, K. Makki, and N. Pissinou. “Achieve con-stant performance guarantees using asynchronous crossbar scheduling without speedup,” presented at the IEEE International Parallel and Distributed Processing Symposium (IPDPS 2010), Atlanta, GA, Apr. 2010.

D. Pan, Z. Yang, K. Makki, and N. Pissinou. “Providing performance guarantees for buffered crossbar switches without speedup,’’ presented at the International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (QSHINE 2009), Las Palmas de Gran Canaria, Spain, Nov. 2009.

D. Pan and Y. Yang. “Localized independent packet scheduling for buffered crossbar switches,” IEEE Transactions on Computers, vol. 58, no. 2, pp. 260-274, Feb. 2009.

D. Pan and Y. Yang. “Providing flow based perfor-mance guarantees for buffered crossbar switches,’’ presented at the IEEE International Parallel and Distributed Processing Symposium (IPDPS 2008), Miami, FL, Apr. 2008.

Alex PelinAssociate Professor, ECS 383Phone: 305-348-3386Email: [email protected]: cis.fiu.edu/~pelina

Dr. Alex Pelin was awarded a B.S. in computer science and engineering from the University of Pennsylvania in 1973, an M.S. in computer and information sciences in 1974 and a Ph.D. in computer and information sciences in 1977, also from the University of Pennsylvania. After eight years on faculty at Temple University, Dr. Pelin joined the School of Computing and Information Sciences at Florida International University in 1985.

Research and Instructional Interests: artificial intelligence, logic, computer aided instruction, programming languages


Selected Publication:A. Pelin and J. H. Gallier, “Building exact compu-tation sequences,” Theoretical Computer Science, Volume 53, Issue 1, 1987, pp. 125-150,

Niki PissinouProfessor, ECS 359Phone: 305-348-3716Email: [email protected]: http://it2.fiu.edu/IT2_Faculty_Pissinou.htm

Dr. Pissinou has published over two hundred and fifty research papers in peer reviewed journals, conference proceedings and books chapters on networking, telecommunications, distributed systems, mobile computing, security and aspects of non traditional data management including co-editing over four texts in the area of mobile and wireless networking and systems and over fourteen IEEE and ACM conference volumes. Widely cited in books and research papers, her research has been funded by the National Science Foundation, Department of Homeland Security, Department of Defense, Department of Transportation, National Aeronautics and Space Administration, state governments and industry. Dr. Pissinou is the founding director of the Telecommunications and Information Technology Institute, founded in 2001 and funded by the State of Florida through a state appropriation. She is also the key architect of the Telecommunications and Information Technology M.S. program. She has graduated over nineteen Ph.D. students who now hold positions in academia, federal government and industry. Dr. Pissinou has served as the general and technical program chair on a variety of ACM and IEEE conferences. She also served in various capacities on hundreds IEEE and ACM conferences as general chair, technical committee chair, program committees, organizing committees, review panels, advisory boards, editorial boards etc. She also served as an editor of many journals including the IEEE Transactions on Data and Knowledge Engineering. She also has been the founder of many professional forums, including the ACM GIS. Dr. Pissinou has given keynote talks at various events and served as consultant to industry. Her achievements have been recognized by her peers, who have given her several awards and honors, including best paper awards.

Research and Instructional Interests: computer, communications and network systems

Selected Publications: C. Kamhou, N. Pissinou, K. Makki. “Game Theoretic Modeling and Evolution of Trust in Autonomous Multi-Hop Networks: Application to Network Security and Privacy,” in Proceedings of the IEEE International Conference on Communi-cations, June 2011.

S. Pumpichet, N. Pissinou. “Virtual Sensor for Mobile Sensor Data Cleaning,” in Proceedings of the IEEE Global Communications Conference, December 2010.

Q. Wan, Z. Chen, C. Chen, N. Pissinou. “On the Robustness of the botner Formed by Worm Infec-tion,” in Proceedings for the IEEE Global Com-munications Conference, December 2007.

H. Liu, X. Jia, P. Wan, C. Yi, K. Makki, N. Pis-sinou. “Maximizing lifetime of sensor surveillance systems.” IEEE/ACM Transactions on Network-ing, vol. 15, no. 2, pp. 334-345, 2007.

G. Crosby, N. Pissinou. “Evolution of Coopera-tion in Multi-Class Wireless Sensor Networks,” in Proceedings of the IEEE Conference on Local Computer Networks, October 2007.

Nagarajan PrabakarAssociate Professor, ECS 382Phone: 305-348-2033Email: [email protected]: cis.fiu.edu/~prabakar

Dr. Prabakar developed a scheme to access vast amount of spatial data from a semantic database and flyover the data in real-time – this emerged as TerraFly software from High Per-formance Database Research Center, FIU. He has also designed dynamic mosaicking algorithms for spatial images and integrated vector GIS data with spatial data sets. Towards external funding, seven grant proposals were funded for a total amount of $2.3M with Dr. Prabakar’s role in these proposals as Principal Investigator, Co-Investigator, or Senior Investigator. Currently, Dr. Prabakar is working with a team of his colleagues on a fault-tolerant distributed computing grid with large number of sensors.

Research and Instructional Interests: sensor networks, grid computing, applications of database and image processing for spatial data

Selected Publications:R. Rangaswami, S .M. Sadjadi, N. Prabakar, and Y. Deng. “Automatic generation of user-centric multimedia communication services.” in Proceed-ings of the 26th IEEE International Performance Computing and Communications Conference (IPCCC), New Orleans, April 2007.

V. Hristidis, P. J. Clarke, N. Prabakar, Y. Deng, J. A. White, and R. P. Burke. “A Flexible Ap-proach for Electronic Medical Records Exchange.” Proceedings of the International Workshop on Health Information and Knowledge Management (HIKM), in conjunction with ACM CIKM, pp. 33-40, 2006.

Y. Deng, S. M. Sadjadi, P. J. Clarke, C. Zhang, V. Hristidis, R. Rangaswami, and N. Prabakar. “A communication virtual machine.” in Proceedings of the 30th Annual International Computer Soft-ware and Applications Conference (COMPSAC 2006), Chicago, pp. 521-531, September 2006.

P. J. Clarke, V. Hristidis, Y. Wang, N. Prabakar, and Y. Deng. “A Declarative Approach for Specify-ing User-Centric Communication.” Proceedings of the International Symposium on Collaborative Technologies and Systems (CTS 2006), Las Vegas, pp. 89-98, May 2006.

G. Paschos, I. Radev, and N. Prabakar. “Image Content-Based Retrieval Using Chromaticity Moments.” IEEE Transactions on Knowledge and Data Engineering, vol. 15, issue 5, pp. 1069-1072, 2003.

Raju RangaswamiAssociate Professor, ECS 386Phone: 305-348-6230Email: [email protected]: cis.fiu.edu/~raju

Professor Raju Rangaswami re-ceived a B.Tech. degree in computer science from the Indian Institute of Technology, Kharagpur,

India, and M.S. and Ph.D. degrees also in com-puter science from the University of California, Santa Barbara. At Florida International University, he leads the Systems Research Laboratory (http://sylab.cs.fiu.edu). His research interests include operating systems, storage systems, virtualization, security, and real-time systems. He is a recipient of the NSF CAREER Award and the Department of Energy Early CAREER Award as well as various awards from industry including an IBM Faculty Award and a NetApp Faculty Fellowship.

Research and Instructional Interests: operating systems, storage systems, virtualization, real-time systems, computer security

Selected Publications:J. Guerra, H. Pucha, J. Glider, W. Belluomini, and R. Rangaswami. “Cost Effective Storage using Extent Based Dynamic Tiering,” in Proceedings of the USENIX Conference on File and Storage Technologies, February, 2011.

R. Koller and R. Rangaswami. “I/O Deduplica-tion: Utilizing Content Similarity to Improve I/O Performance,” in Proceedings of the USENIX Conference on File and Storage Technologies, February, 2010.

S. Kundu, R. Rangaswami, K. Dutta, and M. Zhao. “Application Performance Modeling in a Virtualized Environment,” in Proceedings of the IEEE High-Performance Computer Architecture, January, 2010.

M. Bhadkamkar, J. Guerra, L. Useche, S. Burnett, J. Liptak, R. Rangaswami, and V. Hristidis. “BORG: Block-reORGanization for Self-Optimiz-ing Storage Systems.” in Proceedings of the USE-NIX Conference on File and Storage Technologies, February, 2009.

Z. Dimitrijevic, R. Rangaswami, and E. Chang. “Design and Implementation of Semi-preemptible IO,” presented at USENIX File and Storage Tech-nologies, San Francisco, March 2003.

Naphtali David RisheProfessor, ECS 243Phone: 305-348-2025Email: [email protected]: cis.fiu.edu/~rishen

Dr. Rishe has authored three books on database design and geography and edited five books on database management and high performance computing. He has four U.S. patents on for inventions in the areas of database querying, semantic database performance, Internet data extraction, and computer medicine. Dr. Rishe has authored more than 300 papers in journals and proceedings on the topics of databases, software engineering, Geographic Information Systems, Internet, and life sciences and received awards of over $40 million in research grants by government agencies and industry, including NASA, NSF, IBM, DoI, USGS; Architect of major industrial projects. Dr. Rishe is the founder and director of the High Performance Database Research Center at FIU (HPDRC); director of the NSF Center for Research Excellence in Science and Technology at FIU (CREST) and of the NSF International FIU-FAU-Dubna Industry-University Cooperative Research Center for Advanced Knowledge Enable-ment (I/UCRC). He has mentored 70 postdocs, Ph.D. and M.S. candidates and received the inaugural FIU Outstanding University Professor

faculty profiles


award. Rishe’s TerraFly project has been extensively covered by worldwide press, including the New York Times, USA Today, NPR, Science and Nature journals, and FOX TV News.

Research and Instructional Interests: semantic da-tabase management, semantic wrapper of relational databases, Terrafly and web based GIS

Selected Publications:P. Sistla, O. Wolfson, B. Xu, and N. Rishe. “Answer-Pairs and Processing of Continuous Nearest-Neighbor Queries,” in Proceedings of the 2011 The Seventh ACM SIGACT/SIGMOBILE International Workshop on Foundations of Mobile Computing (FOMC 2011), San Jose, California, Jun. 9, 2011.

A. Cary, O. Wolfson, and N. Rishe. “Efficient and Scalable Method for Processing Top-k Spatial Bool-ean Queries.” in Proceedings of 22nd International Conference on Scientific and Statistical Database Management. Lecture Notes in Computer Science, vol. 6187, pp. 87-95, 2010.

A. Cary, Y. Yesha, M. Adjouadi, and N. Rishe. “Leveraging Cloud Computing in Geodatabase Management,” in Proceedings of the 2010 IEEE Conference on Granular Computing (GrC-2010), Silicon Valley, Aug. 2010, pp. 73-78.

Z. Sun, T. Li, and N. Rishe. “Large-Scale Matrix Factorization using MapReduce,” in Proceedings of the 2010 IEEE International Conference on Data Mining, Sydney, Dec. 2010, pp, 1242-1248.

P. Szczurek, B. Xu, O. Wolfson, J. Lin and N. Rishe. “Prioritizing Travel Time Reports in Peer-to-Peer Traffic Dissemination,” in Proceedings of the IEEE International Symposium on Com-munication Systems, Networks and Digital Signal Processing (7th CSNDSP), Newcastle, U.K., Jul. 2010, pp. 454-458.

S. Masoud SadjadiAssociate Professor, ECS 212CPhone: 305-348-1835Email: [email protected]: cis.fiu.edu/~sadjadi

Masoud Sadjadi received the B.S. degree in hardware engineering in 1995, the M.S. degree in software engineering in 1999, and the Ph.D. degree in computer science from Michigan State University in 2004. Dr. Sadjadi is currently an associate professor in the School of Computing and Information Sciences at Florida International University, where he has been on the faculty since 2004. He is the director of the Center of Partnership for International Research & Education (PIRE) funded by the National Science Foundation for $2.3 million. He is also the director of the Autonomic Cloud Research Laboratory (ACRL) and leads several projects under the Latin American Grid initiative. He has extensive experience in software development and leading large scale software engineering projects both in industry and in academia. Currently, he is collaborating with top researchers in 8 countries and is leading several international collaborative research projects. He is serving as a general chair of SEKE 2012 and has served as the program chair, co-chair, and committee member of several top-tier international conferences and workshops of his field. He has served as a referee for several IEEE and SP&E journals and as a referee and panelist for several funding agencies including National

Science Foundation (NSF), Luxembourg National Research Fund (FNR), and Florida Sea Grant. He has more than 80 refereed publications and is PI or Co-PI of 17 grants from NSF, IBM, Kaseya, TeraGrid, and FIU totalling approximately $6 mil-lion. Dr. Sadjadi is a member of the IEEE.

Research and Instructional Interests: distributed systems, software engineering, autonomic comput-ing, high-performance computing, grid comput-ing, cloud computing, pervasive systems, mobile computing

Selected Publications:S. M. Sadjadi, P. K. McKinley, and B. H. C. Cheng. “Adaptive Control Approach for Software Quality Improvement” in Transparent Shaping: A Methodology for Adding Adaptive Behavior to Existing Software Systems and Applications. World Scientific & Imperial College Press, 2011, 99. 77-113.

D. Villegas, I. Rodero, L. Fong, N. Bobroff, Y. Liu, M. Parashar, and S. M. Sadjadi. “The Role of Grid Computing Technologies” in Cloud Comput-ing Handbook of Cloud Computing. B. Furht, Ed.New York: Springer, 2010, pp. 183-218.

O. Ezenwoye, M. B. Blake, G. Dasgupta, L. Fong, S. Kalayci, and S. M. Sadjadi. “Managing faults for distributed workflows over grids.” The IEEE Inter-net Computing, vol. 14, issue 2, pp. 84-88, 2010.

I. Rodero, F. Guimb, J. Corbalan, L. Fong, and S. M. Sadjadi. “Grid broker selection strategies using aggregated resource information.” The Future Generation Computer Systems, vol. 26, issue 1, pp. 72-86, Jan. 2010.

P. K. McKinley, S. M. Sadjadi, E. P. Kasten, and B. H. C. Cheng. “Composing adaptive software”. Computer, vol. 37, issue 7, pp. 56-64, Jul. 2004.

Geoffrey SmithAssociate Professor, ECS 320Phone: 305-348-6037Email: [email protected]: cis.fiu.edu/~smithg

Geoffrey Smith completed his Ph.D. in computer science in 1991 at Cornell University. After three years as an assistant profes-sor at American University, in 1994 he came to SCIS at FIU, where he is now an associate professor. He has twice been a visiting scientist at the LIX laboratory of the Ecole Polytechnique in Palaiseau, France (June 2009 and September to December 2011). His research areas include computer security, programming languages and semantics, and theoretical computer science. In recent years his main focus has been on secure information flow and quantitative information flow. His work in secure information flow has been quite influential; for instance his 1996 Journal of Computer Security paper has been cited 677 times, and his 2009 FOSSACS paper has been cited 70 times, according to Google Scholar. He has been supported as PI by five NSF grants.

Research and Instructional Interests: theory of programming languages (formal semantics, type systems), computer security (secure information flow, language-based security, applied cryptogra-phy), automata theory (minimal NFAs)

Selected Publications:B. Köpf and G. Smith. “Vulnerability Bounds and Leakage Resilience of Blinded Cryptography under

Timing Attacks,” in Proceedings CSF 2010: 23rd IEEE Computer Security Foundations Sympo-sium, Edinburgh, UK, July 2010, pp. 44-56.

G. Smith. “On the Foundations of Quantitative Information Flow,” in Proceedings FOSSACS 2009: Twelfth International Conference on Foun-dations of Software Science and Computation Structures, LNCS 5504, pp. 288-302, York, UK, March 2009.

G. Smith. “Improved Typings for Probabilistic Noninterference in a Multi-Threaded Language.” Journal of Computer Security, vol. 14, issue 6, pp. 591-623, Dec. 2006.

G. Smith and D. Volpano. “Secure Information Flow in a Multi-threaded Imperative Language,” in Proceedings 25th ACM Symposium on Principles of Programming Languages, San Diego, California, January 1998, pp. 355-364.

D. Volpano, G. Smith and C. Irvine. ”A Sound Type System for Secure Flow Analysis,” Journal of Computer Security, vol. 4, issue 3, pp. 167-187, Dec. 1996.

Jinpeng WeiAssistant Professor, ECS 389Phone: 305-348-4038Email: [email protected]: cis.fiu.edu/~weijp

Jinpeng Wei received a Ph.D. in computer science from Georgia Institute of Technology in 2009. He is currently an assistant professor in the School of Computing and Informa-tion Sciences. His research spans stealthy malware detection and defense, operating systems security, cloud computing security, information flow security in distributed systems, and file-based race condi-tion vulnerabilities. He is the winner of three best paper awards, and his research is sponsored by the Department of Homeland Security and the Centre for Strategic Infocomm Technologies, Singapore. In addition to his research activities, he has also served on the Program Committee of top international conferences such as ICDCS 2011, and served as reviewer for top journals such as ACM Transactions on Computer Systems, Elsevier Journal of Comput-ers and Security, the IEEE Network magazine, and the IEEE Communications Magazine.

Research and Instructional Interests: computer systems security, dependable systems, software secu-rity, malware detection and mitigation, information flow, cloud computing, operating systems

Selected Publications: J. Wei, F. Zhu, and Y. Shinjo. “Static Analysis Based Invariant Detection for Commodity Operating Systems,” in Proceedings of the 7th International Conference on Collaborative Computing (Collabo-rateCom 2011), Orlando, FL, October 15-18, 2011.

J. Wei and C. Pu. “Modeling and Preventing TOCTTOU Vulnerabilities in Unix-Style File Sys-tems.” Journal of Computers and Security, vol.29, issue 8, pp. 815-830, Nov. 2010.

J. Wei, B. D. Payne, J. Giffin, and C. Pu. “Soft-Timer Driven Transient Kernel Control Flow Attacks and Defense,” in Proceedings of the 24th Annual Computer Security Applications Confer-ence (ACSAC’2008), Anaheim, CA, December 8-12, 2008.

J. Wei and C. Pu. “Multiprocessors May Reduce


System Dependability under File-Based Race Condi-tion Attacks,” in Proceedings of the 37th Annual IEEE/IFIP International Conference on Depend-able Systems and Networks (DSN’07), Edinburgh, UK, June 25 - 28, 2007.

J. Wei and C. Pu. “TOCTTOU Vulnerabilities in UNIX-Style File Systems: An Anatomical Study,” in Proceedings of the 4th USENIX Conference on File and Storage Technologies (FAST’05), San Francisco, CA, December 2005.

Ming ZhaoAssistant Professor, ECS 363Phone: 305-348-2034Email: [email protected]: cis.fiu.edu/~zhaom

Ming Zhao is an assistant professor in the School of Computing and Information Sciences at Florida International University, where he directs the research labora-tory for Virtualized Infrastructure, Systems, and Applications (VISA). He holds a Bachelor’s degree and a Master’s degree both in automation from Tsinghua University, Beijing, China and a Ph.D. in computer engineering from the University of Florida, Gainesville. His interdisciplinary work often involves bridging computer systems research with other domains such as computational sci-ences, medicine, and business. His research has been funded by the National Science Foundation, the Department of Homeland Security, and indus-try. He has published over 30 refereed articles in journals and conference proceedings, which have been cited more than 450 times. He won the Best Student Paper Award in the International Confer-ence on Autonomic Computing in 2007.

Research and Instructional Interests: virtualiza-tion, cloud computing, high-performance systems, autonomic computing

Selected Publications: Lixi Wang, Jing Xu, Ming Zhao, “Application-aware Cross-layer Virtual Machine Resource Management,” Proceedings of the 9th Interna-tional Conference on Autonomic Computing, September 2012.

Y. Xu, D. Arteaga, M. Zhao, Y. Liu, R. Figueiredo, S. Seelam, “vPFS: Virtualization-based Band-width Management for Parallel Storage Systems,” Proceedings of the 28th IEEE Conference on Massive Data Storage, April 2012.

L. Wang, J. Xu, M. Zhao, Y. Tu, and J. Fortes. “Fuzzy Modeling based Resource Management for Virtualized Database Systems,” in Proceedings of the 19th Annual Meeting of the IEEE Interna-tional Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Pages: 32-42, July 2011.

S. Adabala, V. Chadha, P. Chawla, R. Figueiredo, J. Fortes, I. Krsul, A. Matsunaga, M. Tsugawa, J. Zhang, M. Zhao, L. Zhu, and X. Zhu. “From Vir-tualized Resources to Virtual Computing Grids: the In-VIGO System,” Journal of Future Generation Computing Systems, vol. 21, no. 6, pp.896-909, Jun. 2005. (Authors are listed alphabetically)

Ming Zhao, Jian Zhang and Renato J. Figueiredo, “Distributed File System Support for Virtual Ma-chines in Grid Computing,” 13th IEEE Interna-tional Symposium on High Performance Distributed Computing, Pages: 202-211, June 2004.

Faculty Profiles: Instructors

Walid AkacheInstructor, ECS 312, Phone: 305-348-3731Email: [email protected]: cis.fiu.edu/~akachew

Walid Akache received his M.S., computer science, from the University of Miami in 1984. He also received his M.S. in mathematics from the American University of Beirut in 1970. Walid Akache has been an instructor in the School of Computing and Information Sciences at Florida International University since 1990. Walid Akache has reviewed numerous textbooks in support of computer science courses at FIU.

Research and Instructional Interests: introduc-tion to microcomputers, microcomputer applica-tions, Visual Basic, Pascal, VAX Basic

Tim DowneySenior Instructor, ECS 316Phone: 305-348-3329Email: [email protected]: cis.fiu.edu/~downeyt

Tim Downey earned Master’s degrees in mathematics and computer science. He has been teaching at FIU since 2001. In that time, he has earned three University wide teaching awards (2007, 2002, 1997), one College teaching award (2007) and two School teaching awards (2006, 2002). He is the author of a book on web design using Java.

Tim Downey has attended many conferences on computer science education. These conferences have stimulated his teaching style over the years. He is always open to learning new ways to enhance the learning process.

Research and Instructional Interests: web devel-opment, computer science eduation

Selected Publication: T. Downey. Web Development with Java: Using Hibernate, JSPs and Servlets. NJ, Springer, 2007.

Kip IrvineSenior Instructor, ECS 360Phone: 305-348-1528Email: [email protected]: cis.fiu.edu/~irvinek

Dr. Kip Irvine is a senior instructor at the School of Computing and Infor-mation Sciences, Florida International University (2000-present). He holds an M.S. in computer science and a doctor of musical arts, both from University of Miami. He was a professor of Com-puter Information Systems at Miami-Dade College from 1983-1999. He has published five computer programming textbooks in the following areas: Intel Assembly Language, C++, Visual Basic, and COBOL, with Prentice-Hall and Addison-Wesley. He is a recent recipient of the Excellence in Service Award (2008) and Excellence in Teaching Award (2010) from the FIU School of Computing and Information Sciences. He is a senior member of ACM (Association for Computing Machinery).

Research and Instructional Interests: Intel as-sembly language, desktop and web application

programming, competition programming, and object-oriented programming.

Selected Publications: K. R. Irvine. Assembly Language for Intel-Based Computers. Prentice-Hall, Pearson Education, 1999, 2003, 2006.K. R. Irvine, and T. Gaddis. Starting out with Visual Basic 2008. Addison Wesley Higher Educa-tion, 2006, 2008.K. R. Irvine, and T. Gaddis. Advanced Visual Basic 2005. Pearson/Addison Wesley, 2006.K. R. Irvine, T. Gaddis, and K. Liang. Advanced Visual Basic .NET. Scott/Jones, 2002, 2006.K. R. Irvine. C++ and Object-Oriented Program-ming. Prentice Hall, 1997.

Norman PestainaSenior Instructor, ECS 364Phone: 305-348-2013Email: [email protected]: cis.fiu.edu/~pestaina

Norman Pestaina is a senior instructor in the School of Computing and Infor-mation Sciences, having joined FIU as a Visiting instructor in the Department of Mathematical Sciences in August 1984. He holds the B.S. in mathematics from the University of the West Indies, and the M.S. in computer science from the Pennsylvania State University. Prior to joining FIU, Mr. Pestaina was lecturer in computer science at the Cave Hill campus of the UWI and, earlier, assistant staff member of the MIT Lincoln Labora-tory in Massachusetts.

Mr. Pestaina has taught 18 different courses at FIU and has been recognized for excellence in teaching on four occasions including an inaugural Teaching Incentive Program award in 1994. He has been an SCIS undergraduate advisor for 15 years, often representing the SCIS on College Curriculum Committees, and continues many years of service on the SCIS Undergraduate Com-mittee. A principal architect of the SCIS program assessment processes, Mr. Pestaina has been the SCIS Assessments Coordinator since 2006 and has led the BS-CS ABET re-accreditation efforts in 2004 and 2010. He has been a Reader or Question Leader of the College Board’s Advanced Placement Computer Science Exam since 2000.

Research and Instructional Interests: computer systems and organization, programming methodol-ogy, computer science education

Greg ShawSenior Instructor, ECS 313Phone: 305-348-1550Email: [email protected]: cis.fiu.edu/~shawg

Greg Shaw is a senior instructor in the School of Computing and Information Sci-ences. He was a visiting instructor for five years in the 1980s, and returned to FIU in 1995 as a per-manent faculty member. Greg earned an M.S. in computer science education from Barry University, and was the recipient of a University wide teaching award in 2003.

Research and Instructional Interests: introduc-tory and intermediate level programming courses

faculty profiles


Joslyn SmithInstructor, ECS 380Phone: 305-348-2015Email: [email protected]: cis.fiu.edu/~smithjo

Joslyn Smith, an instructor, joined the School of Computing and Information Sciences, Florida International University in 1997. Joslyn came to FIU with fourteen years of teach-ing experience from the University of the West Indies, as a lecturer in computer science, in the undergraduate program. Mr. Smith holds an M.S and a B.S in mathematics both from Central Con-necticut State University, CT. He earned an M.S degree in computer science from the University of New Brunswick Canada, and a non-degree Certifi-cate in computer science from Clarke University, Massachusetts. Mr. Smith also holds a professional certificate in teacher education from the Mico University College, Jamaica.

At FIU, Mr. Smith’s major focus in programming language is the object oriented paradigm. Over the years he has attended many conferences on computer science education. He has served as reviewer for the SIGCSE Technical Symposium on Computer Science Education and has reviewed several manuscripts for major publishers such as McGraw Hill and Prentice Hall.

Research and Instructional Interests: program-ming languages, object oriented programming, graphical user interface programming.

Tiana SolisVisiting Instructor, ECS 381Phone: 305-348-1749Email: [email protected]: cis.fiu.edu/~tsolis

Tiana Solis is currently a visit-ing instructor at the School of Computing and Information Sciences. Prior to moving to Hawaii in 2007, she was an instructor and academic advisor for the School from 1994 to 2007. Ms. Solis taught different undergraduate courses and mentored sever-al FIU students participating in the Florida-Georgia Louis Stokes Alliance for Minority Participation (FGLSAMP). She is a past adviser of the Women in Computer Science (WICS) student club.

From 2008 to 2010, Ms. Solis was a programmer analyst at the Department of the Attorney General in Hawaii, a member of the team revamping the State Juvenile Justice Information System.

Research and Instructional Interests: software development, programming languages, computer ethics

Jill WeissSenior Instructor, ECS 385Phone: 305-348-1545Email: [email protected]: cis.fiu.edu/~jweiss

Professor Weiss received her M.S. in computer science education from Barry University in 1992, and has worked in the computer industry since 1985 in different capaci-ties, mostly in computer education. She has been involved in all facets of the computer industry, including hardware/software installation, repair, trouble shooting, consulting, programming, and (multi-unit) managing training centers for a major Fortune 100 retailer. Professor Weiss worked as a computer consultant/trainer for large companies such as Texaco, Burger King, Kodak, and Mo-torola, and has trained users from various county and government agencies.

Jill has been an instructor in the School of Computing and Information Sciences since 2002, having previously taught as both an adjunct for ten years, and then as a visiting instructor for three years. She primarily teaches the School’s service courses, and since 2000, she has provided World’s Ahead instruction to roughly 14,000 students. Professor Weiss was the recipient of the School of Computing and Information Science’s Excellence in Teaching award in 2008.

Research and Instructional Interests: business applications

school staffOperationsDonaly DorsettAdministrative Services Coordinator, ECS 354, Phone: 305-348-2744Email: [email protected] GrahamAssistant Director, Research Programs, ECS 354Phone: 305-348-3946Email: [email protected] LuisDirector, IT and Business Relations, ECS 282Phone: 305-348-6215Email: [email protected] L. MendozaBudget Coordinator, ECS 355Phone: 305-348-1038Email: [email protected]

Office SupportMaureen BrahamOffice Manager, ECS 354Phone: 305-348-6636Email: [email protected] CarbonellGraduate Senior Secretary, ECS 354Phone: 305-348-2744Email: [email protected] RiveraOffice Assistant, ECS 352Phone: 305-348-2744Email: [email protected]

IT SupportJohn FlynnSystems Network Administrator, ECS 258Phone: 305-348-2142Email: [email protected] HernandezBusiness Services Manager, ECS 283Phone: 305-348-2739Email: [email protected] S. JohnsonSystem and Network Manager, ECS 258Phone: 305-348-4021Email: [email protected]

Radu Jianu received a Ph.D in Computer Science from Brown University in 2012. His research interest is using data visualization and visual analytics to solve problems in proteomics, genomics, neurosci-ence and other disciplines. He is

also interested in links between general principles of cognition and visualization

Wei Zeng received her Ph.D from Stony Brook University- SUNY, joint with the Chinese Academy of Sciences, in 2008. She is interested in the ap-plication of modern geometry to tackle fundamental problems in engineering and biomedi-

cine to develop both computational theories and algorithms.

Xin Sun is currently a Ph.D. candidate in the Internet Sys-tems Laboratory in the School of Electrical and Computer Engineering at Purdue Univer-sity. His research interests are in the design and management of emerging networks and

networked systems, and in the migration of such networks and systems to innovative architectures. He is a recipient of the Bilsland Dissertation Fel-lowship from Purdue University Graduate School, and a finalist for the Intel Ph.D. fellowship

Shaolei Ren is a final-year Ph.D. student in Electrical Engineering Department, University of California, Los Angeles (UCLA). His research interests include cloud comput-ing, cyber-physical systems and

network economics. He was selected by IBM T. J. Watson Research as one of the 10 worldwide Emerging Leaders in Multimedia and Signal Processing in 2010 and received the prestigious Dissertation Year Fellowship 2011-2012 from UCLA.

Ning Xie is currently a Ph.D. student in the theory group at the Computer Science and Artificial Intelligence Lab, MIT. His supervisor is Prof. Ronitt Rubinfeld. His main research area is sublinear algorithms. He received an M.S. degree

in computer science from the State University of New York at Buffalo, an M.S. in theoretical phys-ics from Fudan University and a B.E. degree in shipbuilding engineering from Harbin Engineering University.

New Faculty members for 2012-13:


SyLab researchers are developing new systems soft-

ware that address energy, performance and self-man-

agement for storage systems and resource isolation

and performance guarantees within virtualized sys-

tems. Recent work at SyLab include the development

of an extent-based dynamic tiering (EDT) storage

solution which demonstrated that multi-tiered storage

systems built out of SAS or SATA hard disk drives

and solid state drives can be more cost effective than

disk-only or SSD-only systems. EDT’s core strenghths

include the dynamic ability to combine the sequential

I/O performance of disks and random I/O perfor-

mance of SSDs seamlessly, consolidate load within

tiers when feasible, rapidly respond to unexpected

changes in the workload, and carefully control the

overhead due to extent migration. An evaluation with

production workloads show that EDT incurs lower

capital and operating cost, consumes less power, and

delivers similar or better performance relative to SAS-

only storage systems as well

as other simpler approaches

to extent-based tiering such

as static tiering (EST) and

dynamic IOPS-based tiering

(IDT). Figure 1. This work was

conducted in collaboration

with IBM Research – Almaden.

Another recent project ad-

dresses a long-standing bottleneck at the interface

between memory and storage systems. Writing data

within user or operating system memory often en-

counters the classic read-before-write problem where-

by the page written to must first be read from the

backing store, effectively blocking the writing process

before modifications are made. The large gap between

memory and storage access performance adversely

affects workloads that require substantial read-

before-write operations when accessing memory. We

developed techniques to make writes to memory truly

non-blocking. The basic approach involves absorb-

ing writes immediately in temporary buffer pages and

asynchronously merging the updates after reading in

the on-disk version of the page, Figure 2. Doing so im-

proves system performance by first, reducing blocking

of processes and second, improving the parallelism of

data retrieval from the backing store leading to better

throughput

for read-

before-write

operations.

SyLab’s work on energy proportional storage led to the

development of Sample-Replicate-Consolidate Map-

ping (SRCMap), a storage virtualization layer optimiza-

tion that enables energy proportionality for dynamic I/O

workloads by consolidating the cumulative workload

on a subset of physical volumes proportional to the I/O

workload intensity. Unlike previous approaches that

migrate data across physical volumes dynamically or

replicating entire volumes, both of which are prohibi-

tively expensive, SRCMap samples a subset of blocks

from each data volume that constitutes its working set

and replicates these on other physical volumes. Dur-

ing a given consolidation interval, SRCMap activates a

minimal set of physical volumes to serve the workload

and spins down the remaining volumes, redirecting

their workload to replicas on active volumes. SRCMap

is vastly superior in matching power consumption to

offered load relative to alternate approaches for energy

proportionality such as caching and replication. Figure

3. This work

was conducted

in collaboration

with IBM Re-

search, India.

Systems Research Lab -SyLabDr. Raju Rangaswami 8 Funding: NSFsylab.cis.fiu.edu

In depth

area of research: Systems


Selected Research Activities: A Brief IntroductionIn the following sections we present selected research activities of the School of Computing and Information Sciences faculty and their students. We present the research work in two styles: as highlights of specific research agendas and investigations and focus sections that present more details of the research activities. Our research community spans a variety of computer science research topic areas such as storage systems, virtualization, software development, sensor networks, GIS systems, computer security, disaster information management, and affective computing. We invite you to browse the variety of highlights to become more familiar with our faculty and the research they pursue.

Fig. 1

Fig. 2

Fig. 3


Kernel Queue Hooking (KQH) attacks stealthily execute malicious functions by embedding their malicious hooks

in dynamic kernel schedulable queues (K-Queues). Since kernel code and persistent hooks remain intact, KQH

attacks can evade detection of state-of-the-art kernel integrity monitors. These attacks have been used by

advanced malware such as the Rustock spam bot to achieve malicious goals. To defend against KQH at-

tacks, Dr. Wei has proposed a Precise Lookahead Checking of function Pointers (PLCP) approach. The PLCP

approach checks the legitimacy of pending K-Queue callback requests by proactively checking the function

pointers that are invoked by the callback functions. To facilitate the derivation of specifications for any K-Queue,

Dr. Wei’s group has built a unified static analysis framework and a toolset that derives the properties of legitimate

K-Queue requests from kernel source code so they can be used by a runtime checker. A prototype defense

against KQH attacks (Figure 4) has been developed for the Linux kernel’s soft timer queue; more comprehensive

defenses for the Linux kernel and the Windows Research Kernel (WRK) are under active development.

K-Queue static analysis framework

In brief

In brief

Cyber security defenses against kernel queue hooking malwareDr. Jinpeng Wei 8 Collaboration: Georgia Tech; CSTI, Singapore

Virtual machine images must have high integrity since the

initial state of every virtual machine in the cloud is deter-

mined by its image. However, as some of the benefits of

the cloud depend on users employing images built by third

parties, users must also be able to share images safely. To

address the risks faced by administrators and users, Dr.

Wei’s group has proposed the first image management

system (Figure 5) that controls access to images, tracks the

provenance of images, and provides users and administra-

tors with efficient image filters and scanners that detect and

repair security violations. An early implementation of the

system achieves efficiency by exploiting redundancy among

images.

Virtual machine image security in cloud computingDr. Jinpeng Wei

Security features of the Mirage image management system

Fig. 4

Fig. 5

Virtualized Infrastructure Systems and Applications LaboratoryDr. Ming Zhao 8 Funding: NSF, DHSvisa.cis.fiu.edu

In depth

area of research: Systems

Virtualization is an enabling technology for creating

important new system abstractions and addressing

the various challenges faced by today’s computing

systems. The use of virtualization can span across

computing systems of different sizes, from desktops

to supercomputers, and across different layers of the

systems, from virtual machines and virtual storage to

virtual networks. The fundamental goal of Dr. Ming

Zhao and his VISA Research Lab is to explore innova-

tive techniques in virtualization as well as autonomics

in order to effectively utilize the resources in large-

scale, dynamic, and complex computing systems and

to support the high-performance, robust, and secure

computing of challenging applications from different

domains. Currently, his team is focusing on several

projects related to virtualization in distributed and

high-performance computing systems.

System virtualization is a powerful technology that

enables the emerging computing paradigms such as

public and private cloud systems. It allows applica-

tions to be conveniently deployed along with their

required execution environments through virtual ma-

chines (VMs), and supports them to flexibly share the

underlying physical resources with strong isolation.

However, there exists an increasingly urgent need for

virtualized systems to deliver strong Quality of Service

(QoS) guarantees to their hosted applications. Cur-

rently such systems can meet only coarse-grained

and relaxed performance requirements, and their

management considers only limited facets of an ap-

plication’s multi-type resource usage. The continued

existence of the lack of strong QoS guarantees from

virtualized systems presents a critical hurdle to their

further adoption by applications with diverse QoS

requirements and their support of more economical

QoS-based charging models.

The objective of this FIU and DHS sponsored project

is to create a QoS-driven multi-type resource man-

agement system and to support strong QoS guaran-

tees for applications hosted on virtualized computing

systems. Dr. Zhao and his team are creating novel

nonlinear modeling and predictive control based

techniques for accurate and adaptive on-demand

resource allocation as well as new cross-layer opti-

mization techniques for improved application QoS

and resource-use efficiency (Fig. 6). The proposed

research is significant because it will enable virtualized

systems to support strong QoS guarantees and effi-

cient resource allocation for applications with dynamic

and complex multi-type resource usage behaviors.

As a result, this project will allow a broader range of

applications with different levels of QoS requirements

to benefit from the use of virtualized computing. It will

enable virtualized systems such as public clouds to

provide QoS-based contracting models, which will al-

low resource providers to more efficiently allocate their

resources across VMs and allow users to more cost-

effectively purchase resources for their applications.

High-performance computing (HPC) systems are

important platforms for solving challenging problems

in many science and engineering domains. In such

systems, the parallel file system (PFS) is at the core

of the storage infrastructure, which provides ap-


Fig. 6

plications high-throughput data access through the

parallelism of I/Os. However, existing PFS-based

storage systems are unable to recognize the different

application I/O workloads and incapable of satisfy-

ing the applications’ different I/O bandwidth needs.

These limitations prevent applications from efficiently

utilizing the HPC resources while achieving their

desired QoS. This problem is continuing to grow with

the ever-increasing scale of HPC systems and with

the increasing complexity and number of applications

running concurrently on these systems. It presents

a hurdle for the further scale-up of HPC systems to

support many large, data-intensive applications. The

objective of Dr. Zhao’s NSF HECURA-funded project

is to address the research challenges in application of

QoS-driven storage management in HPC systems, in

order to support the allocation of storage resources

on a per-application basis as well as the efficient

execution of applications with I/O demands varying by

several orders of magnitude. Dr. Zhao and his team

are creating new parallel file system virtualization and

autonomic bandwidth allocation techniques to enable

per-application QoS-driven control and optimization

of HPC storage resources. This research has the po-

tential to drastically improve the state of the art in I/O

management in existing HPC systems and generate

an impact on the design of future systems. It will also

allow HPC applications with diverse I/O characteris-

tics and requirements to achieve their desired QoS on

shared HPC resources.

Integrity assurance of cloud computingDr. Jinpeng Wei

One of the most critical security issues surrounding cloud computing is computation integrity. MapReduce, for example,

suffers from integrity assurance vulnerability since it only takes one malicious worker node to render the overall com-

putation result useless. In order to increase assurances of cloud computing integrity, Dr. Wei has proposed a set of

measures that can tolerate malicious partici-

pants in cloud computing environments. These

measures include job replication, verification,

quizzing, and task obfuscation. Dr. Wei’s group

has begun to design and implement these

ideas into the Verification-Based Integrity

Assurance Framework (VIAF), which detects

both collusive and non-collusive mappers in

a MapReduce environment, (Figure 7). The

group’s theoretical analysis and experimental

results demonstrate that VIAF can achieve high

accuracy; its ongoing research plans are to

overlay the VIAF framework on top of existing

cloud infrastructures such as Amazon EC2 and

Microsoft Azure.

Data flow of VIAF

In brief


Fig. 7

In depth

In recent years, we have witnessed a great increase in

the number and variety of multimedia communication

services that have been developed and deployed. Ex-

amples range from IP telephony, instant messaging,

video conferencing, and multimedia collaboration, to

specialized communication applications for telemedi-

cine, disaster management, and scientific collabora-

tion. Given the ease of creation of multimedia data,

the continuous improvements in network capacity

and reliability, and the varying and changing commu-

nication needs of end-users, it is likely that the pace

of innovation in multimedia communication services

will further accelerate.

Although this trend presents a tremendous oppor-

tunity for technological growth and for an improved

end-user experience, current approaches for develop-

ing multimedia communication services are severely

lacking in several respects. Multimedia communica-

tion services today are conceived, designed and

developed following a stovepipe (vertical) approach

that has resulted in a fragmented set of incompatible

tools, technologies, and products. In addition, there is

limited separation between application logic, commu-

nication requirements, underlying platform specifics,

and networking protocols and infrastructure. The

fragmented development approach poses a great

challenge in providing integrated multimedia com-

munication services. Users are forced to hop between

tools to satisfy their communication needs since the

current suite of multimedia communication tools are

technology-centric and largely ignore user-specific

communication needs.

We argue that the root causes holding back rapid

innovation in multimedia communication services are

the lack of user-centric developmental approaches

combined with stovepipe implementations. We are

investigating a Communication Virtual Machine, a new

paradigm for developing and deploying multimedia

communication services through specification and

automatic generation, rather than through traditional

design and development. This paradigm advocates

a model-driven process for conceiving and delivering

multimedia communication that is tailor-made to fit

user or application needs. Both general-purpose and

domain-specific communication needs are specified

in a model, called a communication schema, which is

independent of device types and underlying network

configuration. This model is instantiated, negotiated,

synthesized, and executed via a fully automated

process to satisfy user communication needs (Figure

8). Using this approach, multimedia communication

services can be built within hours or days, rather

than months or years as required by current devel-

opment cycles. We are developing techniques for

the automatic generation of user-centric multimedia

communication services from communication schema

descriptions, which allows changing the communica-

tion schema (or requirements) as required by the user

or application at run-time. We refer to our automatic

service generator as the synthesis engine. In con-

trast to general-purpose, model-driven application

development, we focus on automatic synthesis for

multimedia communication. Our preliminary studies

suggest that automated synthesis is largely feasible

at least for the functional aspects of the communica-

tion such as coordination of communication features,

communication capabilities, and media delivery.

Automatic Generation of User-Centric Multimedia Communications ServicesDr. Peter J. Clarke and Dr. S. Masoud Sadjadi 8 Patented Technology cml.cis.fiu.edu

area of research: Software


Fig. 8

Software Testing Dr. Peter J. Clarke

Model-Driven Software Development Dr. Peter J. Clarke

This research investigates implementation-based testing of object-oriented (OO) software, and testing of

autonomic software systems. The core of the OO testing work is the classification of Java and C++ classes

that supports the unification of testing techniques, testing of abstract

class features, and predicting fault-proneness of classes in OO software.

The classification results in a taxonomy of OO classes based on combi-

nations of characteristics exhibited by the features of the classes. Using

this taxonomy, we have developed an approach to unify implementation-

based testing techniques and to efficiently test the features of abstract

classes. The educational component is focused on introducing software

engineering students to software testing concepts and to the use of test-

ing tools. Dr. Clarke has developed WReSTT (Web-based Repository

of Software Testing Tools), a web portal containing learning materials on

software testing concepts, and interactive tools that facilitate collabora-

tive learning (Figure 9).

This research focuses on domain-specific modeling languages

(DSMLs) and the semantics to support the interpretation of DSML

models without generation of intermediate code. Dr. Clarke’s work

investigates these in the domains of user-driven communication

services and micro-grid energy management systems, the principal

problem being the dynamic definition of DSML semantics based on

runtime changes to user-supplied DSML models. This research builds

upon the communication modeling language (CML) and the communi-

cation virtual machine (CVM) – an interpreter of CML models – cre-

ated by Dr. Clarke’s team (Figure 10). The research group is currently

applying the basic ideas of CML/CVM to the language, MGridML, and

an interpreter, MGridVM, for micro-grid energy management systems.

Dr. Clarke’s recent graduates who have worked on CML/CVM projects

include: Dr. Yingbo Wang (Summer 2009), Dr. Andrew Allen (Spring

2011) and Dr. Yali Wu (Summer 2011 - tenure-track assistant professor).

In brief

In brief


Fig. 9

Fig. 10

In depth

area of research: Sensors and Networks

Geographic location information is critical in wire-less sensor networks. The distributed sensors should organize a coordinate system so that the physical coordinates of any node or any detected object can be determined. Integrating GPS receivers into all the sensors is too expensive for huge-sized networks, so localization using a limited number of GPS resources is very important in many cases. Localization must be accurate and reliable while the cost must be as little as possible. To solve this challenging problem, many algo-rithms, hardware, and applications are being explored. However, several key issues necessary to support ac-curate localization for critical detection in complex and real environments have not been adequately solved.

To compute the localization, i.e. to construct a global coordinate system from metrics measured from dis-tributed sensors, most existing methods build the coordinates on a flattened metric space (e.g., on a 2D Euclidean plane), assuming sensors are distributed on flat land. Such an assumption can often lead to significant distortions in reconnaissance tasks, where sensors are very often spread over curved terrain (2.5D) or underwater (3D, see the figure below, image from UCONN).

It is desirable to have a unified effective geometric-based localization paradigm for both centralized and distributed networks. It should work well for not only 2D sensor networks, but also 2.5D (e.g. terrain scout-ing) and 3D (e.g. underwater reconnaissance and atmospheric monitoring) networks. It should also facili-tate robust localization in noisy and huge-sized military sensor networks, and should benefit many subsequent applications such as reliable routing, hole/boundary detection, and environment mapping and scouting.

OPTIMIZING CENTRALIZED APPROACHES

Sensor’s coordinates are usually represented relatively, as rigid transformations away from beacon-nodes (also called anchor nodes). Beacon nodes (equipped with GPS receivers thus knowing their global coor-dinates) are expensive and ideally should be used as sparsely as possible. In a convex 2D (3D) region with no holes (voids), 3 non-collinear (4 non-coplanar) beacons are required to unambiguously define a global coordinate system; while in more general environments with obstacles, topological holes, etc. (e.g. sensing in urban environments, underwater reconnaissance, and atmospheric monitoring), many more beacon points are necessary to ensure accurate and robust localiza-tion within the sensor network.

Optimal anchor placement can be related to an NP-

hard problem called region guarding. The problem is formulated as: given a 3D region M bounded by a discrete polygonal surface ∂M, where should a set of guarding cameras G = {gi} be placed within M, so that any point in M can be visibly covered by at least one point in G. The optimal guarding, which has been shown to be NP hard, seeks the minimal guarding set G. Here in the sensor localization problem, also due to the obstacles, walls, etc., a sensor within the interested network region may not be detectable from a given an-chor. Therefore, we can consider the following discrete problem: given a set of spatially located sensors, upon which sensors shall we place GPS detectors so that, with the fewest GPS, we can build the global coordi-nate system that localizes all the sensor nodes.

We propose an effective optimization framework using hierarchical integer linear programming to seek for approximate optimal solutions for 3D region guarding. This scheme converts the guarding problem into a set-covering problem then computes its approximate solution. The conversion can be similarly applied here: sensor nodes are natural sampled points in the set and each of them can cover a sub-set of neighbor-ing nodes with relatively high accuracy (such a reliable sub-set can then be associated with this node). The computation of intelligent placement of all the anchor sensors could certainly help the design of the localiza-tion sensor network; its hierarchical structure also sug-gests a way to design centralized multi-tier networks.

Sensor Localization: 3D wireless sensor networks based on geometric computationDr. Ram Iyengar 8 Funding: NSF


Fig. 11


This project develops a suite of bandwidth allocation and packet scheduling techniques as an integrated framework for switch virtualization, to achieve scalable, efficient, and isolated link sharing among virtual networks.

Network virtualization is the creation of multiple coexisting logical networks, each customized to a specific purpose, by reor-ganizing the resources of a common physical infrastructure. It has many important applications in delivering reduced hardware cost, improved resource utilization, simplified maintenance, and incremental service deployment. Implementation of network virtualization relies on creating slices for various resources of the underlying physical infrastructure.

However, there have been no effective solutions to create slices for switches, the important inter-connecting components of any networks. Existing approaches to share switch bandwidth among multiple users have several drawbacks, including impractical bandwidth allocation, weak traffic isolation, poor performance guarantees, and lack of multicast support. In this project, we address the above issues and present the Scalability and Efficiency Aware Link Sharing (SEALS) frame-work for switch virtualization. We mainly consider two types of switch virtualization: intra-switch virtualization (Fig. 12) which creates multiple logical switches within a physical one, and inter-switch virtualization which creates a logical switch by combining multiple heterogeneous physical ones.

The SEALS framework accurately emulates the ideal Generalized Pro-cessor Sharing (GPS) model to realize scalable, efficient, and isolated switch virtualization. The project consists of three correlated research components. First, we design bandwidth allocation schemes for both unicast and multicast traffic, to fairly allocate switch bandwidth among virtual networks based on their requests. Second, we present unicast and multicast packet scheduling schemes for intra-switch virtualization, to assure the allocated bandwidth of each virtual network with strong traffic isolation, tight performance guarantees, and high bandwidth utilization. Third, we propose packet scheduling schemes for inter-switch virtual-ization, to enable a virtual switch with aggregated capacity, fault tolerance, and simplified control by combining multiple physical switches. We use a combination of theoretical analysis, simulations, and experiments to evaluate the proposed design. In particu-

lar, we will implement the SEALS framework in OpenFlow switches to obtain experimental data from a realistic environment.

A Scalable and Eff icient Framework for Switch Virtualization Dr. Deng Pan 8 Funding: NSF

In brief

In brief Scalable and Energy-Eff icient Data Center Networking by Traff ic Engineering Dr. Deng Pan

Modern data centers contain hundreds of thousands of servers to achieve econo-mies of scale. Such a huge number of servers have created a challenge for the data center network (DCN) to provide proportionally large bandwidth to interconnect the servers. Existing designs to this challenge intend to provide full bisection bandwidth and support worst-case all-to-all communication. However, fully provisioned bisec-tion bandwidth requires significant hardware and operating costs, and cannot be utilized most of the time due to fluctuating traffic patterns in DCNs.

In this project, we apply a traffic engineering approach to the DCN design and operation, so as to improve bandwidth utilization and energy conservation. First, we design a DCN architecture that enables differentiation of delay-sensitive and elastic traffic and fine-grained bandwidth provisioning for the former. Next, we present a fast topology oriented multipath routing al-gorithm to fully explore available bandwidth. Finally, we propose a novel joint host-network optimization scheme to maximize energy conservation at off-peak traffic time. We have conducted theoretical analysis and built an OpenFlow based bandwidth

provisioning prototype, and the preliminary results fully demonstrate the effectiveness of our designs (Fig. 13)

Fig. 12

Fig. 13

area of research: Cyberinfrastructure

Leveraging an innovative and successful international industry and university partnership called Latin American Grid (LA Grid) with

funding from the US National Science Foundation’s Partnerships for International Research and Education (NSF PIRE) program,

Florida International University’s (FIU) School of Computing and Information Sciences has been providing students with opportuni-

ties to receive multiple perspectives in three different aspects of research collaboration as they work with local and international

researchers, in academic and industrial research labs, on basic and applied research projects. Consequently, PIRE students are

able to participate in the full research pipeline from inception of ideas, through basic research, to practical applications with a wide

choice of collaborators and international experiences. The research is focused on enabling cyberinfrastructure (CI) applications

to allow domain experts to effectively express the logic and software artifacts of domain applications while hiding the details of

the cyberinfrastructure architecture, software, and hardware. Our development paradigm, called Transparent Cyberinfrastructure

Enablement (TCE), serves as the foundation for the study of application development methodologies, platforms, and tools that sig-

nificantly ease CI-enabled application development and make applications more portable and adaptable to future changes of CI.

The faculty members at US institutions and their national and international collaborators lead PIRE research collaborations. All

the local and remote advisors are expected to closely supervise the students’ progress in their research. During the recruitment

process, a one-page research proposal is developed by each student and their local and remote advisors. After the review and

approval of the proposals by the PIRE Program Committee local and remote advisors reaffirm their role as PIRE faculty advisors for

the whole duration of their students’ participation in the program. Students who are selected participate in an orientation program

conducted by FIU’s Office of Study abroad that prepares the students for their overseas travel to their research site. Students are

provided with room and board, and office space in the remote site and work under the direction of their remote and local advi-

sors. Each student is expected to send a formal weekly report to their advisors. The reports have to comply with a template that

includes the following sections: activities, accomplishments, issues, plan for next week, and review of papers from the literature.

In the past four years of this project, 109 trips have been

completed by seventy-seven individuals from four US institu-

tions including FIU, FAU, UNCC, and UPRM. Students have

visited eleven countries across four continents: North America,

South America, Europe, and Asia. Twenty-four trips were taken

by twelve PIRE PIs, Co-PIs, Sr. Investigators, and mentors.

There have been two trips by one postdoc; sixty-four trips by

forty-six graduate students; and nineteen trips by eighteen

undergraduate students. Each travel event lasts an average of

fifty-three days. As for diversity, a large percentage of our PIRE

student participants at both graduate and undergraduate lev-

els were Hispanics (22% of graduate student participants and

47% of undergraduate participants), Black (2% of graduates

and 5% of undergraduates), and Female (30% of graduates

and 16% of undergraduates). PIRE participants and collabo-

rators have published thirteen journal articles, seven book

chapters, forty-three conference and workshop papers, and

sixty-six posters; these papers are co-authored by our PIRE

students and their local and international faculty participants. The result from a self-assessment survey has indicated that all PIRE

participants have recommended this program to others.

Cyberinfrastructure Enablement and PIRE Dr. S. Masoud Sadjadi 8 Funding: NSF

pire.fiu.edu

In brief


PIRE student Xabriel J. Collazo-Mujica, (far left), with external advisor Dr. Rosa Badia and

Team at Barcelona Supercomputer Center. Summer 2011


In depth

TerraFly is a technology and tools for visualization and

querying of geospatial data. The visualization compo-

nent of the system provides users with the experience

of virtual “flight” over maps comprised of aerial and

satellite imagery overlaid with geo-referenced data.

The data drilling and querying component of the sys-

tem allows the users to easily explore geospatial data,

to create geospatial queries, and get instant answers

supported by high-performance multidimensional

search mechanisms.

TerraFly’s server farm ingests, geo-locates, cleanses,

mosaics, and cross-references 40TB of basemap

data and user-specific data streams. TerraFly’s Ap-

plication Programming Interface allows rapid deploy-

ment of interactive Web applications and has been

used to produce systems for disaster mitigation,

ecology, real estate, tourism, and municipalities. Ter-

raFly’s Web-based client interface is accessible from

anywhere via any standard Web browser, with no

client software to install. (Figure 14)

TerraFly tools include user-friendly

geospatial querying, data drill-down,

interfaces with real-time data suppliers,

demographic analysis, annotation, route

dissemination via autopilots, customiz-

able applications, production of aerial

atlases, and an application program-

ming interface (API) for production of

Web-based map applications.

The TerraFly project has been featured

on TV news programs (including FOX

TV News), worldwide press, covered

by the New York Times, USA Today,

NPR, and Science and Nature journals.

The project’s primary sponsor is the National Sci-

ence Foundation (NSF). Of the 53,000 NSF-funded

projects in 2009, it chose 120, including TerraFly, for

the NSF annual report to Congress.

The 40TB TerraFly data collection includes, among

others, 1-meter aerial photography of almost the

entire United States and 3-inch to 1-foot full-color

recent imagery of major urban areas. TerraFly vector

collection includes 3 billion geolocated objects, 50 bil-

lion data fields, 1B polylines, 120M polygons, includ-

ing: all World roads (90M roads, 130M intersections,

1B segments), the U.S. Census demographic and

socioeconomic datasets, 110 million U.S. parcels with

property lines and ownership data, 15 million records

of businesses with company stats and management

roles and contacts, 2 million physicians with expertise

detail, various public place databases(including the

USGS GNIS and NGA GNS), Wikipedia, extensive

global environmental data (including daily feeds from

NASA and NOAA satellites and the USGS water

gauges), and hundreds of other datasets.

TerraFly Geospatial Data Management and Analytics Dr. Naphtali Rishe 8 Funding: NSF, NASA, USGS, IBM

TerraFly.com

area of research: Data

Fig. 14

An index structure is the backbone and the first step towards the satisfac-

tory development of any database management system. However, tradi-

tional database management systems cannot accommodate multimedia

indexing since multimedia data carry additional semantic information, which

is not the case with traditional alphanumeric data. To solve this problem,

several multidimensional index structures, such as the Affinity Hybrid Tree

(AH-Tree), the AH+-tree, and the Generalized Multimedia Tree (GeM-Tree),

have been developed by the DMIS Lab to support the retrieval of all types

of multimedia data.

The AH-Tree is an efficient access and indexing framework that combines

feature and metric spaces in a novel way and aims at incorporating high-

level semantic information to generate results that overcome the well-known

problems of semantic gap and user subjectivity. The AH-Tree is able to

organize large image databases and supports popular multimedia retrieval

mechanisms such as Content-Based Image Retrieval (CBIR) shown on

figure 15. The high-level semantic information can be obtained from several

sources, such as high-level affinity relationships between image data. The

concept of affinity relationship stems from the idea that the more two imag-

es are accessed together the more related they are. The AH+-tree provides

the same functionality as the AH-Tree but utilizes the high-level semantics

in a novel way to eliminate I/O overhead incurred by the AH-Tree and thus

provides the same functionality at lower I/O cost.

Multimedia IndexingDr. Shu-Ching Chen 8 Funding: NSF

In brief

area of research: Data

With the rapid development of the Internet and storage systems, enormous amounts of multimedia data

such as images and videos have been generated. There is an increasing need of advanced technologies

to effectively and efficiently process and manage such large-scale multimedia for various applications, and

associated with this need is the emerging demand of multimedia systems that support semantic analysis. To

address this research problem, the DMIS Lab actively conducts research in the areas of event detection and

concept extraction.

Under the aforementioned research areas, the DMIS Lab has developed a novel multimodal semantic

concept/event detection framework that can be utilized in high-performance computing facilities with large

storage resources. The framework follows a layered architecture that consists of: (a) feature extraction, (b)

filtering, (c) model training, and (d) testing. In order to effectively characterize the images and/or videos, low-

level, mid-level, and object-level features are extracted. Since concepts/events of interest are often highly

infrequent, filtering techniques are applied to address the class-imbalance problem. As for model training, the

multiple correspondence analyses (MCA) technique, originated from statistics, is utilized to capture the com-

plex interrelationship between features and concepts/events, which are modeled based on the training data.

Finally, the generated MCA-based models are used for detecting concepts/events from images and videos.

Large-Scale Semantic Concept/Event DetectionDr. Shu-Ching Chen 8 Funding: NSF

In brief


Fig. 15

Dr. Carbunar has contributed to the field of electronic payments with the concept of conditional e-cash and its use in various

network and cloud services He introduced the notion of electronic payments whose correctness can be verified in zero-knowl-

edge when they are received, but become valid only if the outcome of a future, pre-agreed upon event is favorable. He used this

concept to provide secure incentives for cloud and volunteer computing efforts and designed the first anonymous micropayment

system where double spending is prevented probabilistically.

Secure Payments

Dr. Bogdan CarbunarIn brief

One of today’s ubiquitous trends is the online hosting of data and services. Users can access a wide range of content from

Video on Demand services and sites such as Netflix or Hulu on their personal devices. Users can also store personal content

on sites offering specialized services such as Yahoo Mail, Google Docs or YouTube and outsource complex computations

to “cloud” providers such as Amazon, Google and Microsoft. The work of Dr. Carbunar focused on Video on Demand (VoD)

services where he addressed scalability issues of Content Distribution Networks (CDN) used by Comcast, Charter and Time

Warner. Based on request logs from such providers, Dr. Carbunar has proposed predictive caching algorithms that enable

CDN servers to store only items that are predicted to be locally popular while simultaneously minimizing and balancing the

network load and extending the lifetime of the cache storage technology. Furthermore, when transferred content is stored in

client devices, Dr. Carbunar has proposed novel content sharing applications as well as efficient and secure synchronization

protocols for Wi-Fi enabled mobile devices.

Secure Content Distribution

Dr. Bogdan CarbunarIn brief


When accessing data stored on remote servers, users unwittingly reveal personal information which can lead to

unwanted side-effects such as leaking personal information which can result in behavioral profiling, spam and

targeted ad placement. Users have no control over who can access this information and the type of processing

that can be performed on this sensitive data, which on multiple occasions has been sold or even made public

(e.g., Netflix, AOL). Computational private information retrieval (cPIR) techniques allow users to access remote data

without leaking their interests or their access patterns to the server storing the data. While in principle cPIR can

be used to solve the problem previously mentioned, Dr. Carbunar showed that the deployment of non-trivial single

server cPIR protocols on real hardware of the recent past would have been orders of magnitude less time-efficient

than trivially transferring the entire database. To address this challenge, Dr. Carbunar designed a Bloom filter based

construction that significantly reduces the amortized complexity of a cPIR protocol.

Private Remote Data Access Dr. Bogdan Carbunar

In brief

In depth

area of research: Theory

Protecting confidential information from improper

disclosure has emerged as a fundamental issue for

trustworthy computing. While it is sometimes possible

to stop undesirable information flows completely, it

is perhaps more typical that some undesirable flows

are unavoidable. For instance an ATM machine that

rejects an incorrect PIN thereby reveals that the

secret PIN is not the one that was entered. Similarly,

revealing the tally of votes in an election reveals some

information about the secret ballots that were cast.

More subtly, the amount of time taken by a crypto-

graphic operation may be observable by an adver-

sary, and may inadvertently reveal information about

the secret key. As a result, there is growing interest in

quantitative theories of information flow, which allow

us to talk about “how much” information is leaked

and (perhaps) allow us to tolerate “small” leaks. But

while it is tempting to base such theories on classic

information-theoretic concepts like Shannon entropy

and mutual information, these turn out not to pro-

vide very satisfactory confidentiality guarantees. As

a result, Geoffrey Smith and other researchers have

developed an alternative theory, based instead on

Renyi’s min-entropy, which gives strong, direct opera-

tional security guarantees.

His current research aims to deepen our understand-

ing of the theory and applications of min-entropy

leakage, pursuing several themes concurrently. In the

theory of min-entropy leakage, uncertainty is mea-

sured in terms of a random variable’s Bayes vulner-

ability to being guessed in one try by an adversary;

note that this is the complement of the Bayes Risk.

Dr. Smith and his collaborators are exploring the

mathematical properties of this theory, for both

deterministic and probabilistic systems, with the

goal of better understanding the relationship to other

theories, such as mutual information leakage and dif-

ferential privacy. To support the compositional analysis

of complex systems, they are establishing leakage

bounds for channels in cascade, where the output of

one channel becomes the input to another. Also, they

are developing techniques for computing the min-

entropy leakage of a given system, giving a way to

verify whether it conforms to a given quantitative flow

policy; both model-checking and statistical-sampling

based techniques are being considered. Finally, appli-

cations of min-entropy leakage are being explored, for

example to timing attacks against public-key cryp-

tosystems, and to accountability systems that use

logging and auditing to identify misbehaving entities.

These efforts aim to develop new theory, enforcement

techniques, and applications of min-entropy leakage,

contributing broadly to a rigorous science of quantita-

tive information flow.

Quantifying Information Leakage using Min-Entropy Dr. Geoffrey Smith 8 Funding: NSF

With expertise in graph and geometric algorithms, Prof. Narasimhan

studies theoretical questions related to the design and analysis of

optimal geometric networks. His work has applications in designing

good spanner networks, which allow for communication, transpor-

tation, or sensor networks. It is well known that sparse networks are

desirable since they are inexpensive to build, but suffer from many

disadvantages including unacceptable increase in distance between

the nodes, unbounded number of hops, low fault tolerance, high

energy utilization, and much more. Prof. Narasimhan’s work shows

how to overcome these shortcomings and design efficient net-

works. The figure 16 shows a series of road networks with decreas-

ing sparsity and improved guarantees on the ratio of the distances

in the network to the direct “as-the-crow-flies” distance.

Network Design Dr. Giri Narasimhan

In brief


Fig. 16

In depth

3D Hurricane Storm Surge Animation and

Visualization

Hurricanes are one of nature’s most powerful forces

with the proven ability to take lives, destroy cities, and

cause billions of dollars in damages. Therefore, it is

crucial to determine the potential storm surge effects

of an approaching hurricane, plan evacuation routes,

and effectively communicate this information to warn

citizens who may be in severe danger and to avoid

over-evacuation of those who are not. It is well ac-

cepted that 3-D visualizations have a greater impact

on people’s perception of a situation than textual

descriptions and static graphics.

The DMIS Lab has developed a simulated 3-D hur-

ricane environment complete with storm surge effects

for hurricane prone regions in Florida, namely, Key

West, Miami, etc. It utilizes LIDAR data to build city

models and simulates the effects that a hurricane has

on objects (such as cars, buildings, and sea-shores).

This system can be linked to a streaming source of

dynamic hurricane-related data that includes antici-

pated wind speeds and storm surge levels to emulate

real-life scenarios (Figure 17. This visualization envi-

ronment can also be utilized as a training medium to

educate the public about the severity of hurricanes

and their deadly effects, thus enabling them to prac-

tice appropriate safety measures when the situation

arrives. Furthermore, to allow the general public get

a detailed idea of hurricane conditions in locations of

their choice, the environment integrates the simulated

3-D animations with 2-D interactive maps.

Florida Public Hurricane Loss Model

Homeowner insurance rate making is an important

public policy issue in the State of Florida. The State of

Florida has over 2 trillion dollars of residential proper-

ties exposed to hurricane risk. To assure that con-

sumers are charged within lawful insurance ranges,

the Florida Office of Insurance Regulation sponsored

the development of a Florida Public Hurricane Loss

Model (FPHLM) to assess hurricane risk and proj-

ect insured residential losses. The FPHLM is a very

complex set of computer programs that simulate and

predict how, where, and when hurricanes form, their

wind speeds, intensities and sizes, their tracks, how

they decay and how they are affected by the terrain

along their tracks after landfall, how the winds interact

with different types of residential structures, how

much they can damage house roofs, windows, doors,

interior, and contents, how much it will cost to rebuild

the damaged parts, and how much of the loss will be

paid by insurers. The FPHLM consists of three major

components: wind hazard (meteorology), vulnerability

(engineering), and insured loss cost (actuarial). Its

computer platform is a web-based distributed system

that integrates all the functionalities of the model and

is designed to accommodate future integration of ad-

ditional sub-components or enhancements.

Disaster Information Management

Dr. Shu-Ching Chen 8 Funding: NSF

Ft Lauderdale, Fl. Waves crashing on shore

area of research: Community


Fig. 17

The Business Continuity Information Network (BCIN) Project is an initiative that engages university, local, re-

gional, and global communities to work together as partners to benefit society. Its broader impact is provided

by its web-based service (www.bizrecovery.org) where local businesses, emergency management offices,

and organizations that assist businesses can gather to share critical information and support continuity efforts

before, during, and after a disaster. BCIN is capable of capturing disaster preparation, response, and recovery

data between communities to achieve a speedy recovery of locally impacted economies. In order to do this, this

business-to-business community network currently maps and shares critical information about infrastructure

conditions and recovery efforts in collaboration with County Emergency Management Offices (Miami-Dade, Bro-

ward, Palm Beach, and Monroe) and major private infrastructure providers. BCIN localizes and tailors relevant

information to business managers who use this information to better assess an event’s impact to their facilities,

employees, suppliers and customers.

Currently deployed in South Florida, BCIN has been well received by the disaster management community in

Florida and may be deployed throughout the state and beyond. Companies use its information to better under-

stand the current situation caused by the hazard, identify resources they need for recovery, maintain contact with

their supply chain and key customers, and acquire the resources they need to resume operations faster.

area of research: Community

In brief

In brief

Visual Analytics for Command, Control, and Interoperability Environments Dr. Shu-Ching Chen, Dr. Tao Li, Mr. Steven Luis 8 Collaboration: Miami-Dade Emergency Management

Business Continuity Information Network (BCIN) Dr. Shu-Ching Chen, Dr. Tao Li, Dr. Jainendra Navlakha, Mr. Steven Luis www.bizrecovery.org 8 Funding: NSF, DHS, IBM

Responders in the field (both public and private participants) are capturing footage (pictures and

video) of a disaster area with mobile phones. These data are being collected, but are not inte-

grated, in the incident command systems where situation reports and incidence action plans are

being held. Moreover, such data are entered into incident command systems manually, which is

time consuming and requires careful human review and management. To address this problem,

the DMIS Lab has developed a framework that uses advanced data integration and visual analyt-

ics techniques to analyze situation reports and pictures, as well as text captured in the field, and

automatically link reports directly to relevant multimedia content collected in the field.

The server layer of the framework implements an offline Multimedia Analysis Framework (MAF) to

associate situation reports with relevant multimedia content. The MAF framework includes a hier-

archical image classification component developed based on multi-source data fusion and some

data mining techniques, such as multiple correspondence analyses (MCA). The situation reports

are pre-processed using the GATE system and WordNet to associate location-subject pairs. In

addition, the framework provides a prototype iPad application that allows emergency personnel

to easily interact with situation reports and associated multimedia data (Figure 18). The framework

also incorporates a mechanism that allows users to provide feedback information that is used to

refine the association between situation reports and multimedia data. The system’s functionality

was developed in collaboration with Miami-Dade’s EOC department, which has expressed interest

in the application and encouraged us to develop the system into an operational pilot.


Fig. 18

The work required to build BCIN has been a collaboration with many government and industry partners including the

Miami-Dade, Broward, Palm Beach, and Monroe Offices of Emergency Management (EOC), IBM, Office Depot, Wal-

Mart, Greater Miami Chamber of Commerce, and over 100 companies (both nationally or regionally known). BCIN links

participating companies into a community network that is guaranteed to be available after a disaster such as a hurri-

cane. This network supplies tools for company staff to gather and enter situation-awareness data in real-time, provides

an automated means to integrate, analyze and present the data, offers information fusion techniques to channel the

right information to the right people, and enables communication among company staff and between customers and

vendors. In short, the networked information tools, the business community connected by the network, and the busi-

ness intelligence data gathered in the network help to revive the business ecosystem interrupted by the disaster, thus

achieving a speedy recovery. The BCIN system platform provides mechanisms for data integration, data mining, and

visualization utilizing off-the-shelf Web-based technologies. Figure 19 shows a snapshot of the current BCIN proto-

type that displays the information collected from various sources in an intuitive and user-friendly manner. Many BCIN-

enabled community activities have demonstrated the impacts this project has on the community. Miami-Dade and

Palm Beach County Emergency Management offices have both developed procedures for using BCIN as an ongoing

mechanism to reach out to the local business communities as part of their Emergency Support Function. As a result of

the partnership with local emergency management offices, two live joint-county exercises have been conducted where

companies run the system through a hurricane scenario to facilitate information sharing experiences and incorporate

user feedback. Many other exercises enabled by BCIN include: Miami-Dade EM Business Recovery Desk, Florida

Statewide Hurricane Suitor Training Exercise, UASI Operation Cassandra, and Miami-Dade EM Business Recovery

Program Training. In addition, three internal activations with Miami-Dade EOC were executed where live situational data

were injected from EOC sources into the system for 2008 hurricane threats Fay, Gustav, and Ike.

BCIN participates in a broader community of public and private programs working towards community resilience. Pri-

vate initiatives include infrastructure hardening, like improving power and telecommunications availability after a storm.

For example, Office Depot has built an infrastructure to allow business members to charge their phones and laptops

and access the Internet when power outages occur after a hurricane. In another example, The Institute of Business and

Home Safety, an insurance industry group, has developed a business continuity program that helps small businesses

conduct an assessment of their operations. BCIN will provide a situational information platform to these small busi-

nesses to help them understand the risks presently affecting their employees, supply chain, assets, and other factors

addressed in the continuity assessment. BCIN distinguishes itself from the vast array of independent tools such as

instant messaging and resource databases by providing a platform that integrates such user scenario requirements

without requiring participants to abandon their current business continuity systems or reveal private company data.

Fig. 19 BCIN System Screen Shot Depicting Company Situation


In depth

area of research: COMMUNITY

The Affective Social Computing Laboratory (ASCL)

conducts research in affective computing, a new and

growing field in computer science. Affective comput-

ing is an interdisciplinary field involving tasks that re-

late to emotion. It can be seen as the logical continu-

ation within engineering of the ”Emotion Renaissance”

within psychology and neuroscience of the 60s and

70s. It explores the computational nature of affective

phenomena, such as emotions, moods, personality,

and attitudes, and their role in human intelligence,

communication and decision-making. Such insights

can then be applied to allow computers to account

for and adapt to human affect. This research is highly

interdisciplinary in nature; it lies at the intersection

of Artificial Intelligence (AI) and Human-Computer

Interaction (HCI) from computer science, emotion

theories from psychology, social interaction theory

from communication, and other domain knowledge

when used to build systems within a domain (e.g.,

health informatics).

The research goal of ASCL is to create engaging,

embodied socially intelligent agents that can interact

with humans in innovative ways through expres-

sive, multi-modal interaction. Such systems have

applications in a wide variety of contexts involving

socio-emotional content, such as car safety, social

robotics, health care, social orthotic help companions,

cyber-therapy, intelligent training systems, and other

e-learning systems.

To carry out our research, we envision and create fun-

damental theories by finding and synthesizing relevant

interdisciplinary findings into a computational form

useful for artificial intelligent agents. Our research also

seeks to discover innovative AI techniques that are

best suited to become components of an intelligent

agent (from sensing, to decision-making, to actuat-

ing), and to apply HCI principles toward the design of

engaging interactive media for a specific domain (e.g.

health promotion assistants). In each specific context,

these intelligent agents must:

• Sense the affect, preferences, and personality of

their interlocutor (bio-sensing, pattern matching,

knowledge elicitation and/or representation of af-

fective phenomena)

• Make decisions (logic-based and probabilistic rea-

soning) that are socially acceptable based on their

dynamic user-model (knowledge representation)

• Carry out their interactions (HCI design principles)

within the domain-knowledge (e.g. health commu-

nication, computer-based training, driver safety)

• While displaying social competence (social commu-

nication theory)

• Tailor and adapt (machine learning) their interactive

styles to the specific socio-emotional profile (user-

modeling) of their human counterpart

Applications and current emphasis on e-health

There are many potential application domains for our

innovative affective computing technology. At ASCL

we are particularly interested in conceiving affective

computing systems in the domain of smart health and

well-being.

Western healthcare interest has recently started to

move toward finding ways to preventively promote

wellness, rather than to solely treat already estab-

lished illness. This new direction in healthcare has

given rise to a variety of health promotion interven-

tions aimed at helping people to improve their health

by changing their lifestyle and behavior. US statistics

are gloomy: for obesity alone, 33.8% of adults and

17% (or 12.5 million) of children are obese; similar

numbers can be found for alcoholism and other forms

of substance abuse.

It seems impossible to provide health counseling for

13 million obese children, much less preventative care

for the children who are at risk and the rest of the

population. At ASCL, we are studying how socially

engaging virtual characters can provide some of the

complementary personal health informatics automa-

tion that is needed to address this gap.

Framework for Affective Computing

Dr. Christine Lisetti 8 Funding: ONR, NASA, NSF


We build personal health informatics help agents that

users can access anytime, that users can actually use

(and do not require technical sophistication), that users

will actually use (non-threatening and supportive), and

who are emotionally competent since these lifestyle

issues are intensely emotional for the users (Figure 20).

We aim to increase access to e-health by develop-

ing our help agents on different platforms: PC-based,

internet-based, and mobile devices.

Publication venues and events

Affective Computing is an exciting new field of re-

search which is now fully established as a sub-field of

Computer Science. It has recently

launched two journals specialized on

the topic, namely the IEEE Transac-

tions in Affective Computing and the

International Journal of Synthetic

Emotions. Many top rated journals

also publish Special Issues on the

topic.

Researchers from industry and

academia gather at its dedicated

International Conference on Affective

Computing and Intelligent Interac-

tion, and many prestigious interna-

tional conferences feature Special

Tracks on Affective Computing.

The CAKE Center was established by NSF to develop long-term partnerships among industry, academe and government. The

Center is supported primarily by industry center members, with NSF taking a supporting role in its development, evolution, and

core funding.

The FIU High Performance Database Research Center, the FIU TerraFly Geospatial Data Services and the FIU Healthcare Infor-

mation Technology Initiative operate under the CAKE Center’s organizational structure. The Center’s Director, Naphtali Rishe,

is the inaugural Outstanding University Professor of FIU and the principal investigator of $45M in grants. The FAU Site Director,

Borko Furht, is the Chairperson of the FAU Department of Computer & Electrical Engineering and Computer Science. Dubna

International University, Russia, joined the Center in August 2010 under the Site Directorship of Academician Eugenia Cheremi-

sina. The Chair of the CAKE Center’s Industrial Advisory Board is Oded Cohn, Director of IBM’s Haifa Research Center.

The CAKE Center conducts industry-relevant studies in the representation, management, storage, analysis, search and social

aspects of large and complex data sets, with particular applications in geospatial location-based data and healthcare. New

funding in 2010-2011 included $2M from NSF related to geospatial data management and $3M for neuroscience computing.

Industry/University Cooperative Research Center for Advanced Knowledge Enablement (I/UCRC-CAKE) Dr. Naphtali Rishe

cake.fiu.edu

In brief


Fig. 20

area of research: COMPUTATIONAL

The analysis of elliposmetric spectra consists of data acquisition, processing, and interpretation. There are vari-

ous data acquisition technologies but at a minimum each single measurement provides two real numbers relating

the p and s waves, the relative amplitude angle, Ψ, and the phase shift difference, ∆. Data processing (solving)

is almost always required because the desired reflecting surface parameters, such as film thickness, are related

to the measured data through a system of equations which are typically non-invertible and non-linear. We have

restricted the current investigation to measurement of Ψ and ∆. The underlying treatment of the multivalued func-

tions in present least-squares solving methods results in an inherent problem with multiple solutions which the

present work eliminates.

Data acquisition is very similar regardless of the configuration of the films and substrate under investigation.

On the other hand, data analysis may differ markedly depending upon the thickness, optical properties, and

morphology of the reflecting surface. One reason for this is that the physical properties of particular film substrate

combinations may result in parameter correlation in the mathematical models. Another reason is that particu-

lar material combinations may introduce numerical problems into the solution processes. A particular case in

point of problematic analysis is the simultaneous measurement of the thickness and optical properties of thin

absorbing layers such as metals. In an earlier work, one of the authors (Tiwald et al.), investigated prior known

methods for analyzing the data from examples of absorbing films. All of those methods were based on numerical

least-squares analysis. We have analyzed the same films and the measured data using the new mathematical

and n–k plane numerical methodologies of Urban and Barton and have described the ways in which these new

methodologies work better than previous analysis methods. There is reason to believe that other methods may

be developed and used for obtaining these solutions. We are studying the numerical process to obtain solutions,

not the physical model which, of course, is independent of solution method.

Numerical Ellipsometry: Analysis of Thin Metal Layers Using N-K Plane Methods with Multiple Incidence Angles

Dr. David Barton

In brief

Working with collaborators from FIU’s College of

Medicine, Prof. Narasimhan is building analyti-

cal protocols and tools for inferring the microbial

community profile, whether it is in the soil, in other

environmental niches, or in host environments

such as the lungs of Cystic Fibrosis and COPD

patients. Such studies will lead to improved treat-

ments of infections and better long-term prog-

nosis. Students M. Jaric and G. Gonzalez have

contributed to this effort.

Metagenomics

Dr. Giri Narasimhan

In brief

Phylogenetic tools are computational tools to study

evolution of organisms. However, when studying the

evolution of HIV within a single patient over a de-

cade, existing tools fail to tease out the relationships.

Prof. Narasimhan and graduate student P. Buendia

developed MinPD to elicit the evolutionary relation-

ships and to highlight critical stages in the develop-

ment of the viral population and its virulent mutants

within the population.

Phylogenetic Tools for With-in-Host Evolution of HIV

Dr. Giri Narasimhan

In brief


The Bioinformatics Research Group (BioRG) works on build-

ing tools for solving a variety of Bioinformatics problems.

When existing tools failed to design primers for finding resis-

tance genes in the plant T. cacao, the tool DePiCt developed

by Prof. Narasimhan and his team. Wei used clustering

techniques to help USDA scientists to discover many new re-

sistance genes. When two new bacterial genome sequences

were available from the Broad Institute and it was necessary

to compare the sequences, Prof. Narasimhan and his group

developed a suite of tools to help collaborators from Harvard

University and FIU to perform a comprehensive analysis of

the two new genome sequences along with five other existing

ones. See figure 21 for a visual comparison for six genome

sequences of bacterial strains.

Comparative Genomics

Dr. Giri NarasimhanIn brief

Prof. Narasimhan and graduate student, N. Andres Parra, developed PoIRe, a point-based image

registration tool for registering medical images. The applications include registering images taken be-

fore, during and after radiotherapy treatments, and in facilitating accurate delivery of radiotherapy. The

laboratory has also developed registration techniques when images undergo non-rigid transformations,

such as those that take place when a tumor changes in size and shape. The figure 22 shows images

before and after registration.

Image Registration Dr. Giri Narasimhan

In brief


Fig. 21

Fig. 22

area of research: COMPUTATIONAL

High-throughput sequencing technology is now the standard tool for sequencing small and large genomes and laying the

foundation for a systems biology approach to understanding the organisms. However, these techniques invariably result

in a large number of gaps in the sequence. Prof. Narasimhan and graduate student X. Yang developed a tool called CloG

that deftly exploits information from fresh sequencing data and the genomic sequences of closely related species and

stitches fragments together to close the gaps. CloG helped close 75% of the gaps in the draft assembly of the bacterium

Burkholderia dolosa.

Tools for Next Generation Sequencing Assembly

Dr. Giri NarasimhanIn brief

More than half of all solid tumors receive external beam ionizing radiation as part of multimodality treatment (e.g, radio-

therapy + chemotherapy or radiotherapy + surgery + chemotherapy). The goal of radiation treatment is to treat disease

while avoiding damage to normal tissue and critical organs that surround the tumor. Conventional radiotherapy involves

administering a prescribed tumor-killing dose (typically around 50 – 70 Gray) over several sessions (~25 to 35) known as

“treatment fractions”. In recent years, with technological advances as well as improved understanding of radiobiology,

there have been two trends – either to deliver the same total dose in significantly fewer fractions (1 to 5) when accompa-

nied by improved image-guidance using offline and online projection x-ray imaging and computed tomography (CT), or

to increase the total radiation dose using the historical dose per fraction (2 Gray) with the same image guidance. In many

anatomical sites, such “dose escalation” (per fraction) has been shown to offer local tumor control benefits. This has

often been reported in the literature addressing irradiation of lung tumors.

Lung cancer is the most common cause of cancer related death in the United States. Overall, only 10-15% of lung can-

cer patients will be living five years after diagnosis. Its radiation treatment therefore attracts great attention and is in need

of significant improvement. Due to the spatial relationship of lung tumors with important normal tissue structures – spinal

cord, esophagus, heart, brachial plexus, normal lung tissue, bronchial tree, and trachea among others – total dose esca-

lation is often not feasible to a great extent. Furthermore, radiation treatment planning for lung cancers is often complicat-

ed by complex motion of tumors during all phases of the respiratory cycle. This tumor motion and object deformation is

also heavily influenced by the motion of intrathoracic normal tissue structures. Hence, for a number of reasons, treatment

planning for intrathoracic radiation requires better tools to optimize precision and accuracy of delivery. We are developing

a lung tumor modeling and computational infrastructure to facilitate the tracking and the prediction of respiratory move-

ment and deformation of organs surrounding the tumor. These new results will help medical practitioners to accurately

plan and deliver radiotherapy.

MRI-based 4D Computational Modeling of Respiratory Motion for Lung Tumor Radiotherapy

Dr. Ram Iyengar

In brief



Discovery Lab discoverylab.cis.fiu.edu

The Discovery Lab created in Spring 2012 is aimed at developing products for the marketplace. At the same time, the

laboratory provides students with the hands-on experiences they need to solve real-world challenges, develops student-led

research opportunities, fosters students’ entrepreneurial skills, and trains a new generation of IT professionals who reflect the

diversity of South Florida.

The Discovery Lab mission is:

• Engage undergraduate students in hands-on learning

experiences that solve real-world challenges, thereby

strengthening FIU’s positioning as a solutions center.

• Develop student-led research opportunities guided by

faculty with experience in systems development.

• Foster entrepreneurial skills among students.

• Train the next generation of IT professionals who reflect

the diversity of South Florida, strengthening the School’s

dedication to facilitate access to its programs among

historically underrepresented minorities.

The Discovery Lab provides an infrastructure to promote

collaborative research among universities and research

organizations across the nation. In addition to addressing

a comprehensive set of fundamental research topics, the Lab is pursuing commercialization, distinguishing itself from

traditional research labs through its focus on translating research discoveries into technology transfer outcomes.

CIS researchers are currently performing advanced research in the areas of intelligent systems, advanced security systems,

autonomous mobile robots, and smart grids. The use of advanced robotics and sensor networks in home and industrial

applications presents dynamic opportunities for research discoveries. CIS researchers continue to explore several new

promising avenues of research, including the Intelligent Home System, focused on enhancing security and energy efficiency

through the power of home automation and robot technology. Additional areas of promise include the Smart Access Control

system, designed to provide optimal security, and an autonomous pipeline maintenance robot.

Students are using exciting new tools such as 3D printers, semi-

autonomous and autonomous robotic tools and techniques, and

control devices such as iPhones and iPads to create rich multimedia

control and analytic systems. CIS will use the latest 3D design tools

such as AutoCad Studio and 3D Max and other tools to provide a

platform for in-house development.

“The Discovery Lab provides a platform to develop many new ideas. The lab is comparable in its mission to labs at top universities. We are educating entrepreneurs, sustaining research and, developing products that can be commercialized. We are training the next generation of students with the 21st Century skills they need to succeed.” – Director Ram Iyengar. FIU School of Computing and Information Sciences

From left to right: undergraduate students Uwe Cerron, Leo Shao, Irvin Cardenas, Francisco Peleato, Lazaro Herrera, Michael Lazo, Daniela Chavez Guevara and Fernando De Zayas, SCIS Director and Ryder Chair Dr. Ram Iyengar, Visiting Assistant Professor Dr. Jong-Hoon Kim, Associate Professor Dr. Nagarajan Prabakar, Director of Technology Steve Luis and graduate student Sheikh Hossain.

On April 10th, 2012, State Farm awarded FIU’s Discovery Lab lead by Dr. Ram Iyengar, SCIS Director and Ryder Professor, a donation of $50,000 to further the lab’s mission to inspire student innovation. State Farm has designated FIU as one of 20 Universities in the Nation where they recruit exclusively. This grant award was one of only four such grants awarded in the area of IT Systems this year by State Farm.


Recent SCIS Contracts and GrantsSCIS Faculty Title Agency Amount Duration

Naphtali Rishe (PI), Shu-Ching Chen, Tao Li, Ming Zhao (Co-PIs)

MRI: Development of an Integrated, Geospatial Analytics Re-search Instrument

NSF $710,693 2011-2014

Geoffrey Smith (PI) TC: Small: Theory and Applications of Min-Entropy Leakage NSF $502,236 2011-2014

Deng Pan (PI) CSR: Small: A Scalable and Efficient Framework for Switch Virtualization

NSF $365,988 2011-2014

Ram Iyengar (PI) Multi University Research and Training in Protection of Critical Information Infrastructures

NSF $299,998 2011-2013

Ram Iyengar (PI) NeTS: Medium: Collaborative Research: Building an Intelligent, Uncertainty-Resilient Detection and Tracking Sensor Network

NSF $263,202 2011-2013

Jinpeng Wei (PI) Malware Persistence in OS Kernels Georgia Institute of Technology / Centre for Strategic Infocomm Technologies (Singapore)

$121,730 2011-2013

Zhenyu Yang (PI) CSR: Small: Resource Management for 3D Communication Systems

NSF $98,454 2011-2012

Xudong He (PI) SBIR Phase IIa: Petri Nets Controller for Robotic Grasping Energid / NSF $70,000 2011-2012

Christine Lisetti (PI), Naphtali Rishe (Co-PI)

Lifelike Expressive Avatars for the Instruction of Young Learners who are Deaf

Vcom-3D / NSF $70,000 2011-2012

Naphtali Rishe (PI) Knowledge Mining and Bioinformatics techniques to Advance Personalized Diagnostics and Therapeutics

NSF $49,138 2011-2012

Shu-Ching Chen (PI), Steven Luis (Co-PI)

Coordinated Damage Assessment Application Miami-Dade County Office of Emergency Management

$43,670 2011-2012

Shu-Ching Chen (PI), Scott Graham, Steve Luis (SCIS Co-Directors)

An Open-Source Integrated Computing Infrastructure to Support the Life Cycle Design and Engineering of High Performance Building

FIU Division of Research $24,935 2011-2012

Shu-Ching Chen (Co-PI)

Support for the Educational Activities at ACM Multimedia 2011 NSF $15,000 2011-2013

Tao Li (PI), Shu-Ching Chen, and Steven Luis (Co-PIs)

All-Hazard Disaster Situation Browser on Mobile Devices Eugenio Pino and Family Global Entrepreneurship Center

$10,798 2011-2012

Raju Rangaswami (PI), Jason Liu, Ming Zhao (Co-PIs)

Streamlining High-End Computing with Software Persistent Memory

NSF $759,999 2010-2012

Naphtali Rishe (PI) MRI-R2: Development of an Instrument for Information Science and Computing in Neuroscience (FIU SCIS Subaward)

NSF $752,932 2010-2013

Raju Rangaswami (PI), Giri Narasimhan (Co-PI)

CSR: Small: Energy Proportional Storage Systems NSF $504,163 2010-2013

Shu-Ching Chen (PI), Tao Li, Jinpeng Wei, Zhenyu Yang, and Ming Zhao (Co-PIs)

A Research and Educational Framework to Advance Disaster Information Management in Computer Science PhD Programs

US Dept. of Homeland Security

$400,000 2010-2014

Giri Narasimhan (PI) The Airway Microbiome in Chronic Obstructive Pulmonary Dis-ease (COPD)

University of Miami / Florida Dept. of Health

$314,408 2010-2011

Tao Li (PI) Unsupervised Learning from Multiple Information Sources Based on Non-negative Matrix Factorization (NMF)

Army Research Office $300,000 2010-2013

Naphtali Rishe (PI) RAPID: MRI: Development of Database Appliance Module for Multi-temporal Analysis and Correlation of Gulf Oil Spill Related Geospatial Data

NSF $248,000 2010-2012

Naphtali Rishe (PI) III: Gulf RAPID: Multi-temporal analysis and correlation of Gulf Oil Spill Related Geospatial Data on TerraFly Platform

NSF $161,568 2010-2012

Naphtali Rishe (PI) SBIR Phase IIa: Trust-GUARD-Enabled Secure TerraFly BlueRISC / NSF $105,000 2010-2012

Shu-Ching Chen (PI), Tao Li, Steve Luis (Co-PIs)

A Data Mining Framework for Enhancing Emergency Response Situation Reports with Multi-Agency Multi-Party Multimedia Data

Purdue Univ. / US Dept. of Homeland Security

$70,000 2010-2012


Raju Rangaswami (PI) IBM PhD Fellowship for Jorge Guerra IBM $60,000 2010-2012

Jason Liu (PI) PrimoGENI-Developing GENI Aggregates for Real-Time Large-Scale Network Simulation BBN Technologies $525,200 2009-2012

Masoud Milani (PI), Peter Clarke, Xudong He, Christine Lisetti (Co-PIs)

GAANN Fellowships in Computer Science at Florida International University

US Dept. of Education $525,128 2009-2013

Ming Zhao (PI) HECURA: Collaborative Research: QoS-driven Storage Manage-ment for High-end Computing Systems

NSF $432,343 2009-2012

Tao Li (PI) Gene Functional Prediction from Protein-Protein Interaction Data NSF $322,632 2009-2012

Niki Pissinou (PI) REU SITE: Numerical Computing and Optimization in Multidisci-plinary Applications: Methods and Software

NSF $300,000 2009-2012

Tao Li (PI) Information Delivery and Knowledge Discovery for Hurricane Disaster Management

US Dept. of Homeland Security

$199,999 2009-2012

Tao Li (PI) Collaborative Research: Non-negative Matrix Factorizations for Data Mining: Foundations, Capabilities, and Algorithms

NSF $149,981 2009-2012

Niki Pissinou (PI) Providing Secure Communication for Mobile Ad-Hoc Networks DoD / US Southern Command

$100,000 2009-2011

Naphtali Rishe (PI) TIE: UF-FIU inter-I/UCRC collaboration to explore autonomic computing for the TerraFly server system

NSF $50,000 2009-2011

Tao Li (PI) EAGER: Collaborative Research: Cross-Domain Knowledge Transformation via Matrix Decompositions

NSF $46,000 2009-2011

Naphtali Rishe (PI), Xudong He, Shu-Ching Chen (Co-PIs)

CREST: Center for Innovative Information Systems Engineering NSF $5,250,000 2008-2013

Naphtali Rishe (PI), Vagelis Hristidis, Tao Li, Raju Rangaswami (Co-PIs)

MRI: Development of a High-Performance Database Appliance for Geospatial Applications

NSF $1,084,000 2008-2013

Naphtali Rishe (PI), Shu-Ching Chen, Vagelis Hristidis, Tao Li (Co-PIs)

I/UCRC: Center for Advanced Knowledge Enablement NSF $712,000 2008-2013

Raju Rangaswami (PI)

CAREER: Active Block Layer Extensions: A Foundation for Build-ing Self-Managing Storage Systems

NSF $460,000 2008-2013

Masoud Milani (Co-PI)

Development of a Manual for New Construction Requirements and Water Consumption Data Analysis

Miami-Dade County Water & Sewer Dept.

$349,999 2008-2011

Geoffrey Smith (PI) CT-ISG: New Foundations for Quantitative Information Flow NSF $335,852 2008-2012

Naphtali Rishe (PI), Vagelis Hristidis, Raju Rangaswami (Co-PIs)

Investigation of Geospatial Data Management on Mapreduce Platform

NSF $232,000 2008-2011

Niki Pissinou (PI) SGER: A Lightweight Drive-Through Management Service for Internet-enabled Ad-Hoc Networks

NSF $150,001 2008-2011

Peter Clarke (PI) Collaborative Research: Web-Based Repository of Software Testing Tools

NSF $133,116 2008-2011

Tao Li (PI) Collaborative Research: Matrix-model Machine Learning: Unifying Machine Learning and Scientific Computing

NSF $62,000 2008-2012

Tao Li (PI) SGER: Collaborative Research: Nonnegative Matrix Factorization for Data Mining: Algorithms and Applications

NSF $44,000 2008-2011

S. Masoud Sadjadi (PI), Shu-Ching Chen, (Co-PI)

PIRE: A Global Living Laboratory for Cyberinfrastructure Application Enablement

NSF $2,279,991 2007-2012

Xudong He (PI), Masoud Milani, Peter Clarke (Co-PIs)

GAANN Fellowships in Computer Science at Florida International University

US Dept. of Education $387,165 2007-2011

Jason Liu (PI) CAREER: Immersive Large-Scale Network Simulations NSF $380,821 2007-2012

Tao Li (PI) CAREER: Mining Log Data for Computing System Management NSF $606,715 2006-2012

Shu-Ching Chen (Co-PI)

Public Hurricane Loss Projection Model Florida Dept. of Insurance Regulation

$7,880,000 2001-2013

Ram Iyengar• ACM Fellow

• IEEE Fellow

• AAAS Fellow

• SPDS Fellow

• Member European Academy of Science

• Distinguished Service Award Roy Paul Daniel’s Professor Award: 2008 - 2010

• Distinguished Research Award from Tunisian Mathematical Society: March 22, 2010

• Member of the Advisory Board for International Journal of Wireless and Mobile Computing, Inderscience Publishers: 2005 - Present

Mark A. Weiss• Dr. Mark Weiss, elected ACM Distinguished

Educator, 2011

• Excellence in Service Award, FIU SCIS: 2007

• Excellence in Teaching Award, FIU SCIS: 2005

• Excellence in Teaching Award, FIU: 1999

• Excellence in Research Award, FIU: 1994

• Teaching Incentive Program Award, FIU: 1994

• Outstanding Achievement and Performance Award, FIU: 1990

• RCA Fellowship and Merit Prize to Princeton University: 1983

• New York City First Place Winner, Putnam Mathematics Contest: 1981

Shu-Ching Chen• Dr. Shu-Ching Chen, elected ACM

Distinguished Scientist, 2011

• Best Paper Award, IEEE International Symposium on Multimedia: December 11-13, 2006

• Top Scholar Award, FIU: 2011

• Kauffman Professor Award: 2011

• The Inaugural Excellence in Graduate Mentorship Award, FIU: 2006

• Outstanding Faculty Research Award, FIU: 2004

• Excellence in Mentorship Award, FIU SCIS: 2010 and 2006

• Outstanding Faculty Service Award, FIU SCIS: 2004

• Outstanding Faculty Research Award, FIU SCIS: 2002

Xudong He• Faculty Research Excellence Award, FIU

SCIS: 2009

• Excellence in Faculty Scholarship, FIU: 2008

• Executive Dean’s Award in Service, College of Engineering and Computing, FIU: 2006

• Ranked among the top 15 scholars in Systems and Software Engineering worldwide during 1999 –2003 by Journal of Systems and Software, vol.76, no.1, 2005, 91-97.

• Faculty Award for Excellence in Research, FIU: 2005

• Faculty Service Excellence Award, FIU SCIS: 2005

• Faculty Teaching Excellence Award, FIU SCIS: 2003

Giri Narasimhan• Best Research Award, FIU SCIS: 2007

• Faculty Senate Award for Excellence in Research, FIU: 2004

• Best Research Award, FIU SCIS: 2004

• Editor, International Journal of Bioinformatics Research & Applications: 2007 - Present

• Editor, Journal of Discrete Algorithms: 2000 - Present

• Editor, Journal of Bionanoscience: 2005 – Present

Jainendra K. Navlakha• Outstanding Contributions to the

Achievement of Affirmative Action/Employment Opportunities, FIU: 1992

• Teaching Incentive Program Award, FIU: 1995 and 1996

• Excellence in Service Award, FIU SCIS: 2003

• Awarded Honorary Professorship, Universidad Nacional Daniel Alcides Carrion, School of Post Graduate Studies, Peru: 2007

• Fulbright Senior Scholar Specialists in Information Technology: 2004-2009

• Fulbright Senior Scholar Assignment to Voronezh Institute of High Technologies, Voronezh, Russia: 2007

Naphtali Rishe• Inaugural Outstanding Faculty Award, FIU:

2002

• Four US Patents

Peter J. Clarke• Excellence Award in Mentorship Award, FIU

SCIS: 2008

Tao Li• Dr. Tao Li, College of Engineering and

Computing Mentorship Award for 2011

• Scalable Data Analytics Innovation Award, IBM: 2010

• Excellence in Mentoring Award, FIU SCIS: 2009

• Excellence in Research, FIU: 2009

• NSF Faculty CAREER Award: 2006-2011

• Faculty Research Award, IBM: 2008


• US Patent Number 7,091,409 awarded jointly with Qi Li and Mitsunori Ogihara, “Music Feature Extraction Using Wavelet Co-effcient Histograms”: 2006

• Faculty Fellow for Mathematics of Knowledge and Search Engine, Institute for Pure and Applied Mathematics, UCLA

Christine Lisetti• Editorial Board of the IEEE Transactions on

Affective Computing: 2010


• Marie-Curie International Fellowship, European Commission: 2006

• Distinguished Research Lecturer Award, UCF College of Engineering and Computer Science: 2003

• Distributed Mentoring Affiliate Award, Computing Research Association-Women: 2002

• Nils Nilsson Award for Integrating AI Technologies with Prof. R. Murphy, American Association for Artificial Intelligence: 2000

• Individual Research Service Award, National Institute of Health 1998

Selected Awards and Honors


Jason Liu• Associate editor, Simulation: Transactions

of the Society for Modeling and Simulation International: 2009-2011

• Guest editor, Simulation: Transactions of the Society for Modeling and Simulation International, Special Issue on Advanced and Distributed Simulation: 2009

Nagarajan Prabakar• Teaching Incentive Program Award, FIU:

1995

• Prize for attaining the highest level of academic achievement in Computer Science Postgraduate Studies, University of Queensland M.I.M. Holdings Ltd: 1982 and 1984

• University of Queensland Postgraduate Research Scholarship: 1981 - 1984

• Gold medal for securing the first rank in B.E. at Annamalai University: 1977

Raju Ramgaswami• Faculty Award for Excellence in Research

and Creative Activities, FIU: 2011

• Faculty Award, IBM: 2011

• Faculty Fellowship, NetApp: 2011

• Top Scholar, FIU: 2010

• NSF Faculty CAREER Award: 2008-2013


• Excellence in Research Award, FIU SCIS: 2008

• US Department of Energy Early CAREER Award: 2006-2009

• University of California Dissertation Fellowship: 2004

• Dean’s Fellowship, UCSB: 1999

S. Masoud Sadjadi• Dr. S. Masoud Sadjadi, IBM Faculty Award,

2011

• Best Student Paper Award, The Twelfth IEEE International Workshop on Quality of Service: 2004

Jinpeng Wei• Best Paper Award, 2nd IEEE International

Conference on Cloud Computing Technology and Science: 2010

• Best Student Paper Award, High Performance Computing Conference: 2007

Tim Downey• University Excellence in Teaching, FIU: 2007

• Executive Dean’s Teaching Award, FIU College of Engineering and Computing: 2007

• Excellence in Teaching, FIU SCIS: 2006

• Excellence in Teaching, FIU SCIS: 2002

• University Excellence in Teaching, FIU: 2002

• Matriculation Merit Award, FIU: 2001

• Matriculation Merit Award, FIU: 1997


Kip Irvine• Excellence in Service Award, FIU SCIS: 2008


• Senior Member, ACM.

Norman Pestaina• Excellence in Teaching Award, FIU SCIS:

2007

• Best Teaching Award, FIU SCIS: 2004


• Outstanding Achievement and Performance Award, FIU SCIS: 1994

Greg Shaw• Excellence in Teaching Award, FIU: 2003

Jill Weiss• Excellence in Teaching Award, FIU SCIS

2008


SCIS graduate Jairo Pava named FIU World’s Ahead Graduate

Jairo Pava, named an FIU World’s Ahead Graduate at the Fall 2011 commencement ceremony, was born in Ibagué, a small town in Colombia. In the early 1990s, his parents fled the drug-fueled violence in Colombia and brought three-year-old Jairo to the United States. Although his parents had humble jobs in Miami, they always told Jairo that higher education would allow him to achieve his dreams. Jairo came to FIU completely undecided about his future career. But a computer science course opened his eyes to the possibilities of research.

Jairo made significant contributions to the 3-D hurricane storm surge animation and visualization project, under the mentorship of Professor Shu-Ching Chen, and served as project leader. This research led to the creation of computer simulations that will help people decide whether to evacuate when a hurricane is approaching. Miami-Dade County has made the technology available to residents and it could help other areas affected by hurricanes, as well.

Jairo won the Greater Miami Chamber of Commerce’s “Top Technology Student” award and was the only Florida student to get recognition in the 2011 Computing Research Association Outstanding Undergraduate Researcher Award competition. Jairo has co-authored and published five peer-reviewed conference papers and is writing a chapter for a scientific book series. He currently works at IBM as a software engineer, writing software for mainframes, while he applies to some of the nation’s top graduate schools.


Selected Books by Faculty


US Labs

• Jet Propulsion Lab, Pasadena, CA

• SPAWAR Systems Center Pacific (SSC-Pacific), San Diego, CA

• NOAA, Hurricane Research Division, Miami, FL

• Florida Institute for Human-Machine Cognition (IHMC), Ocala, FL

• TeraGrid, Chicago, IL

• Los Alamos National Lab, Los Alamos, NM

• Sandia National Lab, Albuquerque, NM

• Oak Ridge National Lab, Oak Ridge, TN

US Universities

• University of Alabama, Birmingham, Birmingham, AL

• San Diego State University, San Diego, CA

• University of California, Berkeley, Berkeley, CA

• University of California, Irvine, Irvine, CA

• University of California, San Diego, San Diego, CA

• University of Southern California, Los Angeles, CA

• Colorado State University, Fort Collins, CO

• Florida A&M University, Tallahassee, FL

• Florida Atlantic University, Boca Raton, FL

• Florida Institute of Technology, Melbourne, FL

• Florida State University, Tallahassee, FL

• University of Florida, Gainesville, FL

• University of Miami, Miami, FL

• University of North Florida, Jacksonville, FL

• University of South Florida, Tampa, FL

• Georgia Institute of Technology, Atlanta, GA

• Northwestern University, Chicago, IL

• Southern Illinois University, Carbondale, IL

• University of Illinois, Urbana, IL

• University of Illinois at Chicago, Chicago, IL

• Notre Dame University, South Bend, IN

• Purdue University, West Lafayette, IN

• Louisiana State University, Baton Rouge, LA

• University of Maryland, Baltimore County, Baltimore, MD

• Harvard University, Cambridge, MA

• University of Massachusetts, Lowell, MA

• University of Montana, Missoula, MT

• Rutgers University, New Brunswick, NJ

• Stony Brook University, Stony Brook, NY

• University of North Carolina, Charlotte, Charlotte, NC

• North Dakota State University, Fargo, ND

• University of Pittsburgh, Pittsburgh, PA

• Clemson University, Clemson, SC

• Dakota State University, Madison, SD

• East Tennessee State University, Johnson City, TN

• Memphis University, Memphis, TN

• University of Houston, Houston, TX

• University of Puerto Rico, Mayaguez, Mayaguez, PR

US Industry

• IBM Research - Almaden, Almaden, CA

• VMware, Palo Alto, CA

• IBM Research – Watson Research Center, Hawthorne, NY

• Marvell Semiconductor

• Motorola Applied Research Center, Schaumburg, IL

• IBM Research – Watson Research Center, Yorktown Heights, NY

• Raytheon

• Ultimate Software, FL

• Vcom3d, Orlando, FL

Iyengar

Chen

He

Narasimhan

Navlakha + Abi

Rishe

Clarke

Lisetti

Liu

Milani

Rangaswami

Sadjadi

Smith

Carbunar

Pan

Wei

Yang

Zhao

Selected Research and Collaboration

Responding faculty:


International Research Labs

• NICTA, Syndey, Australia

• Digiteo, http://www.digiteo.fr, Saclay, France

• French National Center for Scientific Research (CNRS), Paris, France

• Laboratoire d’Informatique (LIX) of the École Polytechnique, http://www.lix.polytechnique.fr/, Palaiseau, France

• National Institute for Research in Computer Science and Control (INRIA), Bordeaux, France

• National Institute for Research in Computer Science and Control (INRIA), Rennes, France

• National Institute for Research in Computer Science and Control (INRIA), Saclay, France

• Renal Epidemiology Information Network, Paris, France

• Korean Advance Institute of Science and Technology (KAIST), Seoul, Korea

• Center for Strategic Infocomm Technology (CSIT), Singapore

• Barcelona Supercomputing Center, Barcelona, Spain

International Universities

• National University of La Plata, La Plata, Argentina

• Fluminese Federal University, Niterói, Brazil

• Universidade Federal de Goiás, Goiás, Brazil

• University of Brazil, Rio de Janeiro, Brazil

• University of São Paulo, São Paulo, Brazil

• Carleton University, Ottawa, Ontario, Canada

• University of Waterloo, Waterloo, Ontario, Canada

• Hefei University of Technology, Hefei, Anhui, China

• Qingdao University, Qingdao, China

• Tianjin University of Technology, Tianjin, China

• Tsinghua University, Beijing, China

• University of Science and Technology of China, Hefei, Anhui, China

• Xiamen University, Xiamen, Fujian, China

• Zhengzhou University, Zhenzhou, China

• Télécom ParisTech, Paris, France

• University of Rennes 1, Rennes, France

• TU Berlin – Berlin Institute of Technology, Berlin, Germany

• University of Bamberg, Bamberg, Germany

• University of Bonn, Bonn, Germany

• Indian Institute of Science, Bangalore, India

• Indian Institute of Technology, Indore, India

• India Statistical Institute, Bangalore, India

• National University of Ireland, Maynooth, Maynooth, Ireland

• Technion – Israel Institute of Technology, Haifa, Israel

• Tel Aviv University, Tel Aviv, Israel

• University of Milan, Crema, Italy

• University of Tsukuba, Tsukuba, Ibaraki, Japan

• University of Guadalajara, Guadalajara, Mexico

• Eindhoven University of Technology, Eindhoven, Netherlands

• Utrecht University, Utrecht, Netherlands

• Dubna International University, Dubna, Russia

• Moscow State University, Moscow, Russia

• National University of Singapore, Queenstown, Singapore

• Complutense University of Madrid, Madrid, Spain

• Technical University of Catalonia, Barcelona, Spain

• University of Castilla-La Mancha, Ciudad Real, Spain

• Pompeu Fabra University, Barcelona, Spain

International Industry

• IBM Research – China, Beijing, China

• Microsoft Research Asia, Beijing, China

• Cloud VPS

• Oracle China, Hefei, China

• Dialonics, Lannion, France

• IBM Research – India, New Delhi, India

• IBM Research – India, Bangalore, India

• IBM Research – Israel, Haifa, Israel

• IBM Research – Tokyo, Tokyo, Japan

• Yahoo! Labs Barcelona, Barcelona, Spain

• Kaseya, Switzerland


Computer Science and Technology Curriculum

Graduate Courses

CAP 5011 Multimedia Systems and Applications

CAP 5510C Introduction to Bioinformatics

CAP 5602 Introduction to Artificial Intelligence

CAP 5610 Introduction to Machine Learning

CAP 5627 Affective Intelligent Agents

CAP 5701 Advanced Computer Graphics

CAP 5771 Principles of Data Mining

CAP 6776 Advanced Topics in Information Retrieval

CAP 6778 Advance Topics in Data Mining

CDA 5312 Micro Processing for Software Design

CDA 5655 Virtualized Systems

CDA 6939 Special Topics: Advanced Topics in Computer Architecture

CEN 5011 Advanced Software Engineering

CEN 5064 Software Design

CEN 5076 Software Testing

CEN 5082 Grid Enablement of Scientific Applications

CEN 5087 Software and Data Modeling

CEN 5120 Expert Systems

CEN 6070 Software Verification

CEN 6075 Software Specification

CEN 6501 Distributed Processing

CEN 6502 Advanced Topics in Concurrent and Distributed Systems

CGS 5166 Introduction to Bioinformatics Tools

CIS 5027 Computer Systems Fundamentals

CIS 5346 Storage Systems

CIS 5372 Information Assurance

CIS 5373 Systems Security

CIS 5374 Information Security and Privacy

CIS 5900 Independent Study

CIS 5910 Project Research

CIS 5915 Research Experience for Graduate Students

CIS 5931 Special Topics

CIS 6612 Special Topics: Advanced Topics in Software Engineering


CIS 6930 Special Topics: eHealth and Affective Computing

CIS 6931 Special Topics: Advanced Topics in Information Processing

CIS 6933 Computer Science Seminar

CIS 6970 Thesis

CIS 7910 Graduate Research

CIS 7980 Ph.D. Dissertation

CNT 6207 Distributed Processing

CNT 6208 Advanced Topics in Concurrent and Distributed Systems

COP 5614 Operating Systems

COP 5621 Compiler Construction

COP 5725 Principles of Database Management Systems

COP 5949 Cooperative Education in Computer Science

COP 6545 Advanced Database Management

COP 6556 Semantics of Programming Languages

COP 6611 Advanced Operating Systems

COP 6727 Advanced Database Systems

COP 6795 Special Topics on Databases

COT 5407 Introduction to Algorithms

COT 5420 Theory of Computation I

COT 6405 Analysis of Algorithms

COT 6421 Theory of Computation II

COT 6930 Special Topics: Advanced Topics in Theory

COT 6931 Topics in Cognitive Science

COT 6936 Topics in Algorithms

TCN 5010 Telecommunication Technology and Applications

TCN 5030 Computer Communications Network Technologies

TCN 5060 Telecommunications Software and Methods

TCN 5080 Secure Telecommunication Transactions

TCN 5150 Multimedia Computer Communications

TCN 5440 Telecommunication Software Development

TCN 5445 Telecommunication Network Programming

TCN 5455 Information Theory

TCN 5640 Telecommunications Enterprise Planning and Strategy

TCM 6210 Telecommunication Network Analysis and Design

TCN 6215 Advanced Network Algorithms

TCN 6230 Optical Networks

TCN 6260 Internetworking

TCN 6270 Mobile and Wireless Networks

TCN 6275 Mobile Computing

TCN 6420 Modeling and Performance Evaluation of Telecommunications Networks

TCN 6430 Networks Management and Control Standards

TCN 6450 Wireless Information Systems

TCN 6820 Industrial Development of Telecommunications

TCN 6880 Telecommunications Public Policy Development and Standards

TCN 6935 Graduate Seminar

Undergraduate Courses

Computer Science Undergraduate Courses

CAP 4710 Principles of Computer Graphics

CAP 4770 Introduction to Data Mining

CDA 3003 Microcomputer Organization

CDA 3103 Fundamentals of Computer Systems

CDA 4101 Structured Computer Organization

CEN 3721 Human Computer Interaction

CEN 4010 Software Engineering I

CEN 4021 Software Engineering II

CEN 4072 Software Testing

CGS 1920 Introduction to Computing

CGS 2060 Introduction to Microcomputers

CGS 2100 Introduction to Microcomputer Applications for Business

CGS 2518 Computer Data Analysis

CGS 3095 Technology in the Global Arena

CGS 3416 Web-based Programming

CGS 3559 Using the Internet

CGS 3767 Computer Operating Systems

CGS 4285 Applied Computer Networking

CGS 4365 Knowledge-based Management Systems

CGS 4854 Web Site Construction and Management


CIS 3930 Special Topics

CIS 4431 IT Automation


CIS 4911 Senior Project

CIS 4912 Research Experience for Undergraduate Student

COP 1000 Introduction to Computer Programming

COP 2210 Computer Programming I

COP 2250 Programming in Java

COP 2270 C for Engineers

COP 3175 Programming in Visual Basic

COP 3337 Computer Programming II

COP 3353 Introduction to Using UNIX/Linux

COP 3465 Data Structures for IT

COP 3530 Data Structures

COP 3804 Intermediate Java

COP 3832 Advanced Web Server Communication

COP 3835 Designing Web Pages


COP 4005 Windows Programming for IT

COP 4009 Windows Components Technology

COP 4226 Advanced Windows Programming

COP 4338 Computer Programming III

COP 4520 Introduction to Parallel Computing

COP 4555 Principles of Programming Languages

COP 4604 Advanced UNIX Programming

COP 4610 Operating Systems Principles

COP 4655 Mobile Application Development

COP 4703 Information Storage and Retrieval

COP 4710 Database Management

COP 4722 Database survey

COP 4813 Web Application Programming

COP 4814 Component Based Development

COP 4906 Research Experience in Computer Science


COT 3420 Logic for Computer Science

CNT 4403 Computer and Network Security

CNT 4504 Network Administration

CNT 4513 Data Communications

CTS 4348 UNIX Administration

CTS 4408 Database Administration


Alumni Updates

Dr. Konstantin (Kosta) Beznosov is an Associate Professor

at the Department of Electrical and Computer Engineering,

University of British Columbia, where he directs the

Laboratory for Education and Research in Secure Systems

Engineering. His research interests are usable security,

distributed systems security, and access control. Prior UBC,

he was a Security Architect at Hitachi Computer Products

(America) and Concept Five. He received Ph.D. in Computer

Science at FIU in 2000. He recently returned to FIU to give a talk entitled: On the

Feasibility, Effectiveness, and Implications of Socialbot Nets.

Irene Polycarpou is an Assistant Professor at the

Department of Mathematical and Computer Sciences at

Colorado School of Mines. Her research interests are in

computer science education, students’ cognition and learning

styles, instructional software, and educational technologies.

Polycarpou received her BS, MS, and Ph.D. degrees in

Computer Science from Florida International University in

2002, 2004 and 2008, respectively.

Dr. James O’Brien, received his B.S. in Computer Science

from FIU in 1992, is a Professor in the Department of

Electrical Engineering and Computer Sciences at the

University of California at Berkeley, where he conducts

research in the area of computer graphics. He is the 2006

FIU Torch Award recipient as well as winning honors in Time

Magizine, Technology Review and SIGGraph.

Dr. Tariq M. King is a tenure-track Assistant Professor in

the Department of Computer Science at North Dakota State

University (NDSU). He joined NDSU in August 2009 after

graduating with his PhD in Computer Science from Florida

International University, Miami. In Spring 2010, Dr. King

founded the Software Testing Research Group (STRG) at

NDSU to provide students with a collaborative environment

for conducting research in software testing. Dr. King also

serves as a co-principal investigator on an NIH SBIR Phase II subaward from

WoWiWe Instruction Co. In his role at WoWiWe, Dr. King leads the software

testing team and provides software engineering expertise for the products being

developed.

Student Accomplishments and Outreach

SCIS Award Winners:

• Outstanding IT Graduate: Cesar Rojas

• Outstanding CS Graduate: Paul Vonnehring

• 2012 Finalists for Greater Miami Chamber for

Commerce Student Technology Leaders:

Luis Masieri, Jessie Domack

• FIU ACM High School Programming Contest,

March 24

– Over 20 teams from schools in South

Florida, Orlando and Tampa areas

Game Developers Guild

• Incubator for Game Developers

– Organizer: Frank Hernandez,

CS PhD student

– 20+ students/professionals participate

– Advisor: Steve Luis

www.gamedevelopersguild.com

• Organized International Game Developers

Association Global Game Jam in Miami

– Teams created 5 games in 48 hours

– Support from Game Development Studios

such as Blizzard and Unity

– Created significant visibility in the SFL

Tech Community

• Developed Apps for Andriod Market and

Blackberry Markets

– Knowledge Pets

• Started Kickstarter project: Video Game for

the Blind

• Supporting USTLA STEM Tech Challenge on

April 27th

• Next Hackathon in June, 2012



Selected PhD Graduate Employment Profile

STUDENT Major ProfESSor TErM awarDED PhD DISSErTaTIoN TITlE EMPloyMENT

Dmitry Vasilevsky Naphtali Rishe Spring 2004 Design Principles of Semantic Binary Database Management Systems

Microsoft

Yanli Sun Naphtali Rishe Summer 2004 3D TerraFly Quality of Service Management for Online Interactive 3D Geographical Information System

Industry Research, China

Chengcui Zhang Shu-Ching Chen Summer 2004 A Multimedia Indexing and Retrieval Framework for Multimedia Database Systems

Associate Professor, Univeristy of Alabama, Birmingham

Xiangyu Ye Naphtali Rishe Summer 2004 An Indexing Structure and Application Model for Vehicles Moving on Road Networks

Consultant

Lian Mo Xudong He Spring 2005 Refinement Methods for Software Architecture Design Using the Software Architecture Model

Software Engineer, Citrix Systems

Mario Sanchez Naphtali Rishe Spring 2005 Data Structures for Highly Efficient Querying of Spatial Data

Associate Professor, Miami Dade College

Li Yang Raimund Ege Summer 2005 Security Specification and Enforcement in Mediation System

Associate Professor, University of Tennessee at Chattanooga

Qasem Kharma Raimund Ege Summer 2005 Enhanced Skip-List Search Algorithm in 3-Layer Mediator Framework

Assistant Professor, Yarmouk University, Jordan

Shu Gao Yi Deng and Xudong He Fall 2005 An Aspect-Oriented Approach to Designing Role-Based Access Control Services

Software Engineer, Beckman Coulter

Andriy Selivonenko Naphtali Rishe Fall 2005 Data Partitioning and Replication Management in Distributed GIS Database

Chief Technology Officer, mphrx.com

Tianjun Shi Xudong He Spring 2006 A Framework for Specification and Analysis of Software Architectures

Software Development Engineer, Microsoft

Zhijiang Dong Xudong He Summer 2006 A Framework for Transforming, Analyzing, and Realizing Software Designs in Unified Modeling Language

Assistant Professor, Middle Tennessee State University

Chengyong Yang Giri Narasimhan Summer 2006 Knowledge Discovery using Multiple Sources of Biological Data

Algorithm Lead, Life Technologies

Patricia Buendia Giri Narasimhan Fall 2006 Phylogenetic Analysis of within-Host Serially-Sampled Viral Data

Bioinformatics Software Engineer, Infotech Soft

Gaolin Zheng Giri Narasimhan Fall 2006 Statistical Analysis of Biomedical Data with Emphasis on Data Integration

Assistant Professor, North Carolina Central University

Yujian Fu Xudong He Spring 2007 An Integrated Framework for Ensuring the Quality of Software Design

Assistant Professor, Department of Computer Science, Alabama A & M University

Min Chen Shu-Ching Chen Spring 2007 Knowledge Assisted Data Management and Retrieval in Multimedia Database Systems

Assistant Professor, University of Montana

Jianhua Yen Shu-Ching Chen Summer 2007 A Framework for Automatic Feature Extraction from LIDAR Data

Senior Software Developer, Paypal

Onyeka Ezenwoye Masoud Sadjadi Summer 2007 Enabling Adaptability in Service Aggregates using Transparent Shaping Techniques

Assistant Professor, Augusta State University

Na Zhao Shu-Ching Chen Fall 2007 DiMuSe: An Integrated Framework for Distributed Multimedia System with Database Management

Quant Trader, Aien Captial and Aien Technology

David Kaiser Tao Li Fall 2007 The Structure of Games Director of Institutional Research, Miami Dade College


STUDENT Major ProfESSor TErM awarDED PhD DISSErTaTIoN TITlE EMPloyMENT

Weixiang Sun Yi Deng and Xudong He Spring 2008 An Approach for Design and Analysis of User-centric Communication Middleware

Software Development Engineer, Amazon.com

Daniel Cazalis Geoffrey Smith Fall 2007 Algebraic Theory of Finite Nondeterministic Automata with Applications

Instructor, Barry University

Wei Peng Tao Li Spring 2008 Actionable Pattern Analysis in Computer and BI Systems

Research Member, Xerox Innovation Group

Jose Morales Yi Deng and Peter Clarke Spring 2008 A Behavior Based Approach to Virus Detection Academic Researcher for CERT, Carnegie-Mellon University

Irene Polycarpou Ana Pasztor Summer 2008 An Innovative Approach to Teaching Structural Induction for Computer Science

Assistant Professor, Colorado School of Mines

Erliang Zeng Giri Narasimhan Summer 2008 Bioinformatic Analysis for Exploring Relationships Between Genes and Gene Products

Research Assistant Professor, Notre Dame

Gonzalo Argote-Garcia

Xudong He Spring 2009 Formal Verification and Testing of Software Architectural Models


Ramakrishna Varadarjan

Vagelis Hristidis Spring 2009 Ranked Search on Data Graphs Software Engineer, Vertica Systems and HP Company

Tariq King Peter Clarke Summer 2009 A Self-Testing Approach for Autonomic Software Assistant Professor, North Dakota State University

Medha Bhadkamar Raju Rangaswami Summer 2009 Improving I/O Performance Through Layout Optimizations

Research Scientist, Los Alamos National Laboratory

Fernando Farfan Vagelis Hristidis Fall 2009 Efficient Storage and Domain-Specific Information Discovery on Semi-structured Documents

Postdoctoral Research Associate, University of Michigan

Nestor Andres Parra Giri Narasimhan Fall 2009 Rigid and Non-Rigid Point-Based Medical Image Registration

Intermediate Programmer, Miller School of Medicine, University of Miami

Kasturi Chatterjee Shu-Ching Chen Summer 2010 A Generalized Multidimensional Index Structure for Multimedia Data to Support Content-Based Similarity Searches in a Collaborative Search Environment

Software Engineer, Technorati Media

Dingding Wang Tao Li Fall 2010 Document Understanding Using Data Mining and Machine Learning Techniques

Research Fellow, Center for Computational Science, University of Miami

Andrew Allen Peter Clarke Spring 2011 Abstractions to Support Dynamic Adaptation of Communication Frameworks For User-Centric Communication

Visiting Assistant Professor, Georgia Southern University

Rafael Alpizar Geoffrey Smith Spring 2011 Secure Information Flow Via Stripping and Fast Simulation

IT Director, City of Doral

Lily Chang Xudong He Spring 2011 A Nested Petri Net Framework for Modeling and Analyzing Multi-Agent Systems

Assistant Professor, University of Wisconsin - Platteville

Bo Shao Tao Li Spring 2011 User-Centric Music Information Retrieval Database Administrator, Florida Department of Transportation

Zhengguo Sun Naphtali Rishe Spring 2011 Large Scale 3D Construction from Satellite/Aerial Imagery and Digital Elevation Models


Yali Wu Peter Clarke Summer 2011 A Domain-Specific Modeling Approach for Coordinating User-Centric Communication Services

Assistant Professor, University of Detroit Mercy


The School of Computing and Information Sciences (SCIS) main-

tains a data center, research and instructional labs, and computer

classroom facilities. These facilities are housed in the Engineering

and Computer Science Building (ECS) on the Modesto A. Maidique

Campus located in Miami, Fl. The facility is maintained by a dedi-

cated professional IT support staff as noted in the staffing section

below.

The School provides computing services such as file, compute,

web, email, XMPP, backup, print, and other computing services.

Our networking services include a 10 Gigabit Ethernet core network

that interconnects rack mounted swtiches and servers. All school

desktop systems are connected by 1 Gigabit switched ports. Our

network is highly redundant with multiple fiber and copper paths

and is designed with routing fail-over capacity. We provide auto-

mated monitoring of our network and servers 24x7. The building

subscribes to the university 802.11 WiFi network and maintains a

legacy research WiFi network. Our network interconnects at 10GBs

to the campus backbone, which provides a 10GBs connection to

the NAP of the Americas to provide for connections to Internet,

Internet2, Florida and National Lambda Rail, and CLARA (South

American Research) networks.

Our systems feature a variety of open source and commercial de-

velopment and scientific software products from numerous vendors

including IBM, Microsoft, ESRI, MathWorks, etc. We provide middle-

ware technologies to support web services. Our environment takes

advantage of hundreds of open source software solutions including

Apache with full mods., PHP, Perl, and many others.

Notable Shared Computing Infrastructure• Primary File Server: Silicon Mechanics Storform nServ A513, 2x

Opteron 6140 proc, 128gb ram, Intel 82576 dual port gigabit nic, 12x 3tb 7.2k hdd (30TB usable)

• Mail Server: Dell Poweredge 2900 III, 32gb ram, 2x Intel Xeon 5410 proc, 4x 300gb hdd, 500gb PCIe Solid State Disk, gigabit nic,

• Domain Controllers: (2) Dell Poweredge R210, 8gb ram, Intel Xeon X3430 2.4ghz proc, raid 1, gigabit nic, 2x 250gb 7.2k hdd

• Computing Server: (1) Dell Poweredge R210, 8gb ram, Intel Xeon X3430 2.4ghz proc, raid 1, gigabit nic, 2x 250gb 7.2k hdd

• Webserver and Learning Management System:

• (2) Dell Poweredge R310, 16gb ram, Intel Xeon X3470 2.93ghz proc, raid 5, gigabit nic, 4x 600gb 15k hdd

• Dell Poweredge 2900 III, 32gb ram, 2x Intel Xeon 5410 proc, 4x 300gb hdd, gigabit nic,

• Instructional Clusters:

• IBM Blade Center – 5 dual processor Intel blades, 2 dual pro-cessor Power blades. 23+TB of IBM SANS disk storage. Linux operating system.

• Dedicated 12+ node research and instructional Linux Beowulf cluster.

• Online Backups: (2) Silicon Mechanics Storform nServ A513, 1x Opteron 6124 proc, 8gb ram, Intel 82576 dual port gigabit nic, 12x 3tb 7.2k hdd

• Tape Backup Capacity: 45TB, LTO3 and LTO4

Dedicated Shared Research and Instructional Infrastructure• Virtual Machine Servers: (2) Dell Poweredge R900, 64gb ram, 4x

Quad Core Xeon E7340 2.4ghz proc, raid 5, gigabit nic, 4x 400gb 10k hdd; (3) Dell Poweredge R410, 64gb ram, 2x Intel Xeon E5620 2.4ghz proc, raid 5, gigabit nic, 4x 600gb 15k hdd

• General Compute Servers:

• (2) Dell Poweredge 29xx, 64gb+ ram, Intel Xeon proc,

• (3) Dell Poweredge R410, 64gb ram, 2x Intel Xeon X5650, gigabit nic, 3x 600gb hdd

• (2) Dell Poweredge R710, 72gb ram, 2x Intel Xeon X5570, gigabit nic, 8x 300gb hdd

Offsite Business Continuity Infrastructure• General Compute Server: Dell Poweredge R410, 64gb ram, 2x In-

tel Xeon E5620 2.4ghz proc, raid 5, gigabit nic, 4x 600gb 15k hdd

• 30TB Online Backup server: Silicon Mechanics Storform nServ A513, 2x Opteron 6140 proc, 128gb ram, Intel 82576 dual port gigabit nic, 12x 3tb 7.2k hdd

Student Laboratories

SCIS operates four instructional laboratories for use by undergradu-

ates and graduate students in support of our computer science and

information technology degree programs. Our instructional labs of-

fers students access to Windows 7/XP, CentOS Linux, and Mac OS

X which run a variety of software development tools, libraries, data-

bases, and have the capacity to host virtual machines. The specific

lab equipment is listed in sections below. The School has dedicated

servers for student files and/or computing services and a printer in

each lab. Each student receives at least 1,000MB of backed up file

storage space. Students can login remotely into several Linux and

Solaris file and compute servers. The labs provide a “laptop bar” for

students to connect their laptops to the SCIS network and a “de-

sign bar” outfitted with 42” LCD displays where students are able to

collaborate on programming assignments or other joint projects. In

addition, the lab and a majority of the ECS building provide 802.11b

wireless service. The school maintains a computer training class-

room also noted in the specifications below.

ECS 241 - John C. Comfort Lab I Advanced Undergraduate Lab• (44) Dell Precision T1500, Quad Core i7-860 2.8ghz, 4gb ram,

250gb hdd, nVidia Quardo NVS295, 1gb to desktop, 16x dvd rw, dual 19in or single 24in display

• (2) Apple iMac 27 Quad Core i7 2.8ghz, ATI Radeon HD 4850, 4gb, 1tb hdd, 8x Superdrive

Shared Computing Facilities and Laboratories

• (2) 42” Display LCD Monitors for group projects

ECS 237 - John C. Comfort Lab II Advanced Undergraduate Lab• (8) Apple iMac 27, Quad Core i5 2.7 (2nd gen), AMD Radeon

HD 6770M, 1tb hdd, 8gb, 8x Superdive


• (5) Dell Precision T1500, Quad Core i7-860 2.8ghz, 4gb ram, 250gb hdd, nVidia Quardo NVS295, 16x dvd rw, single 24in display

• (15) Dell Precision T1600, Dual Core i3-2100 (2nd gen) 3.1 ghz, 1gb nVidia Quadro 600, 8gb, 250gb hdd, 16x dvd rw, P2411H display

ECS 256 - Networking Lab• (48) Dell Optiplex gx760 Core2Duo e8400, 4gb, 320gb hdd,

16xdvd rw, ATI Radeon HD 3450

• (7) Dell Precision T1500, Quad Core i7-860 2.8ghz, 4gb ram, 250gb hdd, nVidia Quardo NVS295, 16x dvd rw, single 24in display

• Cisco routers, switches and KVMs necessary to manage

ECS 252 - Graduate Lab• (12) Dell Precision T1500, Quad Core i7-860 2.8ghz, 4gb

ram, 250gb hdd, nVidia Quardo NVS295, 16x dvd rw, dual 19in or single 24in display


• (2) 42” Display LCD Monitors for group projects.

ECS 141 - Instructional Lab (ILab)• (48) Dell Precision T1600, Dual Core i3-2100 (2nd gen) 3.1

ghz, 1gb nVidia Quadro 600, 8gb, 250gb hdd, 16x dvd rw, P2210 display

Staffing

The school maintains all its computing facilities (total research

and instruction: 25 labs, 350+ desktops, 100+ servers, layer

2 and 3 networking) via a dedicated Technology Group. The

SCIS Technology Group consists of 4 FTE of permanent

professional staff assigned to all of the school’s research and

instructional laboratories management. In addition, there are

at least 2 FTE of temporary students specifically assigned to

laboratory assistance. The SCIS Technology Group staff is

organized into two groups: Engineering Services, including

Networking, Systems, Desktop, and Help Desk Support, and

Business Services including Technology Procurement, Asset

Management, and Budget/Contract Management.

Industry Advisory BoardPete MartinezIndustry Advisory Board ChairSenior Vice President for Technology Development and Board Chairman Palm Beach Medical College

Dr. Roy GerberIndustry Advisory Board Vice-ChairManaging Member, L3W, LLC

Jaime Borras CEO, Wireless Silicon Group and Senior Fellow at Motorola Mobile Devices

Harald BraunCEO, Director and Executive Vice President Big Bang Networks, Inc.Former Industry Advisory Board Chair

Ruben BravoConsultant at Kennetropy, LLC Former Director, Microsoft LatAm

Michael BuchenhornerP.A., Patent Law

Christopher FleckVice President Platform Development, Citrix Systems, Inc.,

Jorge ReyDirector of Information Security and Compliance, Kaufman, Rossin & Co., P.A.

Dr. Hanafy MeleisPresident of Palmetto Capital Fund, LLCFormer CEO, Trendium, Inc.

John Nygard IIICIO, Lennar Corporation

Steven ReidVice President of Software Engineering, Ultimate Software

Dr. Marek RusinkiewiczVice President of Research, Applied Communication Sciences

Daisy SantanaProgram Director, Industry Enablement, SWG, IBM

Michael Shen, MD, MS, FACC, FASNCHead of the Section of Cardiac Imaging Staff Physician, Department of Cardiology, Cleveland Clinic Florida

Bert SilvestreIBM General Business Leader - Florida, GeorgiaPuerto Rico, Senior Location Executive

Ravi M. UgaleManaging Director, Catalyst Financial


11200 SW 8th Street Modesto A. Maidique, ECS 354Miami, FL 33199305.348.2744

cis.fiu.eduCIS_12037_7-12

Miami, a vibrant and multi-cultural city known as the technological and financial hub of the Americas, is the home of the FIU School of Computing and Information Sciences.

NONPROFIT ORG

US POSTAGE

PAIDMIAMI, FL

PERMIT NO. 3675