School of Information Technology and Mathematical … ITMS Project Book...School of Information Technology and Mathematical Sciences Research Project Booklet 2016/2017 The School of

School of Information Technology and Mathematical Sciences

Research Project Booklet 2016/2017

The School of Information Technology & Mathematical Sciences is the largest information and communications technology provider in South Australia, and is regarded as one of the leading applied mathematics departments in Australia.

We offer undergraduate, honours and postgraduate degrees in information technology, mathematics and statistics, science, software engineering, data science, and library and information management. Our programs emphasise the development of critical thinking, creativity and hands-on learning to produce graduates who are in high demand.

The School of ITMS offers students unique opportunities including an Australia First with the Bachelor of Information Technology (Hon-ours) (Enterprise Business Solutions) which offers a 12 month paid internship with Hewlett Packard Enterprise , scholarships for new and commencing students, summer vacation scholarships and opportunities to work closely with industry.

We also understand the value of engaging potential students early, offering educational programs and resources for high school students and the general community, with the Maths Experience Program for Year 10 students and free IT workshops for Year 9-11 students.

The School provides excellent opportunities for research through our research institutes and centres: Advanced Computing Research Centre (ACRC), Centre for Industrial and Applied Mathematics (CIAM), Institute for Telecommunications Research (ITR),Phenomics and Bioinformatics Research Centre (PBRC)

ph: +61 8 8302 3582 [email protected]

Advanced Computing Research Centre (ACRC)

Director: Professor Markus Stumptner Deputy Director: Professor Bruce Thomas

The Advanced Computing Research Centre (ACRC) maintains a number of relationships and links with prominent Australian and international IT organisations and international universities that have translated into many benefits for our students.

It is one of the largest Research Centres at UniSA, and combines academic rigour and research experience with a highly collaborative approach to provide new and effective computing solutions.

The ACRC members work on cutting edge research across intelligent software engineering, security and information assurance, data ana-lytics and business intelligence.

CRICOS provider number 00121B

Division of Information Technology, Engineering & the Environment

School of Information Technology & Mathematical Sciences

Institute for Telecommunications Research

Acting Director: Associate Professor Gottfried Lechner

The Institute for Telecommunications Research (ITR) is an internationally recognised research group specialised in research and technology development for wireless communication. This includes both fixed and mobile, satellite and terrestrial based applications.

Strong national and international relationships and collaborations with the telecommunications business community ensure our work has a high degree of relevance to the problems facing the wireless communications industry.

Phenomics and Bioinformatics Research Centre (PBRC)

Director: Professor Stan Miklavcic

The Phenomics and Bioinformatics Research Centre (PBRC) aims to enable fundamental advances in biological science through the development and application of mathematical, statistical and computational techniques.

One of the primary undertakings of the PBRC is research in biomathematics, biostatistics and bioinformatics to support the biological studies being undertaken by plant scientists in their quest for an understanding of plant function, particularly the mechanisms responsible for abiotic stress tolerance of cereal plants.

The PBRC receives support from numerous sponsors, including the Government of South Australia, the Australian Research Council, the Grains Research and Development Corporation and industry investors.

Centre for Industrial and Applied Mathematics (CIAM)

Director: Professor John Boland

The Centre for Applied Mathematics (CIAM) brings together researchers in pure and applied mathematics to discover, understand and interpret natural phenomena and apply mathematics to important industrial and social problems.

CIAM researchers work with industry on a broad range of research and consulting projects including: optimal train control and train scheduling, crew rostering, assignment of grain to customers to satifsy orders and maximise profits, forcasting renewalable energy generation, minerals processing and management of water catchments.

Disclaimer: While every effort is made to provide full and accurate information at the time of publication, the University does not give any warranties in relation to accuracy or completeness of the contents.

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Contents Page

PART 1: Advanced Computing Research Centre 2 As one of the largest Research Centres at UniSA, the ACRC is home to a network of dedicated and highly esteemed

researchers, staff, Higher Degree by Research students and Alumni. With more than 30 members and 70 PhD students

working on cutting edge research across intelligent software engineering, visualisation and augmented reality, health

informatics, security and information assurance, data analytics and business intelligence, our research interests are

diverse yet complementary.

Data Analytics Projects 4

Deep Neural Networks and Parallel Computing Projects 11

Knowledge and Software Engineering Projects 12

Strategic Information Management Projects 17

Wearable Computer Projects 22

PART II: Centre for Industrial and Applied Mathematics 29 Mathematics is an enabling discipline that underpins science, engineering and technology. The Centre for Industrial

and Applied Mathematics (CIAM) brings together researchers in pure and applied mathematics to discover, understand

and interpret natural phenomena and apply mathematics to important industrial and social problems.

The Centre also seeks to develop new research strengths in mathematics and statistics and train the next generation of

mathematical scientists.

CIAM research themes include:

Mathematical analysis

Modelling of systems and processes

Optimisation and optimal control

Signal and image processing

Scheduling and control for transportation systems and water management

Financial mathematics and risk management

Each theme provides a focus for specialist mathematical research and consulting in particular fields of industrial and

applied mathematics.

Centre for Industrial and Applied Mathematics Projects 29

PART III: Institute for Telecommunications Research 33 The Institute for Telecommunications Research is an internationally recognised research organisation, specialising in

research, education, and technology development for wireless communications with fixed, mobile, satellite and

terrestrial applications. ITR conducts its research in four main areas: satellite communications, high speed data

communications, flexible radios and networks and computational and theoretical neuroscience.

Computational and Theoretical Neuroscience Projects 34

Free Space Optical Communications Projects 34

Information Theory Projects 35

Networks, Transmission and Coding Topics Projects 36

Software Defined Radio Projects 38

Waveforms and Algorithms Projects 38

PART IV: Phenomics and Bioinformatics Research Centre 40 The Phenomics and Bioinformatics Research Centre (PBRC) aims to enable fundamental advances in biological science

through the development and application of mathematical, statistical and computational techniques Our research is

applicable to a variety of important problems, including improving the resilience of food crops to environmental

stresses.

Phenomics and Bioinformatics Projects 40

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PART 1: ADVANCED COMPUTING RESEARCH CENTRE (ACRC)

Page

DATA ANALYTICS 4 Analytical methods for detection of social media manipulation 4

Automatic labelling of tweets in civil unrest prediction 4

Computer vision applications with unmanned vehicles 4

Developing novel data mining techniques for mining educational data 5

Discovery and use of Twitter network structural features for civil unrest prediction 5

Effective time series feature selection for civil unrest prediction using social media data 5

Efficient Causal Inference in Big Data 6

Identifying cancer subtypes from multi‐levelled biological data with computational methods 6

Implied Comparative Advantage of Australian Economic Complexity 7

Integrated Policing: Generating queries for identity resolution 7

Integrated Policing: Model relationships from text data for identity resolution 7

Integrated Prediction with Multiple Data Sources and Credibility Assessment 8

Integration and visualisation of multiple civil unrest prediction models 8

Interpretable classification and prediction of civil unrest events 8

Investigating genetic causes of cancer through complex gene regulatory networks 9

Multimedia Systems (2D and 3D video coding and video streaming, robotics vision, cloud‐based

video services, panoramic video analysis, video surveillance and monitoring, multimedia data mining,

multimedia sensor networks, medical imaging) 9

Precursor Pattern Analysis and Interpretable Classification 10

Prediction of civil unrest events with news and other data sources 10

Signal processing and analysis for medical imaging 10

DEEP NEURAL NETWORKS AND PARALLEL COMPUTING PROJECTS 11 360 Degree Cameras: Image Analysis Algorithms 11

Deep Neural Networks for Anomaly Detection and Decision Making in Personal Budgeting 11

Deep Neural Networks for Image Understanding 11

KNOWLEDGE AND SOFTWARE ENGINEERING 12 Agile Model‐Driven Visualisation of Big Data 12

Business Process Management for the Internet of Things 12

Co‐Evolution of Linked Lexical Resources 13

Configuration of Software Product Lines 13

Evolving Knowledge Bases automatically through Natural Language Understanding 13

Hybrid Approaches to Natural Language Understanding: Integrating (DEEP) Machine Learning with Knowledge 14

Knowledge management in genomics 14

Natural Language Understanding for Automated Understanding of Software Requirements 15

Ontology‐based Information Ecosystems 15

Patient journey/clinical events analysis 16

Processes and workflows in clinical genomics 16

Semantic Interoperability for Big Data 16

STRATEGIC INFORMATION MANAGEMENT 17 Anti‐Mobile Malware, Mobile Security Including Money Honeypot, VoIP Security and Interception,

Critical Information Infrastructure Protection, Anti‐Phishing/Spam, Cryptographic Protocols and

Information Security Risk Management Framework and Standards 17

Cloud privacy enhancing and/or cryptography 18

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Cloud security 18

Collaborative Web search (social search) 18

Connecting to knowledge: Accessing information via the Internet by Indigenous communities 19

Darknet monitoring and/or analytics 19

Forensic Visualisation, Cloud Forensics, Big Data Forensics, Mobile and Anti‐Mobile Forensics,

Hard Disk Forensics, Multimedia Forensics, and Digital Forensic and Incident Response Standards 19

Immigrant youth and children 20

Information Management and Governance 20

Internet of Things Security and Privacy 21

Mobile app vulnerability detection and exploitation 21

Online multitasking (Mobile multitasking) 21

WEARABLE COMPUTER 22 A New Projector Based Augmented Reality Precise CAD‐Like Manipulations 22

Augmented Reality Intelligent Tutoring Systems 22

Augmented Reality Teleconferencing 23

Deep neural networks for human emotion recognition 24

Deformable User Interfaces 24

Disaggregation of Wearable Computation Devices 24

Empathic Conferencing 25

Face to Face Collaboration Using Hololens 25

Gaze based remote conferencing 25

Spatial Augmented Reality Design Tools 26

Storytelling of Big Data 26

User interaction for interactive constraints and spatial augmented reality 27

Virtual Reality Brain Training Tools 27

Visualising and Interacting with Large Graphs of Big Data 27

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ACRC: DATA ANALYTICS

Analytical methods for detection of social media manipulation Associate Professor Helen Ashman

Computer Science, WebTech and Security Suitable as PhD and Masters project

Social media provide tools for people to communicate with each other, on topics of interest such as travel, shopping, and current affairs. However the anonymity of the Internet means that social media have been infiltrated by people whose aim is to manipulate the opinions of social media users, perhaps for commercial or political gain. In this project, we will develop analytical methods and tools to detect this manipulation. The project aims to identify 'astroturfers' who covertly post under multiple identities and 'shill' posters who post without disclosing their financial or political interests. The tools will include forensic linguistics methods and metadata analysis, and will be applied to different social media types.

Automatic labelling of tweets in civil unrest prediction Professor Jiuyong Li, Dr Wei Kang

Computer Science, Data Mining Suitable as PhD and Masters project

Abstract: Twitter data is considered as an important open source when predicting civil unrest events. A number of

models have been built with features/patterns extracted from tweets, such as the volume‐based model and planned

protest model in (Ramakrishnan et al. 2014), and the forward‐looking approach to crowd behaviour prediction in

(Kallus 2014). However, labelling of tweets still remains a challenging task due to the nature of tweets. In (Zhao et al.

2014), the authors manually labelled 5386 tweets as civil unrest related, and 6147 as unrelated, which required a large

amount of labor force. The objective of this project is to design and implement either unsupervised or semi‐

supervised approaches(Hua et al. 2013), so as to label tweets automatically.

References: 1. Ramakrishnan, N., Butler, P., Muthiah, S., Self, N., Khandpur, R., Saraf, P., Wang, W., Cadena, J., Vullikanti, A.,

Korkmaz, G., others, 2014. “Beating the news” with EMBERS: forecasting civil unrest using open source indicators,

in: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

ACM, pp. 1799–1808.

2. Kallus, N., 2014, April. Predicting crowd behavior with big public data. InProceedings of the companion

publication of the 23rd international conference on World wide web companion (pp. 625‐630). International

World Wide Web Conferences Steering Committee.

3. Zhao, L., Chen, F., Dai, J., Hua, T., Lu, C.T. and Ramakrishnan, N., 2014. Unsupervised spatial event detection in

targeted domains with applications to civil unrest modeling. PloS one, 9(10), p.e110206.

4. Hua, T., Chen, F., Zhao, L., Lu, C.‐T. & Ramakrishnan, N. STED: semi‐supervised targeted‐interest event

detection. KDD’13, 1466‐1469.

Computer vision applications with unmanned vehicles Dr Ivan Lee

Computer Engineering, Multimedia Systems Suitable as PhD and Masters project

Abstract: This project investigates computer vision application on unmanned vehicles, such as:

1. Robot assisted smart homecare with ambient sensors: Internet of Things in smart home for detecting potential

indoor accidents, 3D model reconstruction of the surrounding for identifying new objects in 3D space using a

robot, human detection and pose analysis to facilitate robot‐based in‐situ assistance.

2. Object detection, recognition, and tracking on a UAV: this project applies multi‐camera system on a quadcopter,

and algorithms for 3D model reconstruction and new object detection and tracking will be investigated in this

project.

References:

1. Kalana Withanage, Ivan Lee and Russell Brinkworth, “Mobile robotic active view planning for physiotherapy and

physical exercise guidance,” IEEE International Conference on Robotics, Automation and Mechatronics (RAM),

Angkor Wat, Cambodia, 2015.

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2. Victor Stamatescu, Sebastien Wong, David Kearney, Ivan Lee, and Anthony Milton, “Mutual information for

enhanced feature selection in visual tracking”, SPIE Defense + Security: Automatic Target Recognition XXV, 2015.

Developing novel data mining techniques for mining educational data Professor Jiuyong Li, Dr Lin Liu


Abstract: This project aims to develop data mining techniques for effectively identifying the factors that influence

student academic performance and building better models to predict student learning outcomes. The increasing

adoption of learning management systems, such as Moodle has enabled education institutions to collect a large of

amount of data related to student online activities. Findings from such data can assist the institutions to provide

timely and effective student support and to make interventions. Educational data mining [1] has been attracting more

and more research interests in recent years. However, due to the large volume and high complexity of the data logged

by the learning management systems, traditional data mining methods are facing new challenges to deal with the big

educational data to find out true influential factors on student performance and to build accurate and interpretable

models to predict student outcomes. This project will develop new methods, such causal discovery approaches [2] to

tackle the educational data mining challenges.

References:

1. Cristobal Romero, Sebastian Ventura, and Enrique Garcıa. Data mining in course management systems: Moodle

case study and tutorial. Computers & Education, 51 (1). pp. 368‐384, 2008

2. Jiuyong Li, Lin Liu, and Thuc Le. Practical Approaches to Causal Relationship Exploration. Springer, 2015.

Discovery and use of Twitter network structural features for civil unrest prediction Professor Jiuyong Li


Abstract: Social unrest is predicable using Twitter data (Ramakrishnan et al 2014) and the structures of the Twitter

networks are strong indicators. Baltimore riots and Arab Spring share many similarities in patterns of spread of

messages in Twitter (Bohannon 2015). A recent study shows that there are clear network structure and community

changes in Twitter after the 2011 Japanese earthquake and Tsunami (Lu and Brelsford 2014). Another recent study in

PewResearchCenter characterises six types of conversational structures in Twitters: polarized, tight crowd, Brand

clusters, Community clusters, broadcast network, and support network (Smith et al 2014). This project will study the

methods for extracting structural features in social networks for improving the prediction accuracy of civil unrest.

Some related work for characterisation of Twitter networks can be found in (Myers 2014, Myers and Shama, 2014).

References:

1. Ramakrishnan, N et al (2014). 'Beating the news' with EMBERS: forecasting civil unrest using open source

indicators. KDD 2014: 1799‐1808.

2. Bohannon, J (2015). Can unrest be predicted, Science/AAAS, News May 9.

3. Lu, X and Brelsford, C (2014). Network structure and community evolution on Twitter: human behavior change in

response to the 2011 Japanese earthquake and tsunami, Nature Oct, 2014.

4. Myers, S, Sharma, A, Gupta, P, and Lin, J (2014). The structure of the Twitter follow graph, Proceedings of

International World Wide Web Conference Committee, (IW3C2 14).

5. Myers, S, and Leskovec, J, (2014). The bursty dynamics of the Twitter information network, Proceedings of

International World Wide Web Conference Committee, (IW3C2 14).

Effective time series feature selection for civil unrest prediction using social media data Professor Jiuyong Li


Abstract: Social unrest events can be modelled by time series and are influenced by other event series (local,

neighbour cities and the major cities), posts in social media, news, and economic circumstance, etc. The extracted

information from the media forms features (Ramakrishnan et al 2014). Each feature is represented as a time series,

and the data is a large set of time series. The aim of the project is to select a subset of time series that are informative

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for the prediction the future civil unrest events. Some feature selection work of time series can be found in (Kim 2012;

Sun et al 2012).

References:

1. Ramakrishnan, N et al (2014). 'Beating the news' with EMBERS: forecasting civil unrest using open source

indicators. KDD 2014: 1799‐1808.

2. Kim, M (2012). Time‐series dimensionality reduction via Granger causality. IEEE Signal Processing Letters,19(10),

611‐614

3. Sun, Y, Li, J, Liu, J, Chow, C, Sun, B, Wang, R (2014). Using causal discovery for feature selection in multivariate

numerical time series, Machine Learning, advance access.

Efficient Causal Inference in Big Data Dr Kui Yu, Professor Jiuyong Li

Computer Science Suitable as PhD and Masters project

Abstract: Causal inference is a fundamental problem in science. The access to big data has opened up new

opportunities for inferring causal relationships from purely observational data when experimental tests and

interventions are difficult or unethical. Most of existing causal discovery algorithms are designed for a small and single

data set. Thus, big data brings great challenges on causal inference because of its volume, the diversity of data types

and the speed at which it must be managed. The project will develop efficient and effective causal inference

algorithms to deal with big data challenges for advancing big data mining techniques, and extend those new

algorithms to discover genetic causes of cancer for improving biomedical discovery. The novel causal inference

methods developed in the project will advance data mining techniques and help human being better understanding

cause‐and‐effect relationships hidden in big data. By extending the research outcomes to discover genetic causes of

cancer to help biomedical researchers understand critical causes and trends buried in big biomedical data, this will

bring great potential to improve biomedical discovery for better healthcare in Australia.

References:

1. Y. Liang and A. R. Mikler. (2014) Big data problems on discovering and analyzing causal relationships

in pidemiological data. IEEE BigData 2014, 11‐18.

2. K. Yu, W. Ding, H. Wang, and X. Wu. (2013) Bridging Causal Relevance and Pattern Discriminability: Mining

Emerging Patterns from High‐Dimensional Data. IEEE Transactions on Knowledge and Data Engineering, 25(12):

2721‐2739.

3. G. F. Cooper, I. Bahar, M. J. Becich, P. V. Benos and et.al. (2015) The center for causal discovery of biomedical

knowledge from Big Data, Journal of the American Medical Informatics Association, 1‐6.

Identifying cancer subtypes from multi‐levelled biological data with computational methods Dr Thuc Le, Professor Jiuyong Li

Computer Science, Bioinformatics Suitable as PhD and Masters project

Abstract: Cancer is a leading cause of death, accounting for more than 8.2 million of deaths worldwide, or 22,000

people every day. In the past decade, personalised medicine, using genetic information to develop cancer‐specific

medication, has become a strong focus for health researchers. An important step in this personalised medicine

framework is to identify cancer subtypes, as different cancer subtypes may have different treatment therapies. Since

cancer is an extremely complex and heterogeneous disease, the personalised medicine framework relies heavily on

achievements of advanced research in system biology (Wang, 2010). System biology approaches use knowledge in

Mathematics, Statistics and Computer Science to solve the biological problems. This project will study the

computational methods for identifying cancer subtypes using multi types of biological data. Examples of related works

are in (Wang et al. 2014, Liu et al. 2014). Background in Biology is an advantage but not a compulsory requirement.

References:

1. Wang E. A roadmap of cancer systems biology. Nature Publishing Group. 2010; 713: 1‐28.

2. Wang, Bo, et al. Similarity network fusion for aggregating data types on a genomic scale. Nature methods. 2014:

333‐337.

3. Liu, Yiyi, et al. "A network‐assisted co‐clustering algorithm to discover cancer subtypes based on gene

expression." BMC bioinformatics 15.1 (2014): 37.

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Implied Comparative Advantage of Australian Economic Complexity Dr Ivan Lee

Computer Science, Computational Economics Suitable as PhD and Masters project

Abstract: This project investigates economics complexity at sub‐country level in Australia (with potential extensions

to global economies) based on export data within the country or to overseas, and developing new models for time

series predictions of implied comparative advantage. The outcome of this project will assist policy makers identifying

revealed competitive advantages and opportunity gain for different industrial sections, and predicting the industrial

export growth over time. Students in this project will investigate mathematical modelling and information

visualisation of economical data. This project is supported by the South Australia Department of State Development.

References:

1. The Observatory of Economic Complexity: OEC, https://atlas.media.mit.edu/en/ (last accessed 11 June 2015)

2. Alexander Simoes, Cesar A. Hidalgo, Juan Jimenez, Michele Coscia, Muhammed A. Yıldırım, Ricardo Hausmann,

Sarah Chung, and Sebastián Bustos, “The Atlas of Economic Complexity Mapping Paths to Prosperity,”

https://atlas.media.mit.edu/atlas/ (last accessed 11 June 2015)

3. Ricardo Hausmann, Cesar A. Hidalgo, Daniel P. Stock, and Muhammed A. Yildirim, “Implied Comparative

Advantage,” SSRN Electronic Journal 01/2014; DOI: 10.2139/ssrn.2410427

Integrated Policing: Generating queries for identity resolution Dr Jixue Liu


Abstract: Identity resolution aims to find whether two records are referring to the same entity. A lot of work has been

done on this topic assuming that the databases containing the two records to be matched are fully accessible and

enabling brute force comparison of all records. However, this full access assumption becomes impractical in some

applications because a database may be too sensitive to be accessed in any way that a user likes to take. When such a

database is accessed, the user may get only one record per query or get even only true/false answers. In this case,

what queries should be used to access the database so that an identity resolution process can use the query output to

infer identities becomes a serious problem. This project aims to develop methods and algorithms to generate best

queries to access the restricted database for identity resolution purpose. The query generation would be on the basis

of an existing index over similar entities, e.g., the similar names.

References:

1. Heng Ji. 2015. From Mono‐lingual to Cross‐lingual: state‐of‐the‐art EDL. Invited Talk at JHU HLT‐COE

2. Heng Ji, Joel Nothman and Ben Hachey. 2014. Overview of TAC‐KBP2014 Entity Discovery and Linking Tasks. Proc.

Text Analysis Conference (TAC2014)

3. Dan Roth, Heng Ji, Ming‐Wei Chang and Taylor Cassidy. 2014. Wikification and Beyond: The Challenges of Entity

and Concept Grounding. Tutorial at the 52nd Annual Meeting of the Association for Computational Linguistics

(ACL2014)

4. Roy et al (2005). "Towards Automatic Association of Relevant Unstructured Content with Structured Query

Results." CIKM.

5. Gardezi et al (2012). "Query Rewriting using Datalog for Duplicate Resolution." LNCS 7494: 86‐98.

6. Talburt, J., Entity and Identity Resolution. MIT IQ Industry Symposium http://mitiq.mit.edu/IQIS/2010/Addenda/T2A%20-%20JohnTalburt.pdf, 2010.

7. Christen, P., A Survey of Indexing Techniques for Scalable Record Linkage and Deduplication. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2012. 24(9): p. 1537-1555.

Integrated Policing: Model relationships from text data for identity resolution Dr Jixue Liu


Abstract: Identity resolution aims to find whether two records are referring to the same entity. When identity

resolution is required from entities in text documents, the task becomes complicated. One reason is that a documents

often refers to many entities and properties of entities (like names of people) are not labelled by attributes. At the

same time, the relationships among the entities are described in the documents. For example, a document may

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contain the sentence ‘Alice saw that Bob drove down Stephen St at 11:00pm’. Here three names are mentioned

alongside of the time entity and the relationships between these names are described. Currently, the methods dealing

with this type of text use Natural Language Parsing tools to extract entities and then put the entities into relational

tables and the match with other relational records of a database. The shortage of this practice is that the

relationships are not used. This project aims to model the entities and the relationships extracted in text data, and

develop ways to compare the modelled entities and relationships with records in relational databases. The model is

expected to be a graph model. The comparison will need an effective method and an efficient algorithm.

References:

1. Xiang Ren, Ahmed El‐Kishky, Heng Ji and Jiawei Han. Automatic Entity Recognition and Typing in Massive Text

Data. Tutorial at ACM International Conference on Management of Data (SIGMOD2016)

2. Heng Ji, Joel Nothman and Ben Hachey. 2015. Overview of TAC‐KBP2015 Tri‐lingual Entity Discovery and Linking.

Proc. Text Analysis Conference (TAC2015)

3. Gardezi et al (2012). "Query Rewriting using Datalog for Duplicate Resolution." LNCS 7494: 86‐98.

4. Bruce, J., et al., Pathways To Identity: Using Visualization To Aid Law Enforcement In Identification Tasks. Security

Informatics, 2014. 3(12).

5. Xu, J., et al., Complex Problem Solving: Identity Matching Based on Social Contextual Information. Journal of the

Association for Information Systems, 2007. 8(10): p. 525‐545.

6. Christen, P., A Survey of Indexing Techniques for Scalable Record Linkage and Deduplication. IEEE Transactions on

Knowledge and Data Engineering (TKDE), 2012. 24(9): p. 1537‐1555.

Integrated Prediction with Multiple Data Sources and Credibility Assessment Dr Lin Liu


Abstract: The research topic will focus on the problems of fusing evidence from multiple data sources and models,

and the credibility of data sources and users. The topic will be based on the work in Rekatsinas et al. (2015)’s paper

on the challenge of discovering valuable sources, Hoegh et al. (2015)’s paper, in which a Bayesian model fusion

framework of protest events is proposed, and the work in (Mukherjee, Weikum and Danescu‐Niculescu‐Mizil 2014).

Reference:

1. Rekatsinas, T et al 2015, Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for

Integration. 7th Biennial Conference on Innovative Data Systems Research (CIDR‘15) January 4‐7, 2015, Asilomar,

California, USA

2. Hoegh, A et al 2015, Bayesian Model Fusion for Forecasting Civil Unrest, Technometrics

3. Mukherjee, S, Weikum,G, and Danescu‐NiculescuMizil C 2014, People on drugs: credibility of user statements in

health communities. In KDD’14, pages 65‐74

Integration and visualisation of multiple civil unrest prediction models Professor Jiuyong Li, Dr Wei Kang


Abstract: A complete system often consists of multiple models/components, which work and interact with each other

to provide expected results. The objective of this project is to integrate multiple existing civil unrest prediction models

(Ramakrishnan et al 2014) into one system, and make sure all the components work properly together to provide a

comprehensive and user‐friendly result through user interface and visualisation.

References:

1. Ramakrishnan, N., Butler, P., Muthiah, S., Self, N., Khandpur, R., Saraf, P., Wang, W., Cadena, J., Vullikanti, A.,

Korkmaz, G., others, 2014. “Beating the news” with EMBERS: forecasting civil unrest using open source indicators,

in: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

ACM, pp. 1799–1808.

Interpretable classification and prediction of civil unrest events Professor Jiuyong Li, Dr Jie Chen

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Abstract: The lack of interpretability makes many sophisticated classification/regression models infeasible in real

applications, which place great emphasis on both the accuracy and comprehensibility of the potential models, such as

medical scoring systems (Letham et al. 2015). The goal of the project is to build interpretable prediction models with

patterns, which are easy for human reasoning and understanding. There is recent progress on Bayesian analysis

(Letham et al. 2015) and discriminative pattern‐based classification (Shang et al. 2016; Lou et al. 2013). The patterns

or high‐order features that are highly correlated to the target civil unrest events will be used as the input of the

building of the models. The student may compare the performance of the two major interpretable models in the

context of predicting civil unrest events, and explore a new way of interpretable prediction model, e.g. through the

combination the two approaches.

References: 1. Letham, B. et al (2015). "Interpretable classifiers using rules and Bayesian analysis: Building a better stroke

prediction model." The Annals of Applied Statistics 9.3 (2015): 1350‐1371.

2. Shang, J., et al. (2016). An Effective but Concise Discriminative Patterns‐Based Classification Framework. In

Proceedings of 2016 SIAM International Conference on Data Mining (SDM 2016)

3. Lou, Y. et al (2013). Accurate intelligible models with pairwise interactions. In SIGKDD, 2013, 623–631

Investigating genetic causes of cancer through complex gene regulatory networks Dr Thuc Le, Professor Jiuyong Li

Computer Science, Bioinformatics Suitable as PhD and Masters project

Abstract: This project will study the computational methods for identifying the genetic causes of cancer through gene

regulatory networks containing multiple gene regulators. Gene regulatory networks play an important role in every

process of life, and understanding the dynamics of these networks helps reveal the mechanisms of diseases6. There

have been tremendous works on inferring gene regulatory networks. However, most of the works consider the

networks with only one type of gene regulator, such as transcription factors (Imam et al., 2015) or microRNAs (Le,

2013), thus only help reveal part of the whole regulatory network picture. This project aims to develop methods to

construct gene regulatory networks that contain multiple types of gene regulators and methods to isolate sub‐

networks that are altered between normal and cancer patients. Examples of related works are in (Le et al. 2013, Ping

et al. 2015). Background in Biology is an advantage but not a compulsory requirement.

References:

1. Imam, Saheed, Daniel R. Noguera, and Timothy J. Donohue. "An Integrated Approach to Reconstructing Genome‐

Scale Transcriptional Regulatory Networks." PLoS computational biology 11.2 (2015): e1004103‐e1004103.

2. Le, Thuc D., et al. "Inferring microRNA–mRNA causal regulatory relationships from expression

data." Bioinformatics 29.6 (2013): 765‐771.

3. Le, Thuc D., et al. "Inferring microRNA and transcription factor regulatory networks in heterogeneous data." BMC

bioinformatics 14.1 (2013): 92.

4. Ping, Yanyan, et al. Identifying core gene modules in glioblastoma based on multilayer factor‐mediated

dysfunctional regulatory networks through integrating multi‐dimensional genomic data. Nucleic acids

research 43.4 (2015): 1997‐2007.

Multimedia Systems (2D and 3D video coding and video streaming, robotics vision, cloud‐based

video services, panoramic video analysis, video surveillance and monitoring, multimedia data

mining, multimedia sensor networks, medical imaging) Dr Ivan Lee

Computer Engineering Suitable as PhD and Masters project

Abstract: Multimedia systems use a combination of content forms to facilitate media rich applications such as video

conferencing or robotics vision. The multimedia projects we offer include either software or hardware design,

developing applications for mobile devices (smart phone, tablets), desktop computers, robots, embedded systems, or

high‐performance computers (such as clusters or cloud computers.) The candidates will have opportunities to utilise

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different sensors, such as 2D and 3D video cameras, microphone arrays, marker/visual‐based tracking systems, or the

Australian Synchrotron, for different projects.

Potential projects include, but not limited to:

2D and 3D video coding

Compressive video coding

Free‐viewpoint video coding and streaming

Cloud‐based video streaming

Vision system for unmanned aerial vehicle (UAV), Unmanned ground vehicle (UGV), or autonomous underwater

vehicle (AUV)

Wireless multimedia sensor networks

Medical imaging

Biomechanics using computer vision

Precursor Pattern Analysis and Interpretable Classification Dr Lin Liu


Abstract: The aim is to develop new pattern discovery methods on large‐scale unstructured online data to derive

useful relationships among instances of variables, especially targeted at those messages prior to the civil unrest events

so that interpretable prediction models with causal relationships can be learned based on the methods developed in

(Letham et al. 2013; Li, Liu and Le 2015).

References:

1. Letham, B et al 2013, Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction

model. Technical Report no. 609, University of Washington, August 2013.

2. Li,J, Liu,L, and Le, T 2015, Practical approaches to causal relationship exploration, Springer, 2015

Prediction of civil unrest events with news and other data sources Professor Jiuyong Li, Dr Jie Chen


Abstract: Tweets has played important role in the prediction of civil unrest events, such as protests, and may provide

insights into the root causes of the events. However, online news feeds, blogs and other sources e.g. economic time

series and GDELT data, are also useful in the forecasting of these events (Ramakrishnan et al. 2014). The informative

patterns discovered from the news sources, e.g. interactive patterns (Ning et al.2015) and precursor patterns (Ning eg

al. 2016), can be utilised in enhancement of existing predictive models that majorly rely on twitter data.

References: 1. Ramakrishnan N., Butler P., Muthiah S, et al. “Beating the news” with EMBERS: forecasting civil unrest using open

source indicators. KDD ′14, New York, ACM, August24–27, 2014 pp. 1799–1808

2. Yue Ning, Sathappan Muthiah, Ravi Tandon, Naren Ramakrishnan: Uncovering News‐Twitter Reciprocity via

Interaction Patterns. ASONAM 2015: 1‐8

3. Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan: Modeling Precursors for Event Forecasting

via Nested Multi‐Instance Learning. CoRR abs/1602.08033 (2016)

Signal processing and analysis for medical imaging Dr Ivan Lee

Computer Engineering, Multimedia Systems Suitable as PhD and Masters project

Abstract: This project will investigate sparse signal reconstruction for computed tomography and particle image

velocimetry analysis, on synchrotron phase contract x‐ray images, to overcome challenges on detecting and tracking

overlapping particles for the assessment of cystic fibrosis airway therapies. This project can also apply similar

algorithm for different medical imaging techniques, such as MRI, ultrasound, and confocal microscopic images.

References:

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1. Zhenglin Wang and Ivan Lee, "Backprojection Regularization with Weighted Ramp Filter for Tomographic

Reconstruction", International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan,

Italy, 2015.

2. Hyewon Jung, Ivan Lee, Sang‐Heon Lee, “Circular Particle Detection using Sectored Ring Mask for Synchrotron

PCXI images,” International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan,

Italy, 2015.

ACRC: DEEP NEURAL NETWORKS AND PARALLEL COMPUTING PROJECTS

360 Degree Cameras: Image Analysis Algorithms Associate Professor David Kearney, Dr Victor Stamatescu, Associate Professor Mark McDonnell, Dr Sebastien Wong

Computer Engineering, Machine Learning Suitable as PhD project

Abstract: This project, in partnership with DSTG, is to conduct research into computer vision based on spherical

cameras mounted on a moving platform, such as an aircraft or ground vehicle. One example of a platform coupled

with a 360 degree camera is the Google street‐view car. The student will develop a system to automatically detect,

track and classify multiple objects in all directions. The tracking software developed by our lab automatically learns

the position, velocity and shape of every object in the scene. The research may be either to build a practical system or

to progress underpinning mathematical theory. For a demo, see https://youtu.be/Izyp3U6tmjA.

Contact: [email protected]

References:

1. Sebastien Wong, Adam Gatt, David Kearney, Anthony Milton, Victor Stamatescu. "A Competitive attentional

approach to mitigating model drift in adaptive visual tracking", In Proc. 29th International Conference on Image and

Vision Computing New Zealand (IVCNZ '14).

2. Victor Stamatescu, Sebastien Wong, David Kearney, Ivan Lee, and Anthony Milton. “Mutual information for

enhanced feature selection in visual tracking”, SPIE Defense + Security: Automatic Target Recognition XXV, 2015.

Deep Neural Networks for Anomaly Detection and Decision Making in Personal Budgeting Associate Professor Mark McDonnell, Professor Joffre Swait, Dr Belinda Chiera, Mr Dave Bohn

Data Science, Machine Learning Suitable as PhD project

Abstract: This project, in partnership with Adelaide‐founded company, MyBudget, will investigate ways to use deep

recurrent neural networks to predict future individual financial situations, and deep reinforcement learning methods

to help individuals in their financial decision making. Both of these ”deep learning” techniques have had enormous

recent impact in artificial intelligence: recurrent networks have produced new state of the art speech recognition

systems, while in March 2016 deep reinforcement learning methods were integral to Google’s AlphaGo software

between a world champion Go player for the first time. However, the methods are generically useful for time‐series

based prediction and strategic decision making generally, and in this project a student will apply them in problems

relevant to personal financial management. Contact: [email protected]

References:

1. D. Silver et al. “Mastering the game of Go with deep neural networks and tree search.” Nature, Vol. 529, 484–489,

2015.

Deep Neural Networks for Image Understanding Associate Professor Mark McDonnell, Associate Professor David Kearney, Dr Victor Stamatescu, Dr Sebastien Wong

Computer Science, Machine Learning, Computer Vision Suitable as PhD project

Abstract: The goal of this project, in partnership with DSTG, is to investigate and design algorithms for improving

machine learning for computer vision tasks, such as object recognition in photographs, and tracking of objects in

video, using deep neural networks. Newly developed “deep learning” methods have reignited the field of neural

networks in the last few years. Deep neural networks have, for the first time, been demonstrated to produce better

than human performance in recognition of objects in image databases, such as Imagenet. However, the training

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methods used consume vast resources: time, compute power and human‐labelling of training data. In this PhD

project, we will create novel deep learning algorithms that challenge the existing state‐of‐the‐art. For example, the

student might devise methods for training neural networks based on limited labeled data. Another approach will be to

introduce techniques inspired by recent scientific discoveries on learning in brains from the labs of our collaborators.

Students will benefit from access to GPUs and high performance computing in our labs.

Contact: [email protected]

References:

1. LeCun, Y., Bengio, Y. and Hinton, G. E. (2015). “Deep Learning.” Nature, Vol. 521, pp 436‐444.

ACRC: KNOWLEDGE AND SOFTWARE ENGINEERING

Agile Model‐Driven Visualisation of Big Data Dr Georg Grossmann

Visual analytics, software engineering, model driven engineering, agile visualisation Suitable as PhD project

Abstract: Data visualisation and visual analytics are more frequently used in recent years to describe and explore data

in an easy to understand way. One of biggest challenges is to provide flexible visualisation techniques and guidelines

on when to apply a particular visualisation technique.

This project will investigate a new paradigm, agile visualisation (http://agilevisualization.com/) in combination with

Model Driven Engineering (MDE) to provide increased flexibility to develop personalised visualisation and develop

design guidelines to help the end user to identify the optimal visualisation by supporting the whole life cycle of visual

analytics.

Data will be provided by local industry partner Active Operations Management (AOM) which makes this project a very

interesting applied research project with high relevance to the local industry.

Business Process Management for the Internet of Things Professor Markus Stumptner

Software Engineering, Artificial Intelligence Suitable as PhD project

Abstract: Within the last few years, business process management has evolved from the abstract handling of

software applications involving users in front of screens that are separated from real world events to the provision of

dynamic, interoperating services that are directly linked to each other in vast, planet‐spanning process networks. In

addition, emerging network‐enabled smart device standards have led to the so‐called “Internet of Things” (IoT) which

allows software systems to remotely access and control devices. This has become a priority research topic in the EU,

US, and Asia and is heralded as “the next technology revolution” in a February 2013 special issue of IEEE Computer,

leading to the incorporation of IoT technology into Web applications has led to the Web of Things (WoT). This has

triggered the call for business process modelling techniques to catch up. Assumptions that have shaped much for

business process management for decades, no longer hold in the new, distributed, real world connected environment:

the assumption of a perfect world (i.e., events happen as they are planned), e.g., an airplane arrives exactly at the

time for which its scheduled), and the assumption of a perfect system (events become immediately known when they

occur). A fundamental property of the new generation of business processes is therefore that they need to be time

aware. An event has to be analysed not just in terms of what immediate action it requires in response, but how the

event and that action are going to affect and possibly interfere with steps and expected events already planned for in

the future. Potential key topics to be explored include:

A declarative method to specify bitemporal business rules instead of traditional automata net representations

A business rule language for formal characterisation of the different time‐aware event processing situations

Descriptions of how to react to events or constraint violations (e.g., pro‐, or retro‐actively), and for linking these

to business processes. occurrence time)

Case studies to demonstrate these techniques in realistic, large‐scale environments

References:

1. Opher Etzion. Event processing ‐ past, present and future. PVLDB, 3(2):1651–1652, 2010.

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2. Tim Furche, Giovanni Grasso, Michael Huemer, Christian Schallhart, and Michael Schrefl. Bitemporal complex

event processing of web event advertisements. In Proc. WISE (2), pages 333–346, 2013.

3. Alejandro P. Buchmann, Stefan Appel, Tobias Freudenreich, Sebastian Frischbier, and Pablo Ezequiel Guerrero.

From Calls to Events: Architecting Future BPM Systems. In Proc. Intl. Conf. on Business Process Management

(BPM), LNCS 7481, pages 17–32. Springer‐Verlag, 2012.

4. Internet of Things: Strategic Research Roadmap. Technical report, Cluster of European Research Projects on the

Internet of Things (CERP‐IoT), 2009.

Co‐Evolution of Linked Lexical Resources Professor Markus Stumptner, Dr. Wolfgang Mayer, Dr. Matt Selway Suitable as PhD Project

Abstract: In this era of Big Data, Natural Language Understanding (NLU) applications must link to, query, and

integrate knowledge from a variety of internal and external sources (e.g., knowledge graphs, ontologies, and domain

models) to arrive at the understanding of a piece of text. In our work with the Defence Science and Technology Group,

for example, reading text that describes the behaviour of entities in combat simulations requires the integration of

models of actions that can be performed (e.g., move and attack), while the entity types themselves (e.g., soldiers and

tanks) are defined in a separate ontology and individual entities may be stored in yet another knowledgebase.

The NLU application must be able to connect elements of the text to the entity types, entities, and behaviours

maintained in the different knowledge‐sources; this is done through a common lexical layer linking words

(morphology), syntax, and semantics. This layer provides a common ground for integrating knowledge from different

sources through language use and is a key component of advanced Natural Language Understanding techniques.

However, the lexical layer requires extensive management to ensure consistency between the three aspects. For

example, the lexicon itself may be updated to incorporate new terminology, synonyms, etc., or the knowledgebase

constituting the semantics of the lexical entries may be revised such that the lexical entries need to reflect the change.

Modifying the syntactic rules or semantic elements of a knowledgebase may lead to the lexicon being out‐of‐date,

resulting in incorrect analyses of text.

This project will investigate means of (semi‐)automatically updating a shared lexicon as the result of changes to

different knowledge‐sources in an NLU application. A common framework for ontology and model adaptation should

be developed along with techniques of analysing these adaptation models to propagate changes in knowledge‐

sources to the lexical entries referencing them. The final result will include a prototype implementation integrated

with the NLU framework being developed within the Knowledge and Software Engineering Laboratory.

Configuration of Software Product Lines Professor Markus Stumptner, Dr Wolfgang Mayer


Abstract: In many markets today, customers no longer consider customization as special: they expect it. This

expectation applies both to simple goods like t‐shirts and to more sophisticated products composed of heterogeneous

hardware, software and services. Yet, the complexity in engineering and manufacturing of deeply configurable

products varies significantly. Numerous sectors, such as automotive, semiconductors, and cloud services, lack tools

and methods to keep their hardware and software configurations consistent during configuration and evolution. Ad

hoc solutions frequently patch isolated problems, but fail to effectively improve overall key performance indicators

such as availability, reliability and time‐to‐market. Integrated solutions to align software, hardware and service

configuration are missing. Research in configuration is currently carried out in two main communities: (hardware)

product configuration and software configuration. Despite the significant overlap in research interests, they have

evolved mainly in isolation. Yet, similar challenges and solutions have emerged in both communities.

The goal of this project is to examine the modelling methods used for product configuration (a well‐established

industrial application area) and examine what benefits they can provide for Software Product Line Engineering.

Evolving Knowledge Bases automatically through Natural Language Understanding Professor Markus Stumptner, Dr Wolfgang Mayer, Dr Matt Selway


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Abstract: Over the last ten years, a number of projects such as DIRT, NELL (the NeverEnding Language Learner), BKB

and others [1,2,3,4] have been started with the goal of learning the content of large knowledge bases from text

documents. However, most of these systems study only the learning process in general. To make such systems

relevant in practice, they must produce useful knowledge for particular applications and must be able to consider the

relevance of prior knowledge when reading new text. This project will study the question of how additional

knowledge can be learned from text and merged with an existing knowledge base, resulting in a process that can gain

and retain competence in a real world context throughout years of use.

This work is aligned with the ‘Doctrine to Code’ project funded by the Australian Defence Science and Technology

Organisation (DSTO).

References:

1. L. Schubert, Can we derive general world knowledge from text? in Proc. HLT, 2002, pp. 94–97.

2. P. Clark and P. Harrison, Large‐scale extraction and use of knowledge from text, in Proc. 5th KCAP, 2009, pp. 153–

160.

3. D. Lin and P. Pantel, DIRT: Discovery of inference rules from text, in Proceedings of the ACM SIGKDD Conference

on Knowledge Discovery and Data Mining, 2001, pp. 323–328.

4. Carlson, J. Betteridge, B. Kisiel, B. Settles, E. R. Hruschka, Jr., and T. M. Mitchell, Toward an architecture for never‐

ending language learning, in Proc. AAAI, 2010, pp. 1306–1313

5. Matt Selway, Georg Grossmann, Wolfgang Mayer, Markus Stumptner: Formalising Natural Language

Specifications Using a Cognitive Linguistics/Configuration Based Approach. Proceedings Enterprise Computing

Conference 2013.

Hybrid Approaches to Natural Language Understanding: Integrating (Deep) Machine Learning

with Knowledge Professor Markus Stumptner, Dr Wolfgang Mayer, Dr Matt Selway Suitable as PhD Project

Natural Language Understanding (NLU), the ability for computers to comprehend language to the same degree as a

person so that they can perform actions and respond to complex queries, is an ongoing challenge. For the last two

decades, the focus of Natural Language Processing has been on using Machine Learning techniques to train models for

specific tasks, for example, Part‐of‐Speech tagging, Syntactic Parsing, Sentiment Analysis, and Named‐Entity

Recognition. Moreover, the recent trend of Deep Learning (i.e., the training of layered neural networks) is being

applied to NLP tasks to improve performance over traditional Machine Learning techniques.

While such approaches have been quite successful in obtaining usable results in many applications, they have their

limitations and, hence, cannot realise Natural Language Understanding on their own. Chief among the limitations of

Machine Learning methods is their inability to make use of existing knowledge resources such as lexical resources

(WordNet, VerbNet), ontologies, knowledge‐graphs, domain models, etc. These knowledge resources provide the link

between human and computer understanding; therefore, being able to incorporate them is a necessity to achieve

NLU.

In contrast, non‐Machine Learning approaches to NLP (i.e., symbolic, rule, or knowledge‐based approaches) can

readily incorporate various knowledge resources. This allows them to perform NLU within a restricted application

domain or context; however, they lack the ability to generalise across the large amount of data available in today's

world. Instead new rules must be added manually, new knowledge‐sources must be manually integrated, and large

data sources may lead to inefficiencies in processing text, if they can be incorporated at all. Therefore, to realise

general NLU capability, the two approaches must be combined.

This project aims to develop a hybrid approach to Natural Language Understanding that integrates Machine Learning

and Deep Learning with Knowledge‐based approaches. It will investigate which aspects of Natural Language

Understanding can make best use of Machine Learning and Knowledge‐based components and integrate them in a

prototype NLU system being developed in the Knowledge and Software Engineering Laboratory.

Knowledge management in genomics Dr Jan Stanek

Computer Science, Health/clinical informatics Suitable as PhD project

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Abstract: Genomics (and indeed other “omix”es) are generating big amounts of data. These can be classified into

essentially 3 categories:

1. Research data

2. Clinical data

3. Reference data

At this stage, lots of effort is to build large and high quality databases capturing reference data on gene variants, as

this is a condition sine qua non for clinical evaluation of medical genetic testing results.

There are several significant problems with such databases:

1. Assessment of pathogenicity and maintaining this assessment current (i.e. there should be a regular review of

pathogenicity assessment at least for variants deemed pathogenic) – this is the problem with curation (as

described later), but serious preparation can be done automatically (e.g. by regularly scanning other databases,

literature and in future possibly Electronic Health Records) to detect any patterns indicating the specific variant

requires (human) review.

2. Assembling and management other knowledge (from external sources?) on each variant ‐ at least the pathogenic

ones (integration of pieces of knowledge opens questions on how to capture/represent/resolve possible

contradictions in evidence/opinion)

3. Phenotype link to the variant (I assume electronic health records should be a possible source for this information

– PCEHR nation‐wide – and EPAS in South Australia might be a good place to start experimenting).

4. Curation of the database – the load on curators is growing rapidly, so it cannot be a voluntary commitment any

more (as it used to be in the past). However, the practice is lagging behind and such position (paid enough to

attract senior experienced person) is not easy to establish. Hence the idea offers itself to look at “crowdsourcing”

– i.e. whether the curation task can be (with serious support of IT) distributed amongst members of the

community.

5. To support such work we have a good working relationship with SA Pathology (experts in genetics and genetic

testing) and Human Variome Project (world‐wide initiative collecting data on human variome).

Natural Language Understanding for Automated Understanding of Software Requirements Professor Markus Stumptner, Dr Wolfgang Mayer, Dr Matt Selway


Abstract: Automated construction of software is a long‐held dream of Computer Scientists and Software Engineers.

With the advent of ‘Model driven engineering’, it has moved closer to reality as systems need no longer be developed

in low level code but can be specified in terms of diagrams of behaviour specified in languages such as UML. This

project will build on earlier work to create a system that can understand natural language text describing a particular

application domain and converts it into diagrams that can be executed.

This work is aligned with the ‘Doctrine to Code’ project funded by the Australian Defence Science and Technology

Organisation (DSTO).

References:

1. Matt Selway, Georg Grossmann, Wolfgang Mayer, Markus Stumptner: Formalising Natural Language

Specifications Using a Cognitive Linguistics/Configuration Based Approach. Proceedings Enterprise Computing

Conference 2013.

Ontology‐based Information Ecosystems Professor Markus Stumptner, Dr Wolfgang Mayer, Dr. Georg Grossmann

Software Engineering, Data Management, Ontologies, Artificial Intelligence Suitable as PhD project

Abstract: Flexible data integration has been an important IT research goal for decades. About ten years ago, a

significant step was taken with the introduction of declarative methods (e.g., Clio). Since this work, mostly based on

classic dependency analysis, extensions have been developed that express more powerful semantic relationships.

However, much of this work has remained focused at the relational database (i.e., relatively low) level, and many of

the extensions revert to specific algorithms and function specifications. At the same time, models have evolved to

incorporate more powerful semantics (object or ontology‐based methods). Work in this area will focus on combining

separate but currently unrelated efforts for a coordinated approach to engineering interoperability.

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Use of major existing upper ontologies (e.g., DOLCE)

Incorporation of new modelling concepts such as role relationships

Incorporation of engineering ontologies (e.g., the NASA measurement ontology)

Testing using current activities related to multiple engineering standards ranging from air traffic management

over health to the oil and gas industry.

This work is aligned with the International Oil & Gas Interoperability Pilot (partners Assetricity, IBM, Microsoft, Bentley,

AVEVA, Intergraph, Rockwell Automation), and the Oil & Gas Interoperability Project funded by the SA State

Government.

References:

1. Mayer, W., Stumptner, M., Grossmann, G., Jordan, A. (2013). Semantic Interoperability in the Oil and Gas

Industry: A Challenging Testbed for Semantic Technologies, AAAI Fall Symposium 2013 on Semantics for Big Data.

2. Schneider, T., Hashemi, A., Bennett, M., Brady, M., Casanave, C., Graves, H., Gruninger, M., Guarino, N.,

Levenchuk, A., Lucier, E., Obrst, L., Ray, S., Sriram, R. D., Vizedom, A., West, M., Whetzel, T., Yim, P. (2012).

Ontology for Big Systems: The Ontology Summit 2012 Communique, Applied Ontology 7(3), pages 357‐371.

3. Teymourian, K., Coskun, G, and Paschke, A. (2010). Modular Upper‐Level Ontologies for Semantic Complex Event

Processing. In Proc. of the 2010 conference on Modular Ontologies: (WoMO 2010), IOS Press, pages 81‐93

Patient journey/clinical events analysis Dr Jan Stanek


Abstract: Analysis of event sequences along the path of diagnosing and treating a patient can establish an important

basis for performance (in terms of quality of care, safety of care and cost of care) management in health care. The

research required in this area spans from data mining (path‐mining, workflow mining), through to models of the

patient journey and assessing the clinical/fiscal outcomes across such models. Major challenges in this area are:

Clinical data extraction and preparation for analysis (issues such as confidentiality of the data; reconciliation of

data formats, data schemas and diverse ontologies ‐ I expect use of UMLS metathesaurus and other ontologies to

be utilized to reconcile data from different sources; data linkage)

Finding effective approaches to handle very rich and diverse information (data in health is seldom complete or

consistent) – methods developed for data analytics in business may not be valid in this situation and re‐validation

of such algorithms may be required

Researching (exploration, modelling) of processes involved in such analysis in order to support automation of the

event analytics in clinical practice

Partners from SA Health will be sought ‐ subject to specific project approval and ethics clearance.

Processes and workflows in clinical genomics Dr Jan Stanek


Abstract: Genetic testing is a highly dynamic area of research spanning several groups of specialists: clinicians, clinical

geneticists, medical scientists, laboratories, bioinformaticians (to name the main ones). Members of these groups use

different terminologies, may have different objectives and come from different professional cultures.

Clinicians come from medical background (with limited depth of molecular biology knowledge) and their main

objective is to use genetic testing for better diagnosis and treatment of a given cohort of (cancer) patients. Main

issues for this group are: when the genetic testing is indicated, and how to interpret the results. This is in stark

contrast with e.g. bioinformaticians, who come from mathematical and biology background (with very little clinical

basis and exposure). Their objective is to process massive data produced by genetic testing (such as exom sequencing)

to generate a validated result.

Incorporation of genetic testing into clinical practice represents a challenge:

How we can design a set of processes which would allow integration of activities of such a diverse group of

specialists?

How we have to reconcile the differences in terminology each group of specialists is using?

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What information is needed to support processes (and decision‐making) at a given group of specialists?

And how we have to design the process so that they are robust enough to cope with frequent changes and editing

(NB: all layers of genetic testing are rapidly evolving) without creation of internal inconsistencies and

contradictions?

The proposed research is to explore the application of process mining (to learn what processes are currently used) and

dynamic process modelling and integration (at semantic level – this includes integration of ontologies as well) to

design a federated, hierarchical model describing activities from test ordering through genetic counselling, laboratory

analysis, result generation, validation and interpretation, back to clinical interpretation and use. The research will

build on knowledge and tools developed in the Semantic Systems Group.

Partners:

Centre for cancer biology; SA Pathology – Flinders Medical Centre. Colleagues for the partner organisations will

participate in student supervision.

Semantic Interoperability for Big Data Professor Markus Stumptner, Dr Wolfgang Mayer, Dr Georg Grossmann

Computer Science, Data Management, Ontologies Suitable as PhD project

Abstract: Big Data is the “new oil” – the substance that is expected to drive the information economy of tomorrow.

Big Data applications and projects are everywhere and companies prepare for the future where they cannot survive

without the information gleaned from a variety of data sources. It is this variety (the third of the three ‘V’s associated

with Big Data: volume, velocity, and variety) that Variety refers to the need to deal with many different data sources

and data formats. This project will examine the use of semantics (i.e., background knowledge about the data) for the

effective combination of different data sources that is a prerequisite for data mining.

The work is aligned with the $88 Million Data to Decision Collaborative Research Centre (D2D CRC).

References:

1. Berger, S., Grossmann, S., Schrefl, M., and Stumptner, M. (2010). Metamodel‐Based Information Integration at

Industrial Scale. In Proc. of the 13th ACM/IEEE Conference on Model Driven Engineering Languages and Systems

(MODELS), pages 153‐167, Springer.

2. Feiler, E. et al. (2006). Ultra‐Large‐Scale Systems: The Software Challenge of the Future. Software Engineering

Institute, CarnegieMellon.

3. Stonebraker, M., Bruckner, D., lyas, I., Beskales, G., Cherniack, M., Zdonik, S., Pagan, M., Xu, S (2013). Data

Curation at Scale: The Data Tamer System. 6th Biennial Conference on Innovative Data Systems Research

(CIDR’13), Asilomar, California.

4. Stonebraker, M., Madden S., Debey P. (2013) Intel “Big Data” Science and Technology Center Vision and Execution

Plan. SIGMOD Record 42(1).

5. Knoblock, C., Szekely, P. (2015) Exploiting Semantics for Big Data Integration. AAAI Magazine, Spring 2015.

ACRC: STRATEGIC INFORMATION MANAGEMENT

Anti‐Mobile Malware, Mobile Security Including Money Honeypot, VoIP Security and

Interception, Critical Information Infrastructure Protection, Anti‐Phishing/Spam, Cryptographic

Protocols and Information Security Risk Management Framework and Standards Associate Professor Raymond Choo

Information Systems, Cyber Security Suitable as PhD and Masters project

Abstract: Cyber threats are increasingly important and strategically relevant in developed economies, and cyber

security has been identified as one of the highest‐priority items on the global policy and national security agendas,

and an increasingly challenging policy area for governments (including the Australian Government). Cyber security is a

highly specialised and interdisciplinary field, which requires a deep understanding of the underlying technical and

social aspects, intimate knowledge of temporal trends – historical, recent and emerging trends, etc. For example,

what are the challenges and implications of emerging technologies such as cloud computing, IPv6 and Voice over IP

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(VoIP) for governments and other key stakeholders; and what ICT are needed to protect and secure our critical

infrastructure sectors from cyber criminals?

There is a range of projects available across vastly different disciplinary bases. Examples include:

Anti‐mobile malware

Mobile security (e.g. money honeypot)

VoIP security and interception

Critical information infrastructure protection (e.g. smart grid)

Anti‐phishing/spam

Cryptographic protocols (e.g. key management protocols and digital signatures)

Information security risk management framework and standards

Cloud privacy enhancing and/or cryptography Associate Professor Raymond Choo

Cyber security, Cloud security, Cloud privacy Suitable as PhD project

Abstract: To address emerging security and privacy challenges of the cloud infrastructure, and its applications and

services, students will be part of an exciting team to design solutions to mitigate malicious attacks by trusted users

(e.g. cloud employees) and ensure the security and privacy of user data.

References:

1. http://www.computer.org/cms/Computer.org/transactions/cfps/cfp_tccsi_cse.pdf

2. http://acmtecs.acm.org/special‐issues/15/edfs2015.html

3. Yang Y, Liu J, Liang A, Choo KKR and Zhou J 2015. Extended Proxy‐Assisted Approach: Achieving Revocable Fine‐

Grained Cloud Data Encryption. In Proceedings of 20th European Symposium on Research in Computer Security

(ESORICS 2015), Vienna, Austria, Lecture Notes in Computer Science, Springer‐Verlag [In press]

Cloud security Associate Professor Raymond Choo

Cyber security, Cloud security, Cloud privacy Suitable as PhD project

Abstract: To address emerging security and privacy challenges of the cloud infrastructure, and its applications and

services, students will be part of an exciting team to design solutions to mitigate malicious attacks by trusted users

(e.g. cloud employees) and ensure the security and privacy of user data.

References:

1. http://www.computer.org/cms/Computer.org/transactions/cfps/cfp_tccsi_cse.pdf

2. http://acmtecs.acm.org/special‐issues/15/edfs2015.html

3. Yang Y, Liu J, Liang A, Choo KKR and Zhou J 2015. Extended Proxy‐Assisted Approach: Achieving Revocable Fine‐

Grained Cloud Data Encryption. In Proceedings of 20th European Symposium on Research in Computer Security

(ESORICS 2015), Vienna, Austria, Lecture Notes in Computer Science, Springer‐Verlag [In press]

4. http://www.journals.elsevier.com/pervasive‐and‐mobile‐computing/call‐for‐papers/special‐issue‐on‐mobile‐

security‐privacy‐and‐forensics/

Collaborative Web search (social search) Dr Tina Du

Information Systems, Collaborative Information Retrieval, Web Search, Social Media Suitable as PhD and Masters

project

Abstract: Research has shown that people intend to collaborate in various situations. Nowadays people would like to

collaborate through the Web while searching for information. For example, they often desire to collaborate on search

tasks. It is argued that introducing support for collaboration and communication into information retrieval systems

would help users to find information more effectively. Collaborative information retrieval (CIR) deals with

collaboration in searching for information. The sociality trait of information search has been prominent under Web

2.0. As an emerging online information search approach, social search not only challenges traditional theories of

information searching but influences people's behaviour as they search information online. This project explores the

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characteristics of the collaboration between searchers, and among searchers, platforms (e.g. social media) and

resources available.

References:

1. Boydell, O. & Smyth, B. (2010). Social summarization in collaborative Web search. Information Processing &

Management, 46(6), 782‐798.

2. Morris, M. R. (2008). A survey of collaborative web search practices. In Proceedings of ACM Conference on

Human Factors in Computing Systems (SIGCHI) (pp 1657–1660). New York: ACM Press.

3. Mohammad Arif, A. S., Du, J. T., & Lee, I. (2014). Understanding tourists’ collaborative information retrieval

behavior to inform design. Journal of the Association for Information Science and Technology.

4. Shah, C., & Marchionini, G. (2010). Awareness in collaborative information seeking. Journal of the American

Society for Information Science and Technology, 61(10), 1970‐1986.

Connecting to knowledge: Accessing information via the Internet by Indigenous communities Dr Tina Du

Information systems, internet use, web search, information behaviour, Indigenous people

Suitable as PhD and Masters project

Abstract: For the first time, this research project researches into the social impact of the Internet on the life of

Indigenous Australians. Such as, what it is Indigenous Australians want and do not want from information technology,

their experience with the Internet and web searching, and the extent that they interact with the Internet to meet

every day needs. The findings would be useful to enable government agencies, funding bodies and community groups

to make evidence‐based actions and decisions on the role of the Internet in breaking down barriers and closing the

gap of social and economic isolation of Indigenous Australians.

This project investigates Indigenous People’s engagement with the Internet to meet every day needs and how the

Indigenous Communities will benefit from the use of the Internet and. Welcome all potential applicants from diverse

backgrounds. Aboriginal students are more than welcome to apply.

References:

1. Dyson, L. E. (2004). Cultural Issues in the Adoption of Information and Communication Technologies by

Indigenous Australians. In F. Sudweeks and C. Ess (eds), Proceedings Cultural Attitudes Towards Communication

and Technology 2004, Murdoch University, Australia, pp. 58‐71.

2. Dyson, L. E. & Underwood, J. (2006). Indigenous People on the Web. Journal of Theoretical and Applied Electronic

Commerce Research, 1(1), 65‐76.

3. Lilley, S.C. (2008). Information barriers and Māori secondary school students. Information Research, 13(4) paper

373. [Available at http://InformationR.net/ir/13‐4/paper373.html]

4. Meyer, H.W.J. (2009). The influence of information behaviour on information sharing across cultural boundaries

in development contexts. Information Research, 14(1) paper 393 [Available from 1 March, 2009 at

http://InformationR.net/ir/14‐1/paper393.html]

Darknet monitoring and/or analytics Associate Professor Raymond Choo

Cyber security, Underground economy, Hacker economy, Darknet Suitable as PhD project

Abstract: The scope of this project includes designing of tools to monitor, extract and analysis malicious DarkNet

traffic.

Forensic Visualisation, Cloud Forensics, Big Data Forensics, Mobile and Anti‐Mobile Forensics,

Hard Disk Forensics, Multimedia Forensics, and Digital Forensic and Incident Response Standards Associate Professor Raymond Choo

Information Systems, Digital Forensics Suitable as PhD and Masters project

Abstract: Digital forensics (also known as forensic computing, computational forensics and computer forensics) is the

discipline that is used for the acquisition and analysis of digital evidence. The use of digital forensics can be applied to

any crime that involves a digital device capable of storing electronic/digital information (e.g. in murder investigations

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where computers, (smart) mobile devices and digital cameras were used). Given the increase in ICT in everyday life,

digital forensics is increasingly being used in the courts in Australia and overseas. To reduce the risk of digital

(forensic) evidence being called into question in judicial proceedings, it is important to have a rigorous methodology

and set of procedures for conducting forensic investigations and examinations.

There is a range of projects available across vastly different disciplinary bases. Examples include:

Forensic visualisation (e.g. using visualisation such as virtual reality application to produce interactive prototypes

to visualise, present and reconstruct electronic evidence)

Cloud forensics

Big data forensics

Mobile and anti‐mobile forensics

Hard disk forensics, particularly Solid State Drives (SSDs) forensics

Multimedia forensics

Digital forensic and incident response standards

References:

1. D Quick, B. Martini, and K. R. Choo, Cloud Storage Forensics, Elsevier 2014

(http://store.elsevier.com/product.jsp?isbn=9780124199705)

Immigrant youth and children Dr Tina Du

Information Management, Information Behaviour, Information Use, Public Libraries


Abstract: Population is a central issue for any nation, but particularly for one composed mainly of recent immigrants

that is continuing to build itself on immigration. According to the figures released by the Australian Bureau of Statistics

(ABS), as at June 2010, more than one in four people in Australia were born overseas, with many of these arriving as

young adults, youth, and children. In this project, the student will work with the migrant youth and children in their

own settings to investigate and understand how they engage with their family, friends, and everyday life around

information and social media and how all of this can be better supported through social services such as public library

services. The knowledge gained from this study will recommend strategies that librarians can use to help public

libraries design better services for immigrant populations by focusing on what works best for their youth and

children.

References:

1. Chu, C. M. (1999). Immigrant children mediators (ICM): Bridging the literacy gap in immigrant communities. The

New Review of Children's Literature and Librarianship, 5, 85‐94.

2. Du, J. T. (2014). The information journey of marketing professionals: Incorporating work task‐driven information

seeking, information judgments, information use, and information sharing. Journal of the Association for

Information Science and Technology. DOI: 10.1002/asi.23085

3. Katz, I., & Redmond, G. (2009). Review of the Circumstances among Children in Immigrant Families in Australia. In

Innocenti Working Paper ‐ Special Series on Children in Immigrant Families in Affluent Societies (IWP‐2009‐12).

4. Khoir, S., Du, J. T., & Koronios, A. (2014). Study of Asian immigrants’ information

behaviour in South Australia: Preliminary results. In Proceedings of the iConference (pp. 682‐689).

doi:10.9776/14316.

5. Taylor, J. & H. MacDonald. (1992) Children of Immigrants: Issues of Poverty and Disadvantage, Bureau of

Immigration and Population Research, Canberra.

Information Management and Governance Dr Jing Gao, Professor Andy Koronios

Information Systems, Strategic Information Management Suitable as PhD project

Abstract: Information management has become a critical factor to the success of contemporary organisations.

Information is intricate and its management may be elusive, as the quality aspects of information are often ignored.

Especially with the rapid evolving Big Data analytics capabilities, management of information has become a business

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philosophy, aligning policy, strategy, culture, information and technology to facilitate the ways information can

benefit businesses. Thus, information management is not just a management activity, but also a strategic one

delivering a business innovations and competitive advantage. Consequently SIMLab@UniSA conducts cutting edge

research in the area of strategic information management. Contact: Jing Gao, [email protected]

Internet of Things Security and Privacy Associate Professor Raymond Choo

Cyber security, Internet of Things Security and Privacy Suitable as PhD project

Abstract: Students will be part of an international collaboration (http://toit.acm.org/CfP/ACM‐ToIT‐CfP‐IoT‐

Security.pdf) working on different aspects of Internet of Things (IOT) security and privacy depending on their

background and skillset.

Mobile app vulnerability detection and exploitation Associate Professor Raymond Choo

Mobile security, Mobile app vulnerability and exploitation, Mobile device vulnerability and exploitation

Suitable as PhD project

Abstract: Undertake cutting edge research to detect and/or exploit previously unknown vulnerabilities in mobile

apps, OS and device.

References:

1. Do Q, Martini B and Choo K‐K R 2015. Exfiltrating Data from Android Devices. Computers & Security 48: 74–91.

DOI: http://dx.doi.org/10.1016/j.cose.2014.10.016

2. O'Malley S and Choo K‐K R 2014. Bridging the Air Gap: Inaudible Data Exfiltration by Insiders. In Proceedings of

20th Americas Conference on Information Systems (AMCIS 2014), 7–10 August 2014, Association for Information

Systems. http://aisel.aisnet.org/amcis2014/ISSecurity/GeneralPresentations/12

3. D’Orazio C and Choo KKR 2015. A generic process to identify vulnerabilities and design weaknesses in iOS

healthcare apps. In Proceedings of 48th Annual Hawaii International Conference on System Sciences (HICSS 2015),

pp. 5175–5184, 5–8 January 2015, IEEE Computer Society Press

4. http://www.journals.elsevier.com/pervasive‐and‐mobile‐computing/call‐for‐papers/special‐issue‐on‐mobile‐

security‐privacy‐and‐forensics/

Online multitasking (Mobile multitasking) Dr Tina Du

Information Systems, Interactive Information Retrieval, Web Search, User Experience


Abstract: In the daily life, humans are naturally multitasking beings, who are often either handing multiple tasks

sequentially or in parallel, or executing one task across multiple working sessions. These phenomena have also been

recently observed on the Web environment. Multitasking is viewed to be important user behaviour in Web/online

sessions. Performing multiple tasks (related or unrelated) and multi‐session tasks are two common patterns of

multitasking on the Web. In the first pattern, Web users execute several tasks, related or unrelated, simultaneously

and switch between them; while in the second pattern, users execute a single task spanning multiple online sessions.

There has been a large body of research reporting on the second pattern, including the features and approaches of

multi‐session tasks and the corresponding Web browser tools support such as revisitation functionality and

resumption support. However, little research has examined the first pattern multitasking behaviour in Web search.

This project investigates how Web users manage multiple tasks/topics concurrently and how to present them running

in parallel in a browser in such a way as to make sense to users. Online multitasking on the mobile platform could be

an interesting focus.

References:

1. Du, J.T. (2011). Cognitive coordinating behaviors in multitasking Web search. In Proceedings of the 34th

International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR),

pp.1117‐1118.

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2. Du, J.T. & Spink, A. (2011). Towards a Web search model: Integrating multitasking, cognitive coordination and

cognitive shifts. Journal of the American Society for Information Science and Technology, 62(8), 1446–1472.

3. MacKay, B. & Watters, C. (2012). An examination of multisession Web tasks. Journal of the American Society for

Information Science and Technology, 63(6), 1183–1197.

4. Wang Q. & Chang H. (2010). Multitasking bar: Prototype and evaluation of introducing the task concept into a

browser. In Proceedings of the Special Interest Group on Human–Computer Interaction (SIGCHI) Conference on

Human Factors in Computing Systems (pp. 103–112). New York: ACM Press.

ACRC: WEARABLE COMPUTER

A New Projector Based Augmented Reality Precise CAD‐Like Manipulations Professor Bruce Thomas

Computer Science, Augmented Reality, ACRC, Wearable Computer Lab Suitable as PhD project

Abstract: Projector‐based augmented reality is the projection of virtual information directly onto and registered to

physical objects. Users are able to view this information unencumbered by technology, such head mounted displays or

handheld devices, and they are to interact with physical object and virtual information simultaneously. Interestingly

that much of the physical hardware (computers, projectors, cameras, and networks) requires existing technologies

found in current office workplaces today. The basic software infrastructure to correctly register the virtual information

onto the physical objects is currently operational. The research investigation into the user interface techniques is still

required to make projector‐based augmented reality a useful tool. In particular, there are a number of problems for a

user performing precise manipulation for CAD‐like operations.

The project will demonstrate the effectiveness of the user interface methodology by showing its ability to support

industrial activities such as: product design, training for manufacturing, in‐situ information presentation for assembly,

layout for confined command and control centres, and home entertainment. The current development of information

for these is with traditional CAD applications. The techniques developed under this proposal will allow users to

interact and perform effective tasks in a completely new fashion with computers, such as interact with simulated

buttons, precise placement of details on a physical object, presentation of animated instructions on a moving

assembly line, or react to the placement of a user’s hand on the physical object. Currently the best options are the use

of a traditional mouse and simple 3D pointing.

Research question posed by this investigation is as follows: “What are an effective precise user interface interaction

techniques to support tasks in projector‐based augmented reality?”

This investigation is critical as there is not an appropriate user interface methodology for projector‐based augmented

reality. The current state of the art projector‐based augmented reality is simple freehand drawing and painting, with

all the precise manipulation performed with 3D CAD applications.

Augmented Reality Intelligent Tutoring Systems Professor Mark Billinghurst

Computer Science, Augmented Reality, Expert Systems, Intelligent Tutoring Suitable as PhD project

Abstract: The research aims to develop a platform for building Intelligent Training Systems (ITS) using Augmented

Reality (AR) for improving training on spatial tasks (eg machine maintenance, object assembly, etc). There has been

existing research that shows that constraint based ITS can significantly help with improving training, and similarly AR

has been used to create simple procedural training systems. However there has been little research that has tried to

combine the two fields together to create Intelligent AR training systems, thus this research will creating a new

approach for intelligent training systems.

The overall research aim is to explore if Augmented Reality (AR) and be combined with Intelligent Training System

(ITS) software to provide a significantly improved training experience on real world spatial tasks (eg assembly,

maintenance, etc) than traditional tools (eg paper manuals, video clips, etc). We will develop a prototype system that

will allow a user wearing an AR head mounted display (or using a desktop/handheld system) to look at real world

objects and see virtual training cues superimposed over them to help him or her learn how to perform a task in their

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natural work setting (eg how to disassemble a real engine). This aim will be achieved through research conducted in

four related areas: (1) Fundamental tracking, interaction, and AR interface techniques, (2) ITS system development

and tools for spatial representation, (3) System integration and demonstration development, (4) Evaluation and user

testing. Underlying all of this work is background research in each of the areas to ensure that we are using the most

recent research approaches and that it is novel compared to existing methods.

References:

1. Mitrovic, A., Martin, B. Suraweera, P., Zakharov, K., Milik, N., Holland, J., McGuigan, N. (2009) ASPIRE: an

authoring system and deployment environment for constraint based tutors. Artificial Intelligence in Education,

19(2), 155‐188.

2. Henderson, S. J. & Feiner, S. (2009) Evaluating the benefits of augmented reality

3. for task localization in maintenance of an armored personnel carrier turret. Proc. 8th

4. Int. Symp. Mixed and Augmented Reality, 135‐144.

5. Westerfield, G., Mitrovic, A., Billinghurst, M. (2013) Intelligent Augmented Reality

6. Training for Assembly Tasks. In: K. Yacef et al. (Eds.): AIED 2013, LNAI 7926, pp.

7. 542‐551.

Augmented Reality Teleconferencing Professor Mark Billinghurst

Computer Science, Wearable Computing, Augmented Reality, Teleconferencing Suitable as PhD project

Abstract: The goal of this project is to explore how Augmented Reality technology can be used to enhance remote

collaboration and teleconferencing, particularly for remote expert assistance in industry. Augmented Reality (AR) is

technology that allows virtual images to be overlaid on the real world. Currently, audio and video conferencing tools

can provide remote technical assistance, however software such as Skype is typically designed for supporting face‐to‐

face communication and not task space collaboration, where the goal is showing the user’s workspace. In complex

repair tasks is it more important to see what the user is trying to do, rather than show their face.

Previous research has shown that using a head mounted display with a camera attached can allow a remote expert to

see what a worker is doing and provide effective support. However, there are limitations with traditional video

conferencing when it is used to support task space conferencing, such as the remote person not being able to

annotate the local user’s view, limited support for gesture input, or being difficult for the remote user to see separate

from where the local user is looking. Using AR can overcome some of these limitations by directly annotating the

workers view with virtual cues.

Earlier research has explored various aspects of using AR to improve remote collaboration. It has shown that sharing

video views of the real world, providing remote virtual pointing, using spatial audio, and shared 3D models overlaid on

real objects can all aid remote collaboration. In this project we want to continue this research, and in particular

exploring how AR can be combined with depth sensing technologies to support very nature gesture collaboration, and

the capture and sharing of the users environment.

References:

1. Kim, S., Lee, G., Sakata, N., & Billinghurst, M. (2014, September). Improving co‐presence with augmented visual

communication cues for sharing experience through video conference. In Mixed and Augmented Reality (ISMAR),

2014 IEEE International Symposium on (pp. 83‐92). IEEE.

2. Gauglitz, S., Nuernberger, B., Turk, M., & Höllerer, T. (2014, November). In touch with the remote world: remote

collaboration with augmented reality drawings and virtual navigation. In Proceedings of the 20th ACM Symposium

on Virtual Reality Software and Technology (pp. 197‐205). ACM.

3. Billinghurst, M., & Kato, H. (2002). Collaborative augmented reality. Communications of the ACM, 45(7), 64‐70.

4. S. Fussell, L.Setlock, and R.Kraut. 2003. Effects of head‐mounted and scene‐oriented video systems on remote

collaboration on physical tasks. In Proceedings of CHI '03. ACM, New York, NY, USA, 513‐520.

5. Gurevich, P., Lanir, J., Cohen, B., & Stone, R. (2012, May). TeleAdvisor: a versatile augmented reality tool for

remote assistance. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 619‐

622). ACM.

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Deep neural networks for human emotion recognition Professor Mark Billinghurst, Associate Professor Mark McDonnell

Computer Science, Wearable Computing, Teleconferencing Suitable for Vacation Scholarship

Newly developed "deep learning" methods have reignited the field of neural networks in the last few years. For

example, Google DeepMind recently announced the first

computer program that plays the game of Go at human expert level, and this relied on deep learning.

The aim of this project is to design software that learns to robustly recognise human emotions, by making use of a

multiple types of sensor data, such as video, still images, and biometrics. It is expected that the main algorithm to be

implemented will be a deep convolutional neural network. It will be based on the earlier work of Yu and Zhang [1]

who have been able to get emotion recognition rates of up to 85% with a neural network technique.

The context of use will be explore if emotional recognition code can be developed that can run in near real time on

live camera video and so provide feedback on user emotion while operating a computer interface. For example, using

the video feel from a laptop camera to monitor the emotions of a person in front of it. Contact

[email protected] and [email protected]

1. Yu, Z., & Zhang, C. (2015, November). Image based static facial expression recognition with multiple deep network

learning. In Proceedings of the 2015 ACM on International Conference on Multimodal Interaction (pp. 435‐442).

ACM.

Deformable User Interfaces Dr Ross Smith

Computer Science, Augmented reality Suitable as PhD project

Abstract: Advancing the science of Deformable Surfaces by inventing new smart materials that can not only capture

their changing form through input but can also recognise properties of the objects they touch such as sharp, dull,

curved and planar characteristics. Deformable Surfaces have great potential to significantly change the way humans

interact with computing systems ‐ just as touch screens have revolutionised the mobile phone and tablet computing

fields. Materials and electronics are beginning to support flexible and stretchable devices, this research will model

deformable surface properties for future applied uses. As soft deformable materials such as foam, silicon rubber and

liquids are enhanced with sensors, a host of novel devices and interaction techniques will be made possible. This

project will investigate the use of smart materials including new physical prototypes and actuation technologies.

References:

1. Ou, J., et al., jamSheets: thin interfaces with tunable stiffness enabled by layer jamming, in Proceedings of the 8th

International Conference on Tangible, Embedded and Embodied Interaction. 2013, ACM. p. 65‐72.

2. Follmer, S., et al., Jamming user interfaces: programmable particle stiffness and sensing for malleable and shape‐

changing devices, in Proceedings of the 25th annual ACM symposium on User interface software and technology.

2012. p. 519‐528.

3. Fujimoto, Y., Smith, R. T., Taketomi, T., Yamamoto, G., Miyazaki, J., Kato, H., Thomas, B. H., Geometrically‐correct

projection‐based texture mapping onto a deformable object, IEEE Transactions on Visualization and Computer

Graphics (TVCG), , *TO APPEAR*, 2014

4. Smith, R. T., Thomas, B. H., Piekarski, W., Digital foam interaction techniques for 3D modeling, Proceedings of the

2008 ACM symposium on Virtual reality software and technology, 61‐68, Bordeaux, France, 2008

Disaggregation of Wearable Computation Devices Professor Bruce Thomas


Abstract: This project will investigate the disaggregation of wearable computation devices over different portions of

the user’s body. The current trend of mobile and wearable devices is for them to be self‐contained with all the

required functionality. Self‐contained devices have the advantage of being able to operate autonomous without the

need of other devices. The approach taken in this project is to enhance wearable computation devices with the

aggregation of functionality from several devices carried by the user. This approach is particularly appropriate for light

weight devices such as head mounted displays that have an absolute maximum size and weight for the user to wear

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comfortable and have a fashionable appearance. The project will produce a series of wearable computational devices

to support head mounted displays and watch computing devices in user interaction, sensing, and device memory. The

main goals of the project are to increase the functionality and reduce the energy consumption of the wearable

devices.

Empathic Conferencing Professor Mark Billinghurst

Computer Science, Wearable Computing, Teleconferencing Suitable as PhD project

Abstract: The goal of this project is to conduct research on how wearable computers can be used to capture and share

emotional experiences. In recent years there has been a lot of research conducted on how wearable computers can

be used to create new types of collaborative experiences. For example, wearable computers such as Google Glass

have cameras on them that can be used to stream video to a remote person and allow them to see what the wearer is

seeing. However there has been much less research on sharing people's emotional experience. In this project we will

explore how simple physiological sensors can be used to capture a user's emotion and then share that with a remote

partner. For example, heart rate and skin conductivity sensors can be used to detect when a person is feeling excited,

and the visual and audio cues could be used to convey that excitement to a remote collaborator.

References:

1. Tan, C. S. S., Luyten, K., Van Den Bergh, J., Schöning, J., & Coninx, K. (2014). The role of physiological cues during

remote collaboration. Presence: Teleoperators and Virtual Environments, 23(1), 90‐107.

2. TAN, C. S. S. (2014). Enabling Empathic Communication in Ubiquitous Computing Environments to Improve

Interaction between People.

3. Datcu, D. On the Enhancement of Augmented Reality‐based Tele‐Collaboration with Affective Computing

Technology.

4. Cai, Y. (2006). Empathic computing. In Ambient Intelligence in Everyday Life (pp. 67‐85). Springer Berlin

Heidelberg.

Face to Face Collaboration Using Hololens Professor Mark Billinghurst


The Microsoft Hololens hardware combines a see‐through head mounted display with excellent indoor tracking, and

so provides an ideal platform for Augmented Reality. In this project we want to explore how the Hololens could be

used to enhance face‐to‐face collaboration.

The project will involve developing an example Hololens application that will allow two people in the same room to

view and interact with the same virtual content. This will build on earlier work that we have done in face‐to‐face AR

interaction [1][2]. In addition we will explore novel interaction methods such as using virtual cues to show where

people are looking, and enabling users to see from each other viewpoints. Contact [email protected]

1. Billinghurst, M., & Kato, H. (2002). Collaborative augmented reality.Communications of the ACM, 45(7), 64‐70.

2. Billinghurst, M., Kato, H., Kiyokawa, K., Belcher, D., & Poupyrev, I. (2002). Experiments with face‐to‐face

collaborative AR interfaces. Virtual Reality,6 (3), 107‐121.

Gaze Interaction for Remote Collaboration Professor Mark Billinghurst


For a number of years people have been studying how head worn cameras (HWCs) and head mounted displays

(HMDs) can be used for remote collaboration on physical tasks. The HWC allows a remote expert to see what the local

user is doing, while a HMD can allow the remote expert to provide Augmented Reality (AR) virtual cues overlaid on the

local user’s view of the real world to help them complete the task. For example, in a remote maintenance task,

workers using a wearable AR interface were able to reduce their task performance time by up to 30% [1].

In face‐to‐face conversation gaze provides information about where a person is directing his or her attention and so it

could also be an important cue in remote collaboration. Previous research has found that sharing gaze between two

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remote collaborators significantly improved performance on a desktop visual search task, compared to audio only

communication [2]. However there has been little research conducted on sharing gaze cues from a wearable

collaborative system. In this project we want to explore the effect of adding gaze tracking to wearable systems for

remote collaboration.

The work would extend our earlier pilot work in this area [3] and involve the following: Background research on gaze

tracking in collaborative systems, Create a prototype system integrating a HMD, HMC and eye‐tracker, Conduct user

studies with a variety of physical tasks, and Write research report. Contact [email protected]

1. Gauglitz, S., Lee, C., Turk, M., Höllerer, T. (2012). Integrating the physical environment into mobile remote

collaboration. In Proceedings of the 14th international conference on Human computer interaction with mobile

devices and services, pp. 241‐250.

2. Brennan, S. E., Chen, X., Dickinson, C. A., Neider, M. B., Zelinsky, G. J. (2008). Coordinating cognition: the costs and

benefits of shared gaze during collaborative search. Cognition. 106, 1465–1477.

3. Masai, K., Sugimoto, M., Kunze, K., Billinghurst, M. (2016) Empathy Glasses. In Proceedings of CHI 2016, May 7th –

12th San Jose, CA, USA

Spatial Augmented Reality Design Tools Professor Bruce Thomas


Abstract: Currently the design of manufactured high‐end instrumented facilities (such as command centres and

control panels) is one of working almost entirely in the virtual world. The physical space and layout of such systems

demands high‐level 3D spatial visualizations from the stakeholders. Instead of visualizing a command centre with

virtual reality tools or expensive physical prototypes, this project will explore white painted lightweight wooden

objects that would be built to the external dimensions of the major components of the centre and the details of the

workstation will be projected onto them via large scale augmented reality.

The current process of decision‐making is time consuming. A major effort is the externalisation of the clients’ needs

and requirements. Normal practices require a large number design meetings iterating over concepts that are present

as either engineering drawings or 3D static renderings. The use of animations with fly‐throughs and guided tours

allows for a more immersive experience, but the clients lack the tools to manipulate the concept themselves.

This project wishes to investigate a set of novel tools that allows design teams to manage a process of the clients to

manipulate the design concepts. To do this, we will place the clients in physical environment that emulates the final

high‐end instrumented facility. The end users will be able to view the command centre from any vantage point by

merely walking. Physical moving the physical prototypes or manipulating the virtual information projected onto the

prototypes can modify the configuration of workstations or controls on the panels.

To make these tools useful for the manufacturer, this new design methodology must be embedded in the company’s

current design process. Issues of data transfer, operation semantics, workflows, and process planning will have to be

addressed.

Storytelling of Big Data Professor Bruce Thomas

Computer Science, Augmented Reality Suitable as PhD project

Abstract: This project is concerned with the development of storytelling tools to allow a user to develop multimedia‐

briefing presentations. In essence presentations that provide a non‐linear means of presenting a set of data points and

facts to validate a set of augments. The briefing is not a written document, but an interactive tool to provide a more

complete picture of how the data and facts support a set of conclusions. The order of the presentation is driving by

the particular nature of the information and the recipients of that information. What is unique about this approach is

the end users are able to drill down in real time to expose more detail on demand. Linear text documents do not

support this functionality.

The storytelling tool has three main parts: 1) collection, 2) authoring, and 3) presentation. The collection phase

supports the user in identifying potential important pieces of data and particular facts to support a particular

conclusion. These must be readily available to the user for the construction of the final augment. The authoring phase

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provides the user the ability to construct an interactive multimedia presentation to justify the conclusions drawn from

the data and facts. These presentations are chosen from the set of styles that best support the types and forms of

augments presented for the particular domain of the user. Because the presentations are stylised from a set known

forms of augments, the tool is able to provide very high‐level support to the end user. Final the presentation will be

interactive. This interactive nature of the presentation allows for a non‐linear presentation of the information. The

particular people viewing the presentation guides the order and pacing of the delivery of the information.

User interaction for interactive constraints and spatial augmented reality Professor Bruce Thomas, Dr Ross Smith, Dr Wolfgang Mayer


Abstract: This project will investigate the science of human‐computer interaction for spatial augmented reality (SAR)

environments into new methodologies that present design prototypes as virtual/physical (VP) entities that can be

presented and manipulated in ways that are not currently available. This investigation will provide a tight coupling

between design tools and VP design representations, enabling designers to employ 3D constraint specification via

novel input techniques to directly modify VP entities. By crafting, realizing and evaluating a constraint driven AR user

interface for CAD tools, this project aims to enhance users’ spatial reasoning capacity for numerous design

applications.

Virtual Reality Brain Training Tools Dr Ross Smith

Computer Sciences, Simulation Systems, Augmented Reality, Virtual Reality, Health Sciences Suitable as PhD project

Abstract: This project will investigate the use of simulation systems to support medical applications. The study will

explore how Augmented and Virtual reality systems can be employed to develop therapy and training applications.

Current research has demonstrated positive outcomes in a diverse set of medical applications. For example, cognitive

performance can be improved in Alzheimer’s patients by employing simulation systems with exercise [1]. The

reduction of pain can also be achieved through the use of immersive Virtual Reality systems during wound care. More

recently the use of a virtual reality system has been demonstrated to alter the pain thresholds for patients suffering

from neck pain [3]. This project will investigate how a set of virtual reality brain training tools can be developed to

further understand aspects of psychology, pain and cognition with the aim of developing therapy applications.

References

1. Anderson‐Hanley C1, Arciero PJ, Brickman AM, Nimon JP, Okuma N, Westen SC, Merz ME, Pence BD, Woods JA,

Kramer AF, Zimmerman EA. Exergaming and older adult cognition: a cluster randomized clinical trial. American

Journal of Preventitive Medicine, 42(2):109‐19, 2012

2. Hoffman HG, Doctor JN, Patterson DR, Carrougher GJ, Furness, TA III. Use of virtual reality for adjunctive

treatment of adolescent burn pain during wound care: A case report. Pain 2000;85:305‐309.

3. Harvie, D. S., Broecker, M., Smith R. T., Meulders, A., Moseley, G. L., Bogus Visual Feedback Alters Onset of

Movement‐Evoked Pain in People With Neck Pain, Psychological Science, 385‐392, Vol:26, No:4, Feb 2015

Visualising and Interacting with Large Graphs of Big Data Professor Bruce Thomas

Computer science, augmented reality, ACRC, wearable computer lab Suitable as PhD project

Abstract: Current collections of the big data in many cases can be presented as one large graph. Recent technological

advances have produced very large data sets that can be presented as graphs that allow humans to discover and

comprehend previously hidden information. This information presentation strategy is employed by intelligence

agencies that monitor social network data to identify possible terrorist attacks, by biologists to explore interactions

between cell systems, and by engineers to explore complex software architectures. As the size of the data sets

increases exponentially, currently known visualization techniques fail to present easily understandable data, and the

need to find new methods of information presentation to support informed decision‐making is an open research

question. A current open research question is the need for better methods that allow users to understand and

visualise large networks. This project will extend the science of human interaction with large graphs by developing

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new paradigms that present entire graphs employing abstract graph layout algorithms and novel input techniques.

The goal of developing these methodologies is to reduce the cognitive overhead that is the key limiting aspect of

current visualization methodologies.

Some particular issues for visualising and interacting with large graphs are as follows:

When the number of nodes of a graph approaches or exceeds the number of pixels on the computer monitor,

how is the graph presented and how can the user interact with that graph?

How is the major underlying structure of interest presented to the user? This is of particular interest when

multiple graphs are aggregated together.

What are the appropriate methods of visualising and interacting with graphs of known data sources/types? This

question addresses the issue of tailoring tasks and interactions to graphs from particular data sources.

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PART II: CENTRE FOR INDUSTRIAL AND APPLIED MATHEMATICS (CIAM) Page

Applied mathematical modelling in nanotechnology 29

Approximation of Convex Sets 29

Geometry and geometric issues of atomic nanostructures 30

Graphene production, and graphene folding and bubbling 30

Harmonic Analysis: Developing the theory of function spaces on spaces of homogeneous type 30

Modelling methane storage using nano‐bottles 31

Nanoscaled oscillating systems 31

Symmetry methods for nonlinear partial differential equations 32

Applied mathematical modelling in nanotechnology Professor Jim Hill

Applied Mathematics Suitable as PhD project

Abstract: Famous physicist Richard P. Feynman predicted in his historical talk ‘There’s plenty of room at the bottom’

that the possibility of miniaturization and nano‐devices assembling one atom at a time! And with the recent boom and

success in the area of nanotechnology, such prediction seems within reach. Nanotechnology has shown to be useful in

developing future drug delivery and high performance lithium battery, enhancing structural strength, advancing

NEMS, etc. A deeper understanding of mechanics at the nanoscale is key to better design of nano‐devices. In this

project the student will concentrate on classical applied mathematical techniques for problems that would incur high

cost to investigate experimentally or using computational methodologies.

References:

1. B. J. Cox, N. Thamwattana and J.M. Hill, “Mechanics of atoms and fullerenes in single‐walled carbon nanotubes. I.

Acceptance and suction energies.” Proceedings of the Royal Society of London A, 463 (2007) 461‐476.

2. B. J. Cox, N. Thamwattana and J. M. Hill, “Mechanics of atoms and fullerenes in single‐walled carbon nanotubes.

II. Oscillatory behaviour.” Proceedings of the Royal Society of London A, 463 (2007) 477‐494.

3. B. J. Cox, N. Thamwattana and J. M. Hill, “Mechanics of spheroidal fullerenes and carbon nanotubes for drug and

gene delivery.” Quarterly Journal of Mechanics and Applied Mathematics, 60 (2007) 231‐253.

Approximation of Convex Sets Dr Gerald Cheang

Mathematics, Approximation Theory, Functional Analysis, Artificial Neural Networks Suitable as PhD project

Abstract: It is well known that convex polytopes are not good approximations for smooth convex bodies, such as balls

in d‐dimensional space. The traditional polytope approximation of a ball suffers from the curse of dimensionality

problem in high‐dimensional space. In contrast, approximations of the ball by zig‐zag sets such as those proposed in

Cheang and Barron (2000) and Arstein‐Avidian et al. (2005) achieve much better approximation rates. Cheang and

Barron (2000) showed that a threshold of a linear combination of c(d/E)^ 2 half‐spaces is needed to achieve an

accuracy of E for such an approximation. Arstein‐Avidian et al. (2005) improved the result to show that only c(d

log(1/E)/E^2) indicators of half‐spaces are needed. But their result only holds with high probability 1 – e^{‐cd}. More

recently Cheang (2010) used a single‐hidden layer perceptron neural network implanting the ramp sigmoid activation

function to approximate the indicator function of a d‐dimensional ball and used c(d/E)^ 2 ramp sigmoids to achieve a

relative accuracy of E. The goal of this project is to improve on the accuracy of the Cheang (2010) result for the

approximation with ramp sigmoids and also to explore ways of sharpening the result of Arstein‐Avidian et al. (2005).

References:

1. S. Artstein‐Avidan, O. Friedland, V. Milman, Geometric applications of Chernoff‐type estimates and a zigzag

approximation for balls, Proc. Amer. Math. Soc. 134 (2005) 1735–1742.

2. G.H.L. Cheang, A.R. Barron, A better approximation for balls, J. Approx. Theory 104 (2000) 183–203.

3. G.H.L. Cheang, Approximation with neural networks activated by ramp sigmoirs, J. Approx. Theory 162 (2010)

1050‐1065.

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Geometry and geometric issues of atomic nanostructures Professor Jim Hill


Abstract: It is clear from the various structures seen at the nanoscale that the complex self‐ interactions of these

structures often lead to symmetric configurations. In satisfying an overall minimum energy constraint, the system

often adopts a symmetric structure that shares the energetic costs of bending and stretching covalent bonds equally

to all components in the structure. By assuming the symmetric configuration, it is possible to reduce fundamentally

complex problems of molecular structure to problems with are more mathematically tractable and thus derive results

which can be confirmed by experiment and simulation. This approach can also be used to predict ideal systems and

novel structures in certain extreme cases. In this project the student will study geometric models for nanostructures

such as nanotubes, cones and spheres (buckyballs) with the aim of providing more precise predictions of structural

parameters like lengths and radii.

References:

1. B. J. Cox, and J. M. Hill, “Exact and approximate geometric parameters for carbon nanotubes.” Carbon, 45 (2007)

1453‐1462.

2. B. J. Cox, and J. M. Hill, “New carbon molecules in the form of elbow‐connected nanotori.” Journal of Physical

Chemistry C, 111 (2007) 10855‐10860.

3. B. J. Cox, and J. M. Hill, “Geometric structure of ultra‐small carbon nanotubes.” Carbon, 46 (2008) 711‐713.

4. B. J. Cox, and J. M. Hill, “A variational approach to the perpendicular joining of carbon nanotubes to plane

graphene sheets.” Journal of Physics A: Mathematical and Theoretical, 41 (2008) 125203 (11pp).

5. B. J. Cox, and J. M. Hill, “Geometric model for boron nitride nanotubes incorporating curvature.” Journal of

Physical Chemistry C, 112 (2008) 16248‐16255.

Graphene production, and graphene folding and bubbling Professor Jim Hill


Abstract: Graphene comprises carbon sheets of one atomic thickness. The production of graphene that has uniform

electrical and mechanical properties is a major technological challenge, since with present production methods the

graphene tends to inherit any flaws or dislocations that are apparent in the host metallic material. An ideal production

method might involve a sequential technique rather like that used in conventional weaving with a loom. Once

graphene is prepared, it needs to be transferred onto whatever device is being manufactured, which is usually done

with a metal stamp. On being released from the stamp, graphene tends to crumple and stick together forming folds

and bubbles, both of which are highly undesirable. This project will analyze possible methods for sequential graphene

production, and the mathematical modelling of graphene folds and bubbles.

References:

1. B. J. Cox, D. Baowan, W. Bacsa and J. M. Hill, Relating elasticity and graphene folding conformation, submitted for

publication.

Harmonic Analysis: Developing the theory of function spaces on spaces of homogeneous type Associate Professor Lesley Ward

Mathematics, Harmonic Analysis Suitable as PhD project

Abstract: In the mathematical field of harmonic analysis, the functions we study have traditionally been defined on

Euclidean spaces R^n. In recent years, there has been much interest in the new setting where a Euclidean space is

replaced by a more general space of homogeneous type: a set X equipped with a quasi‐metric and a doubling

measure. This project will focus on developing the theory of function spaces such as Hardy spaces, Bounded Mean

Oscillation, A_p weights and reverse Holder weights, the relationships between them, and the operators that act on

them, on spaces X of homogeneous type. We will also consider dyadic and multiparameter versions of the theory.

References:

1. P. Chen, J. Li and L.A. Ward (2013), BMO from dyadic BMO via expectations on product spaces of homogeneous

type, Journal of Functional Analysis 265: 2420—2451.

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2. J. Li, J. Pipher and L.A. Ward (in press), Dyadic structure theorems for multiparameter function spaces, Revista

Matematica Ibéroamericana.

3. E.M. Stein (1993), Harmonic analysis: real‐variable methods, orthogonality, and oscillatory integrals, Princeton

University Press, 1993.

Modelling methane storage using nano‐bottles Professor Jim Hill


Abstract: The traditional storage of methane involves the gas stored in a high‐pressure environment. This presents

environmental hazards for applications requiring a lot of methane, such as for vehicle fuel, domestic cooking and

heating, because of the dangers of explosion. A new storage mechanism for methane involves nano‐bottles, which

combines the advantages of a high ‐ pressure vessel and adsorbents, but requires a lower pressure and thus presents

less risk of an accident. In this project, the student will study models for new storage possibilities for methane using

applied mathematical modeling in nanotechnology.

References:

Suitable as PhD project

1. O. O. Adisa, B. J. Cox and J. M. Hill, “Encapsulation of methane in nanotube bundles.” Micro and Nano Letters, 5

(2010) 291‐295.

2. O. O. Adisa, B. J. Cox and J. M. Hill, “Encapsulation of methane molecules into carbon nanotubes.” Physica B, 460

(2010) 88 – 93.

3. O. O. Adisa, B. J. Cox and J. M. Hill, “Packing configurations for methane storage in carbon nanotubes.” European

Physical Journal B, 79 (2011) 177 ‐ 184.

4. O. O. Adisa, B. J. Cox and J. M. Hill, “Modelling the surface adsorption of methane on carbon nanostructures.”

Carbon, 49 (2011) 3212 – 3218.

5. O. O. Adisa, B. J. Cox and J. M. Hill, “Open carbon nanocones as candidates for gas storage.” Journal of Physical

Chemistry C, 115 (2011) 24528‐24533.

6. Y. Chan and J. M. Hill, “Hydrogen storage inside graphene‐oxide frameworks.” Nanotechnology, 22 (2011) 305403

(8pp).

Nanoscaled oscillating systems Professor Jim Hill


Abstract: Nanoscaled structures such as carbon nanotubes and fullerenes undergo atomic interactions that are

described by van der Waals forces. These can lead to extreme accelerations, and velocities, and in the case of

oscillating systems, to ultra high frequencies in the gigahertz regime. In terms of creating novel electronic devices,

these high frequencies regimes might be important. By modelling the structures as surfaces with uniform atomic

densities and the van der Waals interactions using a 6‐12 Lennard‐ Jones potential, we can make predictions regarding

these systems including derivation of formulae for the frequency that are often in good agreement with molecular

dynamics simulations. This project examines models to calculate the force to predict the behaviour of various

oscillating systems.

References:

1. B. J. Cox, N. Thamwattana and J.M. Hill, “Mechanics of atoms and fullerenes in single‐walled carbon nanotubes. I.

Acceptance and suction energies.” Proceedings of the Royal Society of London A, 463 (2007) 461‐476.

2. B. J. Cox, N. Thamwattana and J. M. Hill, “Mechanics of atoms and fullerenes in single‐walled carbon nanotubes.

II. Oscillatory behaviour.” Proceedings of the Royal Society of London A, 463 (2007) 477‐494.

3. T. A. Hilder and J. M. Hill, “Oscillating carbon nanotori along carbon nanotubes.” Physical Review B, 75 (2007)

125415‐8.

4. N. Thamwattana and J. M. Hill, “Oscillation of nested fullerenes (carbon onions) in carbon nanotubes.” Journal of

Nanoparticle Research, 10 (2008) 665‐677.

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Symmetry methods for nonlinear partial differential equations Dr Bronwyn Hajek, Professor Jim Hill

Applied mathematics, partial differential equations Suitable as PhD project

Abstract: In this project we will apply a number of symmetry methods to determine solutions of some well‐known

nonlinear ordinary and partial differential equations, such as those arising in general relativity, acoustics, finance,

environmental and biological situations, and industrial processes. In this project we will exploit the use of Lie point

(classical) symmetry analysis and other modern approaches to solving PDEs. Lie point symmetry analysis provides a

powerful method for finding groups of transformations which enables one to transform the ODE or PDE to an

equivalent equation of simpler form. In this way, exact analytical and numerical solutions may be found.

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PART III: INSTITUTE FOR TELECOMMUNICATIONS RESEARCH (ITR) Page

COMPUTATIONAL AND THEORETICAL NEUROSCIENCE 34 Bio‐inspired machine learning and intelligence 34

FREE SPACE OPTICAL COMMUNICATIONS 34 Adaptive Free‐Space Optical Communications 34

Coding and Signal Processing For Future Fibre‐Optical Communications 34

MIMO and modulations in visible light communications 35

Positioning by visible light communications 35

INFORMATION THEORY 35 Content distribution using index coding and caching 35

Information theoretic security and privacy 36

Partial rate region characterisations: new frontiers of information theory 36

Refinement of fundamental tools in information theory 36

NETWORKS, TRANSMISSION AND CODING TOPICS 36 Adaptive streaming with delay‐constraints 36

Big Data in Cloud Storage 37

Distributed control and tracking 37

Fundamental Limits of LPD Communication 37

Information theoretic security for networks 38

Network coding for multimedia multicast 38

SOFTWARE DEFINED RADIO 38 Distributed beamforming with SDRs 38

WAVEFORMS AND ALGORITHMS 38 High speed satellite downlinks 39

Second Generation Search and Rescue 39

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ITR: COMPUTATIONAL AND THEORETICAL NEUROSCIENCE Computational neuroscience is the field of scientific research that aims to understand how electrical activity in the

brain represents and processes information. For example, how does information from our senses become transformed

into recognition of objects, sounds or odours, and how do these become learnt by the brain? This research requires

contributions from mathematicians, physicists, computer scientists and electronic engineers. However, our brains

operate very differently to digital electronic computers, and this makes the problem one of "reverse‐engineering" a

complex system, which is quite different to typical engineering design problems.

Bio‐inspired machine learning and intelligence Associate Professor Mark McDonnell

Computational and theoretical neuroscience Suitable as PhD project

Abstract: Engineered technology and biological brains share many common features. For example, brains have

evolved ways to (i) acquire information (sensing), (ii) communicate between brain regions (information transmission)

and (iii) form and recall memories (information storage). Improved knowledge about these processes is essential for

understanding how our brains "compute." The goal of this project is to use insights from computational neuroscience

to design bio‐inspired machine learning algorithms and devices. This project will potentially contribute to future

technologies, as well as "neural engineering" techniques for enabling direct communication between neurons in the

brain and external electronics, such as "bionic eyes" and brain‐machine interfaces.

ITR: FREE SPACE OPTICAL COMMUNICATIONS With increasing demand for broadband communications we are running out of RF spectrum, particularly for mobile

users. Free space optical (FSO) communications offers the possibility of Gbit data rates for terrestrial and satellite

applications without using any licenced spectrum. ITR has been working on a range of FSO and hybrid RF/FSO topics for

the last several years. Examples include the evaluation of channel capacity of FSO channels under various modulation,

fading and MIMO scenarios; channel modeling for FSO and hybrid RF/FSO systems; channel coding schemes for FSO

systems under both ergodic and block fading models; high‐speed architectures for coded FSO communications; and

adaptive transmission techniques for FSO communications. A number of these topics are well suited for further

investigation by research degree candidates, both at the Masters and PhD levels.

Adaptive Free‐Space Optical Communications Professor Bill Cowley

Free space optical communications Suitable as PhD project

Abstract: Over the last few decades the uptake of FSO transmission has been limited by attenuation due to cloud and

fog, plus scintillation fading cause by small variations in the refractive index of the atmosphere. ITR has shown, both

in theory and practice, that channel coding methods are able to address the fading issues and provide reliable and

high‐speed communication channels. Recently our institute has started research into adaptive transmission methods

for FSO communications. Adaptive methods have been used very successfully in fading RF channels for many years,

but so far there has been little use of this approach in optical communications. Our initial investigations indicate that

significant performance gains are possible in FSO links. HDR research in this area will develop these adaptive

techniques, including dealing with practical issues such as the need for rapid synchronisation and the power and

bandwidth limitations of real transducers.

Coding and Signal Processing For Future Fibre‐Optical Communications Associate Professor Terence Chan

Information theory Suitable as PhD project

Abstract: Optical communications offers many advantages compared to its radio frequency counterpart. Optical

carriers have a much higher carrier frequency, allowing for significantly higher information bandwidth. Currently,

technological advance in optical communications is overwhelmingly driven by breakthroughs in physics and photonics.

As photonics technologies mature, and data rates increase, higher‐order nonlinear physical effects and dispersion in

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the medium cannot be ignored (especially for long‐haul transmission). Advanced digital coding and signal processing

techniques become increasingly relevant to address these channel impairments. The aim of this project is to answer

questions concerning data transmission over optical channels.

The project will:

Develop the mathematical tools required for analysis of optical channels

Develop new coding and modulation techniques for optical communications

MIMO and modulations in visible light communications Dr Siu Wai Ho


Abstract: To efficiently use the radio frequency (RF) spectrum is an important area due to the scarcity of the limited

spectrum bandwidth. Despite the efforts to improve the RF spectrum efficiency, the data throughput demand has

outpaced the development. Optical wireless communication has shown the potential to bridge the demand gap due to

the wide bandwidth availability of the optical spectrum. The unregulated and easily available bandwidth (over

terahertz) provided by Visible Light Communication (VLC) is one of the main factors that gives these systems an

advantage over the existing radio frequency (RF) communications. To use visible light for data communications has

gained much attention recently and is developing as a viable and beneficial communication technology, especially for

short‐range indoor systems. The advent of high‐power light emitting diodes (LEDs) and highly sensitive photo diodes

(PDs) and simultaneous use as a source of lighting and data communication have helped the development of VLC as an

attractive as well as energy‐efficient technique for high‐speed data communication. This project will investigate novel

approaches to deal with new challenges in VLC, including coding techniques for intensity constraints in VLC systems,

single carrier and multi‐carrier modulations, etc. In particular, a Multiple‐Input Multiple‐Output (MIMO) system will be

developed by using multiple PDs and LEDs.

Positioning by visible light communications Dr Siu Wai Ho


Abstract: Location‐based services are becoming increasingly important. By knowing a user’s physical location, a

mobile device can provide adequate information to the user and support different mobile applications. For example,

we can have navigation applications and tracking/monitoring applications in our smartphone. To locate a user in

outdoor environments, Global Positioning System (GPS) and cellular‐based positioning have been widely used. For

indoor environments, the performance of these systems is degraded because signals are blocked by walls or

infrastructure. Therefore, alternative solutions are needed for indoor positioning. For example, positioning systems

can be built over wireless local area networks (WLANs). However, the accuracy of these systems depends on whether

the indoor environment is complicated or not. The accuracy can be from one up to several meters.

This project will investigate an indoor positioning system which is cost‐effective and provides accuracy levels within

0.2 meters by using Visible Light Communications (VLC), which is an emerging and promising research area. The aim of

this project is to develop algorithm and system designs for such a high precision requirement.

ITR: INFORMATION THEORY

Content distribution using index coding and caching Associate Professor Gottfried Lechner


Abstract: The explosion of 'cloud' services, streaming video, 'big data', and a myriad of new applications, are opening

up new opportunities and impacting on almost every sector of the economy from education to advanced healthcare.

Communicating this data is putting increasing pressure on limited bandwidth and resources.

This project proposes to change the way we encode data, offering significant potential to improve the efficiency of the

communications network and provide a 10‐100 fold increase in speed. Research topics in this area include index

coding, index coding over noise channels and distributed caching.

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Information theoretic security and privacy Dr Siu Wai Ho


Abstract: Information theoretic security relies on no assumption on the computational power of the adversary. Since

the seminal work by Shannon in 1949, a lot of important results have been developed. Recently, we have a

breakthrough by showing a new fundamental relationship between key size and message size. A new concept about

the consumption of a secret key has been developed. This project explores other fundamental questions in this new

direction. The results can be applied to security problems and also the protection of privacy when we use the Internet.

Partial rate region characterisations: new frontiers of information theory Dr Siu Wai Ho


Abstract: Rate regions define the fundamental limits of applications in different areas, including data networks,

wireless communications, and security systems. However, techniques of information theory are unable to completely

characterise these regions for every application. Our aim is to develop methods for analysing rate regions that do not

rely on complete characterisations. These methods will revolutionise our understanding of rate regions by bypassing

the difficulties of existing techniques. Outcomes will provide practically relevant properties of rate regions that will

enable novel applications in communications systems.

Refinement of fundamental tools in information theory Dr Siu Wai Ho


Abstract: In information theory, many famous tools or results cannot be applied to countably infinite alphabets, e.g.,

strong typicality, Fano’s inequality and one‐time pad. It is important to consider countably infinite alphabets because

this is the general case and this usually gives tighter bounds, faster convergent rates, etc. Recently, we have

generalized the aforementioned tools to countably infinite alphabets due to the observation that entropy is indeed a

discontinuous function.

This project aims to generalize more fundamental results in information theory. Students with good mathematical and

analytical skills are preferred.

In information theory, many famous tools or results cannot be applied to countably infinite alphabets, e.g., strong

typicality, Fano’s inequality and one‐time pad. It is important to consider countably infinite alphabets because this is

the general case and this usually gives tighter bounds, faster convergent rates, etc. Recently, we have generalized the

aforementioned tools to countably infinite alphabets due to the observation that entropy is indeed a discontinuous

function. This project aims to generalize more fundamental results in information theory. Students with good

mathematical and analytical skills are preferred.

ITR: NETWORKS, TRANSMISSION AND CODING TOPICS

Adaptive streaming with delay‐constraints Dr Khoa Nguyen

Networks, transmission and coding topics Suitable as PhD project

Abstract: In streaming data over wireless channels with delay constraints, the instantaneous performance is subject

to fluctuations of system states such as the queuing traffic and channel realization. The streaming performance can be

improved by adapting the transmission rate with the instantaneous system states. The project can be divided in two

stages. The first stage focuses on designing and analysing a new coding scheme, namely rate‐varying code, that is

suitable for adaptive streaming. In the second stage, rate adaptation policy based jointly on the link layer traffic and

the physical layer performance will be developed.

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Big Data in Cloud Storage Associate Professor Terence Chan, Dr Siu Wai Ho


Abstract: In the era of Big Data, data storage systems storing massive amounts of data have become an indispensable

component of modern networks, cloud computing and network applications. In a distributed storage system (DSS),

data is stored across multiple data centres to increase reliability against faults and failures of any individual data

centre.

Traditionally, data is directly replicated and stored in each data centre. Despite its simplicity, this direct mirroring

approach requires a huge amount of storage capacity in each data centre. Motivated by network coding, the new

generation of distributed storage system will linearly encode the data before storing, resulting in a significant

reduction in the amount of storage needed in each data centre.

Practically, it is of critical importance that a DSS must be efficient, robust and secure. Data in DSS can be efficiently

updated and retrieved. Furthermore, we must ensure that any eavesdroppers should reveal no information about the

data stored in the data centre and that the system can still repair itself in case of failure even when there are

malicious adversaries tampering or jamming the network. However, the majority of existing work in DSS ignores these

efficiency, security and robustness issues. This project on the other hand aims to fill this gap by using an information‐

theoretic approach. We will focus on deriving fundamental limits as well as practical coding schemes that are efficient,

robust and secure.

Distributed control and tracking Dr Khoa Nguyen


Abstract: Classical closed‐loop control systems rely on having high‐capacity links between the sensors, controller and

actuators. Meeting this requirement is challenging in distributed systems, especially in controlling over wireless

channels. The communication requirements for distributed control, namely anytime transmission, were established by

Anant Sahai in 2001. However, current practical anytime codes only partially meet these requirements. This project

aims at investigating the impact of these limitations, and developing new communication and control strategies to

address these issues.

Fundamental Limits of LPD Communication Dr Nick Letzepis


In defence and national security, many situations arise where information must be conveyed in such a way that it

either cannot be reliably recovered, or is rendered undetectable by unauthorised entities. The former scenario is

referred to as secure communication – signal detection is tolerated, but its information content must be

undecipherable to all but the intended recipient. The latter scenario is referred to as low probability of detection

(LPD), or covert communication – the sender cannot even afford its signal to be detected, let alone its information

content be compromised. While over several decades LPD communication has received much attention in the

literature, most of this work has concentrated on solutions based on pragmatic/heuristic reasoning. Until recently,

very little work has been done regarding the fundamental limits of LPD communications, especially in the context of

modern advancements in wireless communication such as multi‐antenna/multi‐carrier communication, cognitive

radio and software defined radio. Toward this end, this research project aims to:

Formulate a generic information theoretic framework applicable to any channel, e.g. AWGN, binary symmetric, binary erasure, multi‐carrier, multi‐antenna channels.

Understand the trade‐offs between key design parameters, e.g. signal‐to‐noise ratio, local interference, probability of transmission (burst signalling), decoding error probability and detection probability.

Note that this project will require close collaboration with the Defence Science and Technology (DST) Group,

Edinburgh, South Australia. As such, it is required that potential candidates are Australian citizens to be eligible for

appropriate security clearances.

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Information theoretic security for networks Associate Professor Terence Chan


Abstract: Security is an extremely important aspect in modern information technological infrastructure. Any security

breaches to the system can have disastrous consequences, causing significant financial losses and long‐lasting

damages. Therefore, it is of critical importance that data must be stored and transmitted robustly and securely in the

networks, against any eavesdropping or tampering by malicious adversaries. Network coding opens the door to many

interesting possibilities for information security. The use of multiple transmission paths may increase robustness to

denial of service or jamming attacks. It can also provide security against eavesdroppers. This project explores some of

the security implications and advantages of network coding.

Network coding for multimedia multicast Associate Professor Terence Chan


Abstract: Network coding is a recent breakthrough in telecommunications network research. Some attractive

features of network coding include the efficient use of network resources, higher data throughput rates and increased

robustness against network errors. Network coding is particularly effective in multicast scenarios, where many users

require the same data from a single source. For example, consider streaming multimedia data over the internet from a

single source to multiple users. Investigate the application of network coding principles to the transmission of

multimedia data in telecommunication networks. Of particular interest are situations where users require multimedia

data at different fidelity/resolution levels. For example, some users may require high‐quality video for high‐resolution

displays, while other users will require low‐fidelity video for small mobile devices. The main purpose is to devise

schemes for efficiently transporting multimedia data from a single source to many users with different fidelity

requirements.

ITR: SOFTWARE DEFINED RADIO ITR is an institutional member of the International Wireless Innovation Forum, an industry, government and academic

forum pushing the technical boundaries and application of SDR and cognitive radio technologies. ITR hosts several SDR

systems and development environments for prototyping, demonstration, hardware‐in‐the‐loop testing and real‐time

channel and performance measurements. Research in SDR is focused on design methodologies, architectural aspects

and reliability. A number of postgraduate research topics are available in this project.

Distributed beamforming with SDRs Associate Professor Gottfried Lechner

Software defined radio Suitable as PhD project

Abstract: Modern communication systems often include software defined radios (SDRs). SDRs not only allow

flexibility in the selection and modification of communication standards but also open new possibilities. One aspect is

cooperative communications where multiple radio cooperate in either receiving or transmitting a signal from/to a

remove host.

Critical aspects are the protocol between the radio and the remote host and synchronisation between the radios. The

project requires knowledge in signal processing and communications as well as good knowledge of programming

languages such as C++.

ITR: WAVEFORMS AND ALGORITHMS This research will provide Australia with an improved capacity to collect information vital for industry, defence, the

environment and national security. Funded by the Australian Space Research Program, with a consortium that includes

national and international partners, the project will scope and test the use of Low Earth Orbit (LEO) satellites in

providing two‐way data communications to remote sensors and devices.

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High speed satellite downlinks Associate Professor Gottfried Lechner

Waveforms and algorithms Suitable as PhD project

Abstract: Future earth‐observation satellites require gigabit transmission rates in higher frequency bands. Limitations

in radio frequency spectrum call for spectrally‐efficient modulation schemes, which make gigabit data rates

particularly challenging.

In this project we will design a next‐generation transmission scheme for future Ka‐ Band gigabit satellite downlinks,

including novel approaches for dealing with channel effects such as group delay, ripple and non‐linear satellite power

amplifiers.

Available PhD and Masters projects include high‐speed signal processing and coding architectures, plus real‐time

signal synthesis and acquisition to allow realistic performance testing and optimisation with satellite hardware.

Second Generation Search and Rescue Associate Professor Gottfried Lechner

Waveforms and algorithms Suitable as PhD project

Abstract: The satellite‐based Cospas‐Sarsat search and rescue system has assisted with the emergency rescue of

more than 35,000 lives worldwide since introduction in 1982.

A second generation of this system is currently under development, promising to significantly improve detection rate

and localisation accuracy. However, in an emergency, the system’s performance is often compromised due to

interference and atmospheric effects, leading to false detections that waste valuable resources.

Projects in this area aim to provide novel techniques leading to faster, more reliable, more accurate, and more cost‐

effective search and rescue operations using techniques like multi‐user detection, beamforming and advanced signal

processing algorithms.

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PART IV: Phenomics and BIOINFORMATICS Research Centre (PBRC) Page

Controlled drug delivery with multi‐layered tablets 40

Controlling Nanopatterns from Polymer Brushes 40

Creating Nanopatters by dewetting polymer brushes 40

Mathematical models for microelectromechanical machines 41

Mathematical signal processing for distributed systems 41

Modelling of salt and water transport in plants 41

Modelling of surface forces in ionic liquids 42

Modelling of fluid and solute transport in non‐uniform, periodic capillaries 42

Modelling Co‐variations in 3D Shapes 42

RGBD camera‐based 3D modelling of plants 43

Sequential data analysis by integrating hidden Markov modelling with domain knowledge 43

Statistical Shape Analysis of 3D Objects Using Riemannian Elastic Metrics 43

Thin Films from Ionic Liquids 44

Controlled drug delivery with multi‐layered tablets Dr Bronwyn Hajek

Partial differential equations Suitable as an honours project

Abstract: In order to control the effects of many illnesses, the steady release of a drug into the body is necessary.

However, a drug (in tablet form) is usually only administered a few times per day, with each dosage leading to a

dramatic increase in the drug concentration within the body, followed by a slow decrease as the drug is metabolised.

Fortunately, it is now possible to manufacture layered tablets, with the drug concentration and release rate varying

between the layers. This results in a more steady release of the drug into the system, and maintains it at a more

constant concentration within the body. In this project, we will tackle this problem from two directions. First, we will

calculate the rate of drug delivery assuming that we know the concentration of the drug within each layer and also the

rate at which each layer dissolves. Second, we tackle the more difficult inverse problem: if the required drug delivery

rate is known, how could you construct a tablet with a finite number of layers that would closely replicate the

necessary delivery rate.

Controlling Nanopatterns from Polymer Brushes. Dr Marta Krasowska, Dr Bronwyn Hajek

Advanced Materials, Applied Mathematics Suitable as Honours, MSc or PhD project

Abstract: Nanopatterned polymer surfaces are important for applications with controlled mechanical properties.

Polymer brushes grafted onto a solid substrate can, depending on polymer interaction with the solvent, either stay

extended or collapse. By controlling the nature of the solvent as well as its amount, we can control the patterns

formed by polymer brushes, and the hence mechanical properties of such layers.

The properties of polymer layers grafted on a solid surface will be studied using atomic force microscopy (AFM). AFM

is a powerful characterization tool for materials science, capable of revealing surface structures with superior spatial

resolution (nanometer scale) as well as mechanical properties (softness, adhesion, deformation) of such surfaces.

References:

1. T. Lee, S.C. Hendy, C. Neto, Tunable nanopatterns via the constrained dewetting of polymer brushes,

Macromolecules, 2013, 46 (15), pp 6326‐6335

Creating nanopatters by dewetting polymer brushes Dr Bronwyn Hajek, Dr Marta Krasowska

Partial differential equations Suitable as an honours project

Abstract: Polymer brushes are polymer chains that have been grafted by one end on to a solid substrate. In the

presence of a solvent, the polymer chains are stretched away from the substrate, however, if the solvent surrounding

polymer brushes dries out, the polymer brushes collapse onto the substrate in a compact layer. Molecular dynamics

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simulations have shown that as the brushes collapse, they can form nanopatterns on the substrate, with the type of

pattern depending on the grafting density and the amount of solvent. In this project, we will test the robustness of

these conclusions using partial differential equations, in much the same way as Murray describes the patterning on

mammalian coats (eg leopards and zebras).

References:

1. T Lee, SC Hendy, C Neto, Tunable nanopatterns via the constrained dewetting of polymer brushes,

Macromolecules, 2013, 46(15):6326‐6335

2. JD Murray, Mathematical Biology II: Spatial Models and Biomedical Applications, Springer‐Verlag, Berlin, 2003

Mathematical models for microelectromechanical machines Dr Bronwyn Hajek, Professor Jim Hill, Dr Marta Krasowska, Associate Professor David Beattie

Applied math modelling, Physical Chemistry Suitable as PhD project

Abstract: Microelectromechanical machines are increasingly being used as sensors and actuators. At present, their

performance is limited due to issues with contamination and friction. In this project, we will develop a mathematical

model to investigate the mechanisms which govern the interactions in these devices. In particular, we will model the

surface forces within these devices and investigate the use of liquid lubricants, combined with specially designed

coatings.

Mathematical signal processing for distributed systems Associate Professor Anatoli Torokhti, Professor Stanley J. Miklavcic

Signal Processing, Computational Mathematics Suitable as PhD and Masters project

Abstract: This project will investigate effective numerical algorithms for an information processing scenario that

involves a set of spatially distributed sensors and a fusion center. The sensors make local observations which are noisy

versions of a signal of interest. Each sensor transmits compressed information about its measurements to the fusion

center which should recover the original signal within a prescribed accuracy. Such an information processing relates to

a wireless sensor network (WSN) scenario. In the recent years, research and development on new and refined WSN

techniques has increased at a remarkable rate.

Particular research areas include, but not limited to:

Data compression techniques

Signal reconstruction from noisy data

Matrix approximation

Modelling of non‐linear systems

Extensions of Principal Component Analysis

References:

1. A.Torokhti and P. Howlett, Computational Methods for Modelling of Nonlinear Systems, Elsevier, 397 p.,

2007.

2. A. Grant, A. Torokhti, S.J. Miklavcic (2014) “Efficient compression of distributed information in estimation

fusion”, Electronic Notes of Discrete Mathematics, 46, pp297‐304.

3. A. Torokhti, S.J. Miklavcic, P. Soto‐Quiros (2016) “Distributed systems: identification, optimization and

simulations”, International Journal of Electronics and Electrical Engineering, 4(4), pp322‐327.

Modelling of salt and water transport in plants Professor Stanley Miklavcic

Applied mathematics/mathematical modelling Suitable as PhD project

Abstract: Abiotic stresses such as high salt levels in soils can severely affect cereal crop health, development and grain

yield. Currently, high salinity affects two‐thirds of Australian cereal crops. To increase plant salinity tolerance it is

necessary to manipulate the transport of ions (e.g., sodium and chloride) through a plant. However, this requires

knowledge about how ion transport through a plant occurs. In particular, it is necessary to identify the key points in

this transport pathway to target in order to generate a salt‐tolerant cereal variety. For example, is targeting the initial

influx of ions from the soil the best method for increasing plant salinity tolerance, or should more effort be directed

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towards increasing the compartmentalization of ions in the shoot? None of the existing models of water and solute

transport in plants are currently suitable for analysing the transport of ions. This project aims to develop detailed

mathematical models of water and solute transport through plant organs and tissues, which will be compared with

physiological measurements of fluxes and accumulated ion concentrations. The overall aim is to aid understanding of

the biophysical mechanisms and processes responsible for increasing plant salinity tolerance. It is envisioned that the

results will help guide plant geneticists and plant breeders in their search for specific genetic traits that enhance a

plant's ability to tolerate salinity.

References:

1. K. Foster and S.J. Miklavcic. “Mathematical modelling of the uptake and transport of salt in plant roots”, J. Theoretical Biology, 336, pp132-143.

2. K. Foster and S.J. Miklavcic. “On the competitive uptake and transport of ions through differentiated root tissues”, J. Theoretical Biology, 340, pp1-10.

3. K. Foster and S.J. Miklavcic. “Toward a biophysical understanding of the salt stress response of individual plant cells”, J. Theoretical Biology, 385, pp130-142.

Modelling of surface forces in ionic liquids Professor Stanley Miklavcic, Dr Jason Connor


Abstract: Ionic liquids or molten salts are very highly concentrated salts in a fluid state. Such systems feature

prominantly in many chemical industry processes. However, their behavior has not been completely nor adequately

quantified. In particular, how ionic liquids influence the interaction between macroscopic surfaces is not known, with

conflicting experimental studies confusing the picture. This is a theoretical project aimed at developing a

mathematical model to describe the forces between macroscopic surfaces in the presence of an intervening ionic

liquid. The project involves the application of advanced statistical mechanical models to help understand how ionic

liquids influence the forces. We shall compare the results with published data as well as new in‐house surface force

measurements.

Modelling of fluid and solute transport in non‐uniform, periodic capillaries Professor Stanley Miklavcic, Dr Bronwyn Hajek


Abstract: The flow of fluids and transport of suspending particles in capillaries has attracted a lot of experimental and

theoretical interest in recent years. The interest is partly inspired by the potential for commercial exploitation in the

area of microfluidics and nanofluidics applications in chemical and pharmaceutical industries. However, inspiration

also comes from a desire to understand a range of natural phenomena, such as arise in plants. We have an interest in

extending our recent efforts to model fluid flow and particle transport in periodic tubes to more general tube

conditions, on the one hand, and considering more detailed (perturbation or asymptotic) analyses in simpler cases, on

the other.

References:

1. N. Islam, B. Bradshaw‐Hajek, S.J. Miklavcic, L.R. White (2015) “The onset of recirculation flow in periodic

capillaries: geometric effects”, European Journal of Mechanics ‐ B/Fluids, 53, pp119‐128.

2. N. Islam, S.J. Miklavcic, B. Bradshaw‐Hajek, L.R. White (2016) “Convective and diffusive effects on particle

transport in asymmetric periodic capillaries”, Physical Review E (submitted).

Modelling Co‐variations in 3D Shapes Dr Hamid Laga and Professor Stanley Miklavcic

Computer vision and computer graphics Suitable as PhD project

Abstract: This project aims at developing statistical models that capture the co‐variations in shape and structure of 3D

anatomical objects. Objects in nature do not behave in isolation but interact with their neighbours. Changes in the

shape of an object, e.g. erosion of a bone in a human hand, affects not only the shape of the neighbouring bones but

also the entire structure and configuration of the bones that compose the hand, which may result in the alteration of

their functionality. Previous works on statistical shape analysis focused on modelling the shape of individual objects in

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isolation. This project aims at developing statistical models that capture the way 3D objects, particularly anatomical

ones such as human organs or plants, interact with each other and the way variations in the shape of individual

objects affect the structure and configuration of the entire system.

References:

1. Sebastian Kurtek, Anuj Srivastava, Eric Klassen, and Hamid Laga. “Landmark‐Guided Elastic Shape Analysis of

Spherically‐Parameterized Surfaces”. Computer Graphics Forum (Proceedings of Eurographics 2013). 32(2), pp.

429‐438, 2013.

2. Hamid Laga, Michela Mortara and Michela Spagnuolo. “Geometry and Context for Semantic Correspondences and

Functionality Recognition in Manmade 3D Shapes. ACM Transactions on Graphics, 32(5), 2013.

RGBD camera‐based 3D modelling of plants Dr Hamid Laga, Dr Jinhai Cai, Professor Stanley Miklavcic

Image processing, computer vision, image‐based plant phenotyping Suitable as PhD project

Abstract: The purpose of this project is to build virtual 3D models of plants from data acquired with a combination of

RGB and depth sensors such as Kinect. 3D models of plants play important roles not only for entertainment and games

but also for plant biology, where an accurately reconstructed 3D model can be used to estimate the plant’s biomass,

analyze its growth patterns and predict yield.

Sequential data analysis by integrating hidden Markov modelling with domain knowledge Dr Jinhai Cai, Professor Stanley Miklavcic, Dr Hamid Laga

Image processing, computer vision and machine learning Suitable as PhD project

Abstract: Hidden Markov Models (HMMs) are statistical models of sequential data that have been used successfully in

many applications in artificial intelligence, pattern recognition and modelling of gene sequences. This project aims at

developing new statistics modelling approach to integrate conventional HMMs with experts’ prior knowledge (domain

knowledge) to improve the capacity and the accuracy of the HMMs.

Previous works on HMMs focus on how to capture the statistic information from the sequential data and the

relationships between events in time sequences. In this approach, we will develop new structure for HMMs, likely the

multilayered and coupled structure, to represent domain knowledge, structure information as well statistic

information into individual models. The developed novel HMMs will be applied to biology and health science.

References:

1. J. Cai and Z.Q. Liu, “Integration of structural and statistical information for unconstrained handwritten numeral

recognition,” Pattern Analysis and Machine Intelligence, IEEE Transactions on 21 (3), 263‐270.

2. J. Cai and Z.Q. Liu, “Pattern recognition using Markov random field models”, Pattern Recognition 35 (3), 725‐733,

2002.

3. J. Cai, D. Ee, R. Smith, “Image Retrieval Using Circular Hidden Markov Models with a Garbage State”, IVCNZ 2007,

115‐120.

4. J. Cai, “Enhanced HMM for the Recognition of Sigma70 Promoters in Escherichia coli”, Digital Image Computing:

Techniques and Applications (DICTA), 2008, 46‐51.

Statistical Shape Analysis of 3D Objects Using Riemannian Elastic Metrics Dr Hamid Laga

Computer vision and computer graphics Suitable as PhD project

Abstract: Shape is an important characteristic of natural as well as man‐made objects. Quantifying similarities and

differences between shapes, referred to as shape analysis, is a fundamental problem and a building block to many

applications. In biology, evolutionary relationships among living and extinct species are discovered through the

analysis of their morphological traits. To understand ontogenetic development, speciation, or evolutionary

adaptation, it is important to quantify the similarity or dissimilarity of objects affected or produced by the phenomena

under study. In medical imaging, studying shapes of anatomical structures in the brain and comparing their evolution

to typical growth patterns are of particular interest because many diseases can be linked to alterations of these

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shapes. Shape analysis problems appear also in many other branches of science, including computer graphics,

computer vision, biometrics, bioinformatics, geology, and anthropology.

Previous studies on shape analysis have often focused on quantifying the similarity between a pair of shapes. In many

situations however one would like to compare collections of shapes. For example, botanists collect several samples of

plant leaves that belong to various species. To study similarities (and differences) between two plant species, it is

important to develop a mathematical tool that is able to compare the population of plant leaves that belong to the

two species.

Recent developments in statistical shape analysis [1, 2, 4] are opening unprecedented possibilities for investigating

tools for characterizing shape populations with probability distributions. The purpose of this project is to develop,

implement, and evaluate algorithms for analyzing 3D shape populations using elastic metrics defined on Riemannian

manifolds and which have bee recently developed by the supervisor and collaborators [1, 2, 3, 4].

References:

1. Sebastian Kurtek, Anuj Srivastava, Eric Klassen, and Hamid Laga. “Landmark‐Guided Elastic Shape Analysis of

Spherically‐Parameterized Surfaces”. Computer Graphics Forum (Proceedings of Eurographics 2013). 32(2), pp.

429‐438, 2013.

2. Hamid Laga, Sebastian Kurtek, Anuj Srivastava, Stanley J. Miklavcic. Statistical Shape Models of Plant Leaves.

International Conference on Image Processing (ICIP) 2013.

3. Hamid Laga, Sebastian Kurtek, Anuj Srivastava, Mahmood Golzarian, and Stanley J. Miklavcic. A Riemannian

Elastic Metric for Shape‐based Plant Leaf Classification. IEEE International Conference on Digital Image Computing

(DICTA), pp. 1‐7, 2012.

4. Anuj Srivastava, Eric Klassen, Shantanu H. Joshi, and Ian H. Jermyn. Shape Analysis of Elastic Curves in Euclidean

Spaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 33, issue 7, pages 1415‐1428, July

2011.

Thin Films from Ionic Liquids Dr Marta Krasowska, Dr Bronwyn Hajek, Associate Professor David Beattie

Advanced Materials, Applied Mathematics Suitable as Honours, MSc or PhD project

Abstract: When a liquid drop contacts a solid surface a thin film can spread ahead of the bulk liquid at the three

phase contact line region. These films are referred to as precursor films. They are formed when intermolecular forces

of attraction between solid and liquid are strong enough to induce spontaneous spreading. Spreading patterns in such

films are influenced by the nature of the liquid (e.g. its volatility) and the solid.

The morphology and extent of precursor films formed by ionic liquids will be studied by atomic force microscopy

(AFM), while elemental surface analysis will be probed with X‐ray photoelectron spectroscopy (XPS).

References:

1. D. A. Beattie, R. M. Espinosa‐Marzal, T. T. M. Ho, M. N. Popescu, J. Ralston, C. J. E. Richard, P. M. F. Sellapperumage,

M. Krasowska, Molecularly‐Thin Precursor Films of Imidazolium‐Based Ionic Liquids on Mica, J. Phys. Chem. C, 2013,

117 (45), pp 23676–23684

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Alphabetical List of Projects 360 Degree Cameras: Image Analysis Algorithms 11 A New Projector Based Augmented Reality Precise CAD‐Like Manipulations 22 Adaptive Free‐Space Optical Communications 34 Adaptive streaming with delay‐constraints 36 Agile Model‐Driven Visualisation of Big Data 12 Analytical methods for detection of social media manipulation 4 Anti‐Mobile Malware, Mobile Security Including Money Honeypot, VoIP Security and Interception, Critical Information Infrastructure Protection, Anti‐Phishing/Spam, Cryptographic Protocols and Information Security Risk Management Framework and Standards 17 Applied mathematical modelling in nanotechnology 29 Approximation of Convex Sets 29 Augmented Reality Intelligent Tutoring Systems 22 Augmented Reality Teleconferencing 23 Automatic labelling of tweets in civil unrest prediction 4 Big Data in Cloud Storage 37 Bio‐inspired machine learning and intelligence 34 Business Process Management for the Internet of Things 12 Cloud privacy enhancing and/or cryptography 18 Cloud security 18 Coding and Signal Processing For Future Fibre‐Optical Communications 34 Co‐Evolution of Linked Lexical Resources 13 Collaborative Web search (social search) 18 Computer vision applications with unmanned vehicles 4 Configuration of Software Product Lines 13 Connecting to knowledge: Accessing information via the Internet by Indigenous communities 19 Content distribution using index coding and caching 35 Controlled drug delivery with multi‐layered tablets 40 Controlling Nanopatterns from Polymer Brushes 40 Creating Nanopatters by dewetting polymer brushes 40 Darknet monitoring and/or analytics 19 Deep Neural Networks for Anomaly Detection and Decision Making in Personal Budgeting 11 Deep neural networks for human emotion recognition 24 Deep Neural Networks for Image Understanding 11 Deformable User Interfaces 24 Developing novel data mining techniques for mining educational data 5 Disaggregation of Wearable Computation Devices 24 Discovery and use of Twitter network structural features for civil unrest prediction 5 Distributed beamforming with SDRs 38 Distributed control and tracking 37 Effective time series feature selection for civil unrest prediction using social media data 5 Efficient Causal Inference in Big Data 6 Empathic Conferencing 25 Evolving Knowledge Bases automatically through Natural Language Understanding 13 Face to Face Collaboration Using Hololens 25 Forensic Visualisation, Cloud Forensics, Big Data Forensics, Mobile and Anti‐Mobile Forensics, Hard Disk Forensics, Multimedia Forensics, and Digital Forensic and Incident Response Standards 19 Fundamental Limits of LPD Communication 37 Gaze based remote conferencing 25 Geometry and geometric issues of atomic nanostructures 30 Graphene production, and graphene folding and bubbling 30 Harmonic Analysis: Developing the theory of function spaces on spaces of homogeneous type 30 High speed satellite downlinks 39 Hybrid Approaches to Natural Language Understanding: Integrating (DEEP) Machine Learning with Knowledge 14 Identifying cancer subtypes from multi‐levelled biological data with computational methods 6 Immigrant youth and children 20 Implied Comparative Advantage of Australian Economic Complexity 7 Information Management and Governance 20 Information theoretic security and privacy 36 Information theoretic security for networks 38 Integrated Policing: Generating queries for identity resolution 7 Integrated Policing: Model relationships from text data for identity resolution 7 Integrated Prediction with Multiple Data Sources and Credibility Assessment 8 Integration and visualisation of multiple civil unrest prediction models 8 Internet of Things Security and Privacy 21 Interpretable classification and prediction of civil unrest events 8 Investigating genetic causes of cancer through complex gene regulatory networks 9 Knowledge management in genomics 14 Mathematical models for microelectromechanical machines 41 Mathematical signal processing for distributed systems 41 MIMO and modulations in visible light communications 35 Mobile app vulnerability detection and exploitation 21 Modelling Co‐variations in 3D Shapes 42

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Modelling methane storage using nano‐bottles 31 Modelling of fluid and solute transport in non‐uniform, periodic capillaries 42 Modelling of salt and water transport in plants 41 Modelling of surface forces in ionic liquids 42 Multimedia Systems (2D and 3D video coding and video streaming, robotics vision, cloud‐based video services, panoramic video analysis, video surveillance and monitoring, multimedia data mining, multimedia sensor networks, medical imaging) 9 Nanoscaled oscillating systems 31 Natural Language Understanding for Automated Understanding of Software Requirements 15 Network coding for multimedia multicast 38 Online multitasking (Mobile multitasking) 21 Ontology‐based Information Ecosystems 15 Partial rate region characterisations: new frontiers of information theory 36 Patient journey/clinical events analysis 16 Positioning by visible light communications 35 Precursor Pattern Analysis and Interpretable Classification 10 Prediction of civil unrest events with news and other data sources 10 Processes and workflows in clinical genomics 16 Refinement of fundamental tools in information theory 36 RGBD camera‐based 3D modelling of plants 43 Second Generation Search and Rescue 39 Semantic Interoperability for Big Data 16 Sequential data analysis by integrating hidden Markov modelling with domain knowledge 43 Signal processing and analysis for medical imaging 10 Spatial Augmented Reality Design Tools 26 Statistical Shape Analysis of 3D Objects Using Riemannian Elastic Metrics 43 Storytelling of Big Data 26 Symmetry methods for nonlinear partial differential equations 32 Thin Films from Ionic Liquids 44 User interaction for interactive constraints and spatial augmented reality 27 Virtual Reality Brain Training Tools 27 Visualising and Interacting with Large Graphs of Big Data 27

Index to Projects by Academic ASHMAN, Helen p 4 BEATTIE, David pp 41, 44 BILLINGHURST, Mark pp22, 23, 24, 25 BOHN, Dave p 11 CAI, Jinhai p 43 CHAN, Terence pp 34, 37, 38 CHEANG, Gerald p 29 CHEN, Jie pp 8, 10 CHIERA, Belinda p 11 CHOO, Raymond p 17, 18, 19, 21 CONNOR, Jason p 42 COWLEY, Bill p 34 DU, Tina pp 18, 19, 20, 21 GAO, Jing p 20 GROSSMANN, Georg p 12, 15, 17 HAJEK, Bronwyn pp 32, 40, 41, 42, 44

HILL, Jim pp 29, 30, 31, 32, 41 HO, Siu Wai pp 35, 36, 37 KANG, Wei pp 4, 8 KEARNEY, David p 11 KORONIOS, Andy p 20 KRASOWSKA, Marta pp 40, 41, 44 LAGA, Hamid pp 42, 43 LE, Thuc pp 6, 9 LECHNER, Gottfried pp 35, 38, 39 LEE, Ivan pp 4, 7, 9, 10 LETZEPIS, Nick p 37 LI, Jiuyong pp 4, 5, 6, 8, 9, 10 LIU, Jixue p 7 LIU, Lin pp 5, 8, 10 MAYER, Wolfgang pp 13, 14, 15, 17, 27 McDONNELL, Mark pp 24, 34

MIKLAVCIC, Stan pp 41, 42, 43 NGUYEN, Khoa pp 36, 37 SELWAY, Matt pp 13, 14, 15 SMITH, Ross pp 24, 27 STAMATESCU, Victor p 11 STANEK, Jan pp 14, 16 STUMPTNER, Markus pp 12, 13, 14, 15, 17 SWAIT, Joffre p 11 THOMAS, Bruce pp 22, 24, 26, 27 TOROKHTI, Anatoli p 41 WARD, Lesley p 30 WONG, Sebastien p 11 YU, Kui p 6

Vacation Research Scholarships

If you are in your second, third or honours year and have a strong academic record, a Vacation Research Scholarship

may be for you. Students from other universities are welcome to apply. These scholarships give you the opportunity to

earn $300 a week undertaking research for up to 8 weeks with experienced researchers, usually between November

and February.

Projects listed in this booklet can be adapted to suit Vacation Scholarships.

Documents

School of Information Technology and Mathematical … ITMS Project Book...School of Information Technology and Mathematical Sciences Research Project Booklet 2016/2017 The School of