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This work is sponsored by the Air Force under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the United States Government. SuperUROP Projects “Wireless Anomalies Have No Place to Hide” Faculty Advisor: Mentor(s): W. Mark Smith, PhD Contact e-mail: [email protected] Research Area(s): Cyber Systems and Operations UROP researchers will investigate incorporating transactions in wireless protocols into anomaly detection and response systems. Research topics will include monitoring at the RF layer to complement existing anomaly detectors at the network layer, monitoring and computing resources needed to identify and track anomalous behavior, and responses at the RF layer when anomalies are identified. Given an understanding of anomalous wireless activity, the researcher will develop realistic wireless mobile user application models and incorporate them into an existing emulation infrastructure exercising all layers of the protocol stack. “HLT-Based Advanced Analytics” Faculty Advisor: Mentor(s): William Campbell, PhD Contact e-mail: [email protected] Research Area(s): Human Language Technology UROP researchers work with teams in the Human Language Technology Group to research and develop algorithms for analyzing large collections of speech and text. The effort may include the extraction and analysis of semantic content (names, topics, etc.), social networks, and geo-spatial information. Processing may also include multi-lingual data requiring machine translation. Possible UROP projects include social network analysis, data visualization, and information retrieval based on semantic knowledge. This role involves programming, using machine learning methods, applying text and speech processing algorithms, and presenting results to a technical audience. The work is expected to be challenging, interesting, and involve real data. “Finding Needles in Needlestacks” Faculty Advisor: Mentor(s): Steve Smith, Frederick Waugh Contact e-mail: [email protected], [email protected] Research Area(s): Computing and Analytics

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Page 1: 2017-04-14 LincolnLab SuperUROP Projects Version 1...and assessing cyber systems, including red teaming, system exploitation, building cyber range infrastructure, and conducting tests

ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.

SuperUROPProjects

“WirelessAnomaliesHaveNoPlacetoHide”

FacultyAdvisor:

Mentor(s):W.MarkSmith,PhD

Contacte-mail:[email protected]

ResearchArea(s):CyberSystemsandOperations

UROPresearcherswillinvestigateincorporatingtransactionsinwirelessprotocolsintoanomalydetectionandresponsesystems.ResearchtopicswillincludemonitoringattheRFlayertocomplementexistinganomalydetectorsatthenetworklayer,monitoringandcomputingresourcesneededtoidentifyandtrackanomalousbehavior,andresponsesattheRFlayerwhenanomaliesareidentified.Givenanunderstandingofanomalouswirelessactivity,theresearcherwilldeveloprealisticwirelessmobileuserapplicationmodelsandincorporatethemintoanexistingemulationinfrastructureexercisingalllayersoftheprotocolstack.

“HLT-BasedAdvancedAnalytics”

FacultyAdvisor:

Mentor(s):WilliamCampbell,PhD

Contacte-mail:[email protected]

ResearchArea(s):HumanLanguageTechnology

UROPresearchersworkwithteamsintheHumanLanguageTechnologyGrouptoresearchanddevelopalgorithmsforanalyzinglargecollectionsofspeechandtext.Theeffortmayincludetheextractionandanalysisofsemanticcontent(names,topics,etc.),socialnetworks,andgeo-spatialinformation.Processingmayalsoincludemulti-lingualdatarequiringmachinetranslation.PossibleUROPprojectsincludesocialnetworkanalysis,datavisualization,andinformationretrievalbasedonsemanticknowledge.Thisroleinvolvesprogramming,usingmachinelearningmethods,applyingtextandspeechprocessingalgorithms,andpresentingresultstoatechnicalaudience.Theworkisexpectedtobechallenging,interesting,andinvolverealdata.

“FindingNeedlesinNeedlestacks”

FacultyAdvisor:

Mentor(s):SteveSmith,FrederickWaugh

Contacte-mail:[email protected],[email protected]

ResearchArea(s):ComputingandAnalytics

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UROPresearcherswilltakepartinstate-of-the-artresearchintherapidlyevolvingfieldofdataanalytics.Thisresearchinvolvesdevisingnovelapproachesforingestionandenrichmentofhigh-velocity,high-volumedata,developingnewinformation-theoreticanalyticapproaches,andapplyingrecentinnovationsinmachinelearningandvisualanalyticstohuman-machineintegration.Toolsdevelopedduringthecourseofthisresearchwillbeappliedtoavarietyofdatasources,includingsocialmediaandgeo-taggedeventdata.

“SecuringOurCyberFuture”

FacultyAdvisor:

Mentor(s):HamedOkhravi,RogerKhazan,KyleIngols

Contacte-mail:[email protected],[email protected],[email protected]

ResearchArea(s):SecureResilientSystemsandTechnology

UROPresearchersintheCyberSystemsandTechnologyGroupwillworkonassessingandimprovingthesecurityofU.S.governmentsystems.Researcherswillbementoredbyworld-classcybersecurityexpertsandhavetheopportunitytostudy,develop,andprototypeinnovativecybersecuritytechnologies.

ResearchersjoinR&Dteamsincyberscienceandanalysis,resilientcyberarchitectures,orsecureembeddedplatforms.Pastprojectsincludecybersensorsandanalytics,secureclouds,appliedcryptographyandkeymanagementsolutions,cyberdecisionsupporttools,andsecureembeddedprocessors.UROPresearchersareencouragedtoparticipatefullyinthegroup’sactivitiesandattendavarietyofseminars.

“Assessingthecyber-vulnerabilitiesofwirelesspower”

FacultyAdvisor:

Mentor(s):KevinB.Bush

Contacte-mail:[email protected]

ResearchArea(s):CyberSystemsandOperations

Technologyforshort-rangewirelesspowertransmissionispoisedtorevolutionizethewaywechargeconsumerelectronicsanddefensesystems.However,itremainsunknownwhatcyber-risksthistechnologypresentstothehostsystemsitpowers.Iswirelesspowerfundamentallymoresusceptibletodenialofservice(DoS)thantraditionalmeans?Canwirelesspowersignalsberemotelyandmaliciouslyalteredtocausepermanentphysicaldamage?Whatnovelcyberattack-vectorsdowirelesspowersystemspresenttothesystemstheycharge?Thisprojectseekstoanswerthosequestionsandmorebyidentifyingcyberweaknessandprofilingwirelesspowerstandards,characterizingthefundamentalcyber-securityvulnerabilitiesofwirelesspowertransmission,anddemonstratingacyber-attackagainstarealwirelesspowerplatform.

Engagedinawiderangeofcybersecurity-relatedactivities,theCyber

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SystemAssessmentsGroupisfocusedonanalyzing,understanding,andassessingcybersystems,includingredteaming,systemexploitation,buildingcyberrangeinfrastructure,andconductingtestsandevaluationsofcybercapabilities.

UROPresearcherswillworkwithateamtosupportoneoffourprojectareas:1)thetestandevaluation(T&E)ofnationalcybercapabilitiesandsystems,includingthedevelopmentofnewtestmethodologiesandmetricsforevaluation;2)thedevelopmentofnewtechnologiesandinfrastructurefor“cyberranges,”whicharelarge,isolatednetworkandphysicalenvironmentsinwhichpotentiallydisruptivecybercapabilitiescanbesafelyexplored;3)thereverseengineeringandexploitationofsoftwareandembeddedsystems;and4)theredteamingandvulnerabilityassessmentofcybersystems.

“Low-FrequencyAntennaDesignforSmallUAVFoliagePenetratingRadar”

FacultyAdvisor:TBD

LincolnMentor(s):JasonFranz,PamelaEvans

Contacte-mail:[email protected],[email protected]

ResearchArea:Electromagnetics/Antennas

UROPresearcherswilldevelopandevaluatedesignsforlow-frequencyantennassuitableforasmallfoliage-penetratingsyntheticapertureradar(SAR)system.Theentireradarsystem,includingfourantennastosupportadaptivebeamforming,needstofitwithintwopodsmountedtoasmallUnmannedAirVehicle(UAV)platform.Eachpodprovidesonly2-3ftoflengthtoaccommodatetheantennas,transmitandreceivehardware,andon-boardprocessor.TheantennasneedtooperateintheUHFradarbandfrom250-450MHz,wheretheelectromagneticsignalscanpenetratefoliatedareastoimageobjectsbelow.Akeydesignchallengewillbetoimpedancematchtheantennasoverthisbandwidthandmaintainpatternandgainwhilefittingtheantennasintoasmallformfactor,withincloseproximityoftheotherradarhardware.TheUROPresearchersmayevaluatetheabilitytosupportduallinearpolarizationversusasinglelinearpolarization,andmayinvestigatedesignsthatutilizeactivetuningacrosstheUHFbandtosupportastepped-frequencywaveform.Theprojectwillrequireantennadesignandmodeling,antennafabricationandtuning,andpattern/gainmeasurementsinananechoicchamber.FacilitiesatMITLincolnLaboratorymaybeutilizedtosupportthefabricationandmeasurementwork.

“AnalysisandDesignofObjectTaggingSystems”

FacultyAdvisor:

LincolnMentor(s):JanetHallett

Contacte-mail:[email protected]

ResearchArea:SmallSensorTechnologies

UROPresearcherswillperformanassessmentofsmallform-factortagsthatcanbeusedtodetect,locateandtrackmovinggroundobjectsofinterestfromlongphysicalranges.Differentsensormodalitiesshouldbeconsideredintheassessment.Strawmandesigns

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willbedevelopedtoincludeboththetagandtheread-outsystem,andpotentialperformancewillbepredictedthroughphysics-basedmodeling.Keyperformancemetricswillincludetagdetectionrange,tagformfactor,tagsignalpersistence,andoveralltaglifetime.TheUROPresearchermayalsobuildhardwareforoneormorepromisingtagconcepts,andperformproof-of-conceptmeasurementstovalidatemodeledresults.

“Soft-coreMicroprocessorInfrastructureforaGraphProcessingCluster”

FacultyAdvisor:TBD

LincolnMentor(s):VitaliyGleyzer,WilliamSong

Contacte-mail:[email protected],[email protected]

ResearchArea:AdvancedGraphProcessorArchitecture

Theprojectinvolvesdevelopingcomponentsofthenovelhigh-performancegraphprocessorthatwillbeabletoperformstate-of-the-artgraphanalyticsonlargedatabases.Thestudentwouldimplementanddesignasoft-coremicroprocessorsubsystemtoenablethecontrolinfrastructureforanFPGA-basedgraphprocessingcluster.Itwouldconsistofevaluationandselectionofreal-timeoperatingsystems,designandintegrationofbussesandperipheralsforvariousgraphcomputingmodules,aswellasimplementationofanRTOSsoftwareframeworkfortheGraphprocessorinstructionset.

Pre-requisites:

AdvancedDigitalDesign,OperatingSystems,VHDL,C/C++

“Embedded,Real-time3DPerceptionforRobotAutonomyandAugmentedRealityDisplay”

FacultyAdvisor:TBDLincolnMentor(s):NicholasArmstrong-CrewsContacte-mail:[email protected]:EmbeddedProcessingArchitecturesforPerception

Emerging3Dsensorsprovideawealthofinformationthatsimplifiescommonperceptiontasks(apre-requisiteforrobotautonomyandnaturalhuman-robotinteraction);however,standardcomputingmethodscannotkeepupwiththisbigdatastreamtoreactinreal-time,especiallyonplatformswithconstrainedsize,weight,andpower.Thisprojectintendstoexploretightly-integrated,embeddedsense/computearchitecturesthatexploitdataparallelism,includingFPGAs,GPUs,anddigitalfocalplanearraysusedinconjunctionwithLIDAR,stereo,andstructuredlightsensors.

“ModelingOpenArchitectureStandards”

FacultyAdvisor:TBD

LincolnMentor(s):EddieRutledge,StacyDoyle

Contacte-mail:[email protected],[email protected]

ResearchArea:Model-AidedSoftwareArchitecture,Simulation,andVerification

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Softwareopenarchitecture(OA)standardsdefinestandardarchitecturalelements,interfaces,andrulesforcompositioninbuildingsoftwaresystems.Softwarearchitecturemodelingcanhelppredictandvalidateaspectsofasoftwaresystemsuchasperformance,reliability,availability,andcorrectness.ThisresearchwillfocusonmodelingOAstandardsandthesystemsthatconformtothem.ResearchtopicscouldincludecharacteristicsofanOAstandardthatenableorsimplifymodelingofconformantsystems,capabilitiesandlimitationsofexistingmodelingtoolsandtechniquesinmodelingOAconformantsystems,themodelingandanalysisofanOAstandarditselftodeterminegeneralpropertiesofallconformantsystems,andthespecificationofOAstandardsandconformantsystemsasformalmodels.

“Multi-InputMulti-OutputProcessingforFeatureExtractionandDetection”

FacultyAdvisor:

LincolnMentor(s):HuyNguyen

Contacte-mail:[email protected]

ResearchArea:MultipleApertureSensing

ThisprojectexploresageneralizedMIMOframeworkanddistributedcomputationtechniquesforfeatureextraction,detection,andtrackingfrommulti-channel“sensors”.Adiversesetofapplicationareaswillbeconsideredincluding:millimeter-waveimaging,focal-planearrayimaging,andcyberactivitymonitoring.

“3DSARImageFormationusingaUnmannedAirVehicle”

FacultyAdvisor:TBD

LincolnMentor(s):DanRabinkin

Contacte-mail:[email protected]

ResearchArea:SmallFormFactorRadarandSARProcessing

TraditionalSARimageryisformedfromflyingplatformsthatsweepoutlinearapertureandproduce2-Dimages.AhoveringUAVcanbeusedtosweepouta2-Dapertureandproduce3-Dimagery.Three-dimensionalSARimagery,combinedwithproperdisplaytools,canprovidedetailsofstructuresandobstructionstosoldiersandrescueworkers,andprovideanenhancedmappingcapabilitytorenderterraininhyper-realdetail.AdvancesinUAVplatformdesign,miniaturizedRFreceivers,andminiaturizedandhighprecisiondifferentialnavigationsystemscanbecombinedtointegrateasystemcapableofproducingfocused3-DSARimages.ThisresearchwillfocusoncomponentsystemarchitectureandCOTScomponentintegrationleadingtoaplatformprototype.

“TheoreticalandPracticalMIMORadioCommunicationTechniquesinCongestedSpectrum”

FacultyAdvisor:

LincolnMentor(s):AdamMargetts

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Contactemail:[email protected]

ResearchArea:WirelessCommunications

Multiple-inputmultiple-output(MIMO)radiosystemsarebeginningtodominatethecommercialwirelesscommunicationworldwiththeirpromisetoincreasedataratesandextendrange.Theapplicationofthistechnologytoapplicationstosituationswherealargenumberofstronginterferencesourcesarepresentisstillinitsinfancy.ThisprojectwouldconsistofexaminingwiththementoralgorithmsrelevanttothisscenarioandbuildingaMatlabsimulationwithrealisticchannelmodelstotesttheselectedalgorithms.Thestudentwouldbeimmersedinallaspectsofmoderncommunicationtheoryfromthephysicallayertothenetworklayer.

“TheoreticalandPracticalMIMORadioCommunicationTechniquesinCongestedSpectrum”

FacultyAdvisor:

LincolnMentor(s):KeithForsythe

Contactemail:[email protected]

ResearchArea:WirelessCommunications

Inchallengingenvironments(e.g.,underwateracousticorskywaveRFchannels)signalssufferfromdistortionsassociatedwithtimeandDopplerspreadsintroducedbythepropagationmedium.Thesedistortionscreatedifficultiesfortheimplementationofspatialfilteringasemployedbymulti-sensorreceivingarrays.Withonlydelayspread,signalenergycanbelocalizedinseparatefrequencycells;eachcellcanuseconventionalarrayprocessingforspatialfiltering.ThedualproblemwithonlyDopplerspreadalsoreducestoaknownsolution.Theinabilitytolocalizeinbothtimeandfrequencymakessignalprocessingmuchmoredifficultwhenbothdistortionsarepresent.Thelevelofperformancebecomeshighlydependentonthesignalprocessingarchitectureandisaffectedbytheabilitytotrainthespatialfiltersinadynamicenvironment.Thisprojectwillexplorethedesignandperformanceofvariousarchitecturesforspatialfilteringofsignalswithlargedelay-Dopplerspreads.

“MU-MIMO-MUDSystems”

FacultyAdvisor:

LincolnMentor(s):P.D.Fiore

Contacte-mail:[email protected]

ResearchArea:SignalProcessingandCommunications

Usageofwirelesscommunicationsdeviceswillcontinuetoincrease,andoptimizationofspectrumusagewillbecomeparamount.Advancedsignalprocessingtechniques,suchasmulti-user-detection(MUD),canallowmuchhighereffectiveuseofRFchannels,especiallywhencoupledwithmulti-input,multi-output(MIMO)transmissionschemes.However,theefficacyofthesetechniques,aswellasthecostofimplementation,willbeafunctionofthesymbolconstellationschosenforthecommunications.Inthisproject,wewillinvestigatemultiuserMIMOsymbolconstellationsforcommercialandpersonal

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wirelesscommunications.Explorecombinationsofscale-recursiveconstellationdesigns,OFDM,andSTBCtoachievehigherthroughputthancurrentQAMapproaches.

“ReinforcementLearningforMulti-AgentMarkovGames”

FacultyAdvisor:

LincolnMentor(s):DavidBrowne

Contactemail:[email protected]

ResearchArea:Communications,Robotics,MachineLearning

ReinforcementLearningisaclassoflearningalgorithmthatallowsanagenttoautonomouslylearnhowtoachievesomegoalstatethroughrepeatedinteractionwithitsenvironment.Thesealgorithmshavedemonstratedapplicabilityinsequentialdecisionmakingproblemsforroboticnavigationandradiocommunicationsamongothers.TheprojectwillexploreandextendthetheoryofreinforcementlearninginMarkovgamescomprisedoftwoormoreagentsinteractingineithercooperativeorcompetitivegames.Opensourcesimulationsoftwarewillbeusedasthesandboxfordevelopmentandexperimentationwithagents.Optionsforimplementingagentalgorithmsinsoftware-definedradionetworkswillbeexplored.

“SharpeningofTime-FrequencyRepresentations”

FacultyAdvisor:

LincolnMentor(s):PaulCalamia

Contacte-mail:[email protected]

ResearchArea:SignalProcessing

Thereassignedspectrogram(ortime-correctedinstantaneous-frequencyspectrogram)isaspectralanalysistooloftenusedtodeterminethepreciseinstantaneousfrequenciesandassociatedtimesofoccurrenceofspectralcomponentsinanacquiredsignalofinterest.Ithasbeendescribedintheliteratureasaneffectivemethodofanalysisfor,amongotherthings,humanspeech,animalcommunications,andmusic.Inthisproject,wewouldliketoexplorevariousaspectsofthereassignedspectrogramincludingefficientimplementations,displaymethods(specificallyartifactremoval/de-noising),andextensionstotheanalysisofothernon-stationarysignals.

“Crowd-sourcedExploitationofNGOData”

PotentialFacultyAdvisors:RobMiller(CSAIL)

LincolnMentor(s):OlgaSimek

Contacte-mail:[email protected]

ResearchArea:Crowdsourcing

ThisprojectwillcreateaprocessandtoolsforextractingandanalyzingrelevantinformationfromNon-GovernmentalOrganization(NGO)resourcecollectionsusingcrowdsourcing.NGOsproducedetailedreportsaboutthesituationonthegroundinplacesofinterest

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tothegovernment.However,informationinthesecollectionscanbedifficultorimpossibletofindusingstandardsearchtools,becauseitisgenerallyunstructuredand/orembeddedinimages.Ourgoalistodevelopeffectiveworkflows,taskdesignsandresultaggregationalgorithmsforfast,cheapandaccuratecrowd-sourceddataexploitation.

OurbasicobjectiveistodevelopaprototypesystemwhichwillutilizeworkersonanopencrowdsourcingplatformlikeAmazonMechanicalTurktoquicklyandcost-effectivelycreateintelligencefromNGOdocuments.Crowdsourcingcanbeusedallalongthedatacollectionandexploitationpipeline,including:

• IdentifyingpotentialsourcesofNGOdata

• CollectingdatafromNGOsources

• Transformingunstructureddata(e.g.images,text)intostructureddata(e.g.annotatedmaps,spreadsheets)

• Identifyinganomaliesincharts

Analyststodayareoverwhelmedbyanever-increasingvolumeofopensourcedata,andmethodsandalgorithmsareneededtoeffectivelyextractusefuldatafromthisvaluableinformation.Ithasbeenamplydemonstratedthatcrowdsofnon-expertscansolvecomplexproblemsifproblemsarepresentedinanaccessibleway.Thefirstpartofaneffectivestrategyforproducingfast,cheapandaccurateresultsconsistsofbreakingtheproblemintosmalltasks,andusingworkredundancyanditerativeworkflowstoensuredataaccuracy.Thesecondpartistoutilizeproblem-specificworkerqualityalgorithmstocorrectlyaggregatetheresults.Bothpartsareactiveresearchareas.

“QuantifyingDecisionPerformanceforEarlyWarning”

FacultyAdvisors:SertacKaraman(MITDepartmentofAeronauticsandAstronautics)

LincolnMentor(s):FrederickWaugh

Contacte-mail:[email protected]

ResearchArea:DecisionSupport,ResourceOptimization,Games

Thisresearchprogramwillexplorestrategiestoimprovetheutilizationofdatacollectionassetsusingarepresentativeearly-warninggame.Wewillquantifythehumanperformanceinsuchscenarioswithrespecttovaryingdegreesofuncertaintyandcomplexityasfollows:

1. Wewilldesignasimple(butrealistic)structuredearlywarninggamethatisamenabletomathematicalanalysis.

2. Wewillemploymathematicalandalgorithmicanalysistoquantifythebestpossibleperformanceinthegame.Moreprecisely,wewillprove(inamathematically-rigorousway)tightupperboundsonperformance.Thisanalysiswillemployappliedprobabilitytheory,stochasticgeometry,networkscience,andpercolationtheory,whichhavebeenemployedtoanalyzesimilarplanningproblems[1].Wewillalsodesignandimplementeffectivealgorithmsthatperformclosetosuchupperbounds,similartothosedevelopedin[2].Thesewillhelp

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usquantifytheoptimalperformanceasafunctionofbothsystemnoiseandcomplexity.

3. Timepermitting,wewilldesignandconductexperimentstounderstandhowhumanperformance,simulatingcurrenttaskingprocedures,compareswithcomputedbounds.

[1]S.KaramanandE.Frazzoli,“High-speedFlightinanErgodicForest,”presentedattheIEEEInternationalConferenceonRoboticsandAutomation,2011.

[2]S.KaramanandD.Rus,“PersistentMonitoringofEventswithStochasticArrivalsatMultipleStations,”submittedtotheIEEEInternationalConferenceonRoboticsandAutomation,2014.

“DynamicSaliencyMapGenerationforResourceAllocation,SituationAwareness,andDecision-Making”

PotentialFacultyAdvisors:PatrickJaillet,AlanWillsky,JohnFischer

LincolnMentor(s):BeaYu,DanelleShah

Contacte-mail:[email protected];[email protected]

ResearchArea:ResourceOptimization,DataFusion

Assensorsbecomemorecapable,moreautonomous,andmoreubiquitousinhumanitarian,militaryandscientificdiscoverymissions,itbecomesincreasinglyimportantforsuchsensorstoself-assesstheireffectivenessagainstmissionobjectivesandreacttochangingneedsinreal-time.Aself-assessmentschemewouldideallyfusemultipledatasourcesandconsidermultiplesimultaneousobjectives.Theoutputmaybeusedforautomaticresourcere-allocation,providedtoahumanoperatortomaintainSituationAwareness(SA),orsharedwithcollaboratingagentstoformaCommonOperatingPicture(COP).Forthisproject,theconceptofa“saliencymap”willbeusedtoquantify,visualize,andexploitsensoreffectiveness.

Keyresearchquestionstobeansweredare:howtofusemultipledifferentdatasourcesintoasingle“saliency”value,howtoquantify“sensoreffectiveness”fordifferentmissionobjectives,andhowdifferentsaliencymapseffectoperatorsituationawareness

“NonparametricMultivariateChangePointDetectionUsingProbabilisticGraphicalModels”

PotentialFacultyAdvisors:AlanWillsky,JohnFischer

LincolnMentor(s):PeterMastromarino

Contacte-mail:[email protected]

ResearchArea:ChangeandAnomalyDetection,ProbabilisticGraphicalModels

Multivariatechangepointdetectionisacommonstatisticalanalysistaskwithapplicabilitytoavarietyofproblemsindifferentfieldsinwhichdatacorrelationsandinter-dependenciesareimportantconsiderations[1].Traditionalmethodsofdetectiontypicallyrelyonananalysisofthemeansandcovariancematrixofthevariablesinvolvedinordertodetectchanges[2].Beingthussensitivetoonlythefirstandsecondmomentsofthedata,however,suchmethodsare

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extremelylimitedinthetypesofchangestheyareabletodetect.Theselimitationscanbepartiallyaddressedbyexpandingtothethirdmomentsandbeyond,butsuchastrategyisstatisticallyinefficient,sincemanyofthemomentssharestatisticalsupportandarethereforecoupled.

Nonparametricapproachesofferawayoutofsuchstatisticalinefficiencybyattemptingtomodelanddetectchangesintheunderlyingstructureofthefulljointprobabilitydistributionfunction(pdf)governingtherandomvariables[3].Asthenumberofrandomvariablesgrows,however,itquicklybecomesintractabletomodelthefulljointpdf,orevenitscompactrepresentation(suchasBayesiannetworkgraphicalmodels).Thisprojectwillleveragerecentadvancesinefficientsamplingtechniquesforestimatingthedistributionofpossiblepdfrepresentations[4]inordertobuildasystemcapableofdetectingchangepointsinmultivariatetimeseriesandofprovidingestimatesoftheiruncertainty.

Elementsoftheprojectwillincludeadevelopmentofthemathematicaltheoryunderlyingthetechniquesaswellasprototypedevelopmentoftheuserinterface.Thetoolswillbetestedusingacombinationofsyntheticandreal-world,publiclyavailabledatasets,suchasCongressionalvotingrecords(toautomaticallydetectfromvotingpatternsaloneeventssuchaselections)andfinancialmarketdata(todetectsignificantmarketevents).

[1]J.Reevesetal.,“Areviewandcomparisonofchangepointdetectiontechniquesforclimatedata,”J.AppliedMeteorologyandClimatology,Vol.46,pp.900–915(2007).

[2]M.Lavielle,G.Teyssière,“Detectionofmultiplechangepointsinmultivariatetimeseries,”LithuanianMathematicalJournal,Vol.46,No.3,pp.287–306(2006).

[3]B.Brodsky,B.Darkhovsky,NonparametricMethodsinChange-PointProblems,KluwerAcademicPublishers,Norwell,MA(1993).

[4]N.Friedman,D.Koller,“BeingBayesianaboutnetworkstructure,”MachineLearning,Vol.50,pp.95–125(2003).

“AdaptiveMulti-vehicleSensing”

PotentialFacultyAdvisors:NickRoy,EmilioFrazzoli,BrianWilliams,JulieShah,JonHow,AsuOzudaglar

LincolnMentor(s):BeaYu,DanelleShah,DanGriffith,FrederickWaugh

Contacte-mail:[email protected],[email protected]

ResearchArea:AutonomousSystems,ResourceOptimization

Sensingsystemsareimportantforecological,humanitarian,militaryandspaceexplorationapplications.Theaerialsensingdomainisrapidlyevolvingtoincludeautonomoussystems.Thedeploymentandcontrolstrategiesforthesesystemshavebothhumancentricandcomputationalimplications.Inthisstudy,wewillconsiderdifferentdeploymentandcontrolstrategiesforafuturisticmulti-vehiclesensingsystem.Givenadynamicinformationmapmodel,whichrespondspredictablybutstochasticallytonewinformationcollectionsandevolvesexogenouslywhennosensingisperformed,andasetofN

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unmannedaircraftresourcesforsensing,theobjectiveistooptimizethedeploymentofresourcesinordertomaximizetheinformationcontentoftheresultingmap.

“MIMORadarSignalProcessing”

Facultyadvisor:TBD

LLMentor(s):JohnKay

Contacte-mail:[email protected]

ResearchArea:AntennaArrays,Waveforms,SignalProcessing

Assmallandunmannedplatformsproliferate,thereisanincreaseddemandforthemtoperformmoreandvariedmissions.Thelimitedspaceonsmallplatformsinhibitstheabilitytocarrylargepoddedphased-arrayradarsystemswhicharetraditionallyneededtoachievetherequiredresolutionandsensitivityforairbornesurfacesurveillanceradarsystems.Onepotentialalternativeisadistributed,thinnedarrayswhichhavereducedsizeandweightand,whencoupledwithMIMOsignalprocessing,canregainmuchofthebenefitoflargerfilledarrays.Thisprojectistoexplorepotentialconfigurationsofarraysonmid-sizeUAVsaswellaswaveformsstrategiestooptimizeperformanceforairbornesurfacesurveillancemissions.

“OscillatorTime/FrequencyTransfer”

FacultyAdvisor:TBD

LincolnMentor(s):JoshuaKantor

Contacte-mail:[email protected]

ResearchArea:WirelessCommunications,EmbeddedDigitalSystems

Theprojectistodemonstratetheabilitytopreciselysynchronizeoscillators(onwidelyseparatedmovingplatformsusingabidirectionaldatalink(twowaytimetransfer)andFPGAprocessing.Thegoalistoshowthatwiththissynchronization,coherentintegrationtimeinbistaticSARandTDOA/FDOAprocessingcanbeextendedbeyondthelimitsimposedbytheoscillators'intrinsiclowfrequencyphasenoisecharacteristics.

“Featuredetectionandclassificationalgorithmsfor3-dimensionaldata”

FacultyAdvisor:

LincolnMentor(s):LukeSkelly

Contacte-mail:[email protected]

ResearchArea:ComputerSystems/Computervision

Developnewalgorithmsforfeaturedetection,classificationandsceneunderstandingof3Dpointcloudscollectedfromladarsystems.Inordertoscaleperformancetoenormousdatasets,newalgorithmsmustbeauto-tuning,andthistypicallyrequiresarigoroustheoreticalunderpinningbasedonthephysicsoftheladardatacollectionprocessaswellasstatisticaldescriptionofthescene.Thecodesmustbe

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writtenefficientlyenoughtohandlelargedatasets.Familiaritywithstatisticalsignalprocessing,datastructures(trees,graphs,etc.),andpatternrecognitionispreferred.

“Embeddedprocessingofladardata”

FacultyAdvisor:Prof.VivienneSze

LincolnMentor(s):DaleFried

Contacte-mail:[email protected]

ResearchArea:Circuits/EmbeddedProcessing

Photoncountinglaserradarsystemsarehighlycapablesystemthatcanproducehighresolution,3-dimensionalmapsoverlargeareasatanimpressiverate.Typicallythesesystemsarebig(>1000lbs)anddrawsizeableamountofpower(>kWs)Thereisaconcertedefforttosignificantlyreducetheirsize,weightandpowerbyordersofmagnitudebyusingacombinationofaggressivepackagingandanovelarchitecture.Photoncountingladarimageformationprocessingrequiresnoisefilteringthatdifferentiatesdetectionsfromactualssurfacesfromthoseduetonoiseand/orbackground.Currentlysuchnoisefilteringalgorithmsoccursonmulti-coreCPUs.Thegoaloftheprojectistoperformthisladarimageformationprocessingonlow-powerembeddedprocessors.Theseprocessingalgorithmsmustbeabletokeepupwithhighdatarates,implementdatacompressioninhardwaretomatchthelimitedoff-packagecommunicationbandwidth.FamiliaritywithFPGA,embeddedprocessinganddatacompressiontechniquesisneeded.

“VideoTrackingSidecarandControlSystem”

FacultyAdvisor:

LincolnMentor(s):SethTrotz,EmilyFenn,BobMichniak,andJamesTruitt.

Contacte-mail:[email protected]

ResearchArea:

Airbornepassiveimagingsensorscanbeemployedtoprovidesituationawarenessandtrackingofaircraft.Trackingofunresolvedtargetsatlongrangecanbelimitedbysensorperformanceaswellasscenecomplexityorclutter.UROPresearcherswillworkwithLincolnstafftodevelopageneralizedvideotrackingandcontrolsystem.Thisreal-timecapablesystemwilltakeasinputachoiceofdigitizedvideostreamsandnavigationaldata,applyappropriatealgorithmssuchasspatio-temporaldifferencingoropticalflow,andtrackoneormoreobjectswithinthesensorfieldofview.Thesystemmayoperateinapassive"sidecar"modeorinanactiveclosed-loopmodeinwhichsensorpointingisalsocommanded.Experienceorinterestinimplementingavarietyofnovelalgorithmsinflexiblehigh-speedimageprocessinghardwaresuchasGPUsorFPGAstoenablerapidprototypingisexpected.Thesystemwillinitiallybedevelopedinalaboratoryenvironmentandsubsequentlyruninairborneflighttests.

“MeasurementAssistedModelingofElectromagneticScattering”

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FacultyAdvisor:TBD

LincolnMentor(s):HsiuHan,AndrewO'Donnell

Contacte-mail:[email protected]

ResearchArea:Electromagnetics

Thisresearchfocusesonthepredictionofmicrowavefar-fieldscatteringcrosssectionsofcomplexandelectricallylargeobjectsusingcomputationalmodelsvalidatedwithnear-fieldmeasurementdata.Theinitialemphasisistodevelopunderstandingoftheimpactofnon-uniformorpartialnear-fieldilluminationonthemodelvalidationprocessandtheaccuracyoftheresultedfar-fieldprediction.Bothmeasurementandpredictionwillbeperformedunderthisproject.

“OpticalPhasedArrays”

FacultyAdvisor:R.Ram,M.Watts

LincolnMentor(s):R.Swint,S.Spector

Contacte-mail:[email protected],[email protected]

ResearchArea:optics,photonics

Theopticalbeamfromanarrayoflasersoropticalamplifierscanbenon-mechanicallysteeredorusedtogenerateanarbitrarybeampatternbyadjustingtheopticalphaseofeacharrayelement.Thespeedandphysicalrobustnessofsuchanon-mechanicalbeamsteeringsystemisaholygrailformanyapplicationsrangingfromfree-spaceopticalcommunications,LIDAR,orlaserprinting.Whilephasedarraysystemshavehadahugeimpactinreal-worldmicrowaveradarsystems,asimilarsystemintheopticaldomainhasprovedelusiveduetotechnicalchallenges.Integratedphotonicsispotentiallypartofthesolutiontorealizingpracticalopticalphasedarraysystems.UROPresearcherswillassistindevelopingthiscapability.Theresearcherswillsimulateanddesignphotonicintegratedcircuits(PICs),supportinternalorexternalPICfabrication,characterizedevicesandsubsystems,and/ordevelopopticalphasedarraycontrolalgorithmsandreal-timesoftware.

“WavelengthFilteringinSiliconPhotonics”

FacultyAdvisor:R.Ram,L.Kimerling

LincolnMentor(s):R.Swint,S.Spector

Contacte-mail:[email protected],[email protected]

ResearchArea:Solidstatephotonics

UROPresearcherswilldesignanddevelophighqualityopticalfiltersthatmaybeimplementedinsilicontechnology.Siliconphotonicsisatechnologywhichusessiliconasanopticalmaterial,sothatthevastinvestmentmadeinthedevelopmentofintegratedelectronicscanbeappliedtointegratedoptics.Acommonelementinanopticalsystemisawavelengthorfrequency-selectivefilter.Highqualityfiltershavebeendemonstratedusingresonantdevicesinsiliconphotonics,butchallengesremain.Dependingontheapplication,thesechallengesincludecontrollingtheresonantwavelength,achievingextremelyhighresonantqualityfactors(Qs),andhandlinglargeamountsofoptical

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power.Solutionstooneormoreofthesechallengeswillbeinvestigated.

“Microladar”

FacultyAdvisor:V.Szeand/orM.Watts

LincolnMentor(s):D.Fried,D.Schuette

Contacte-mail:[email protected],[email protected]

ResearchArea:

UROPresearcherswilldesignandimplementascanningladarsystem.Ladarsensorshaveproventhemselvesacriticalcomponentofautonomousnavigationsystemsbecausetheydirectlymeasurethe3Dcharacterofasceneratherthaninferringitindirectlyusinglessreliablecomputervisiontechniques.ThesizeandweightofthesesensorsandtheirpowerrequirementshavehistoricallyprecludedtheiruseinsmallplatformssuchasUAVsorinlowcost3-Dscanners,buttechnologyunderdevelopmentwillproducealadarsensorelementthesizeofachild'sthumbwhosecapacitysurpassesthatofmuchlargersystems.Researchtopicsincludethescanningtransmittersandreceivers,and3Dimageprocessingchips.

“WidebandImagingRadar”

FacultyAdvisor:TBD

LincolnMentor(s):B.Perry,F.Robey

Contacte-mail:[email protected],[email protected]

ResearchArea:RFElectronics/signalprocessing

UROPresearcherswilldesign,buildandtestalowcostwidebandimagingradar.Radarimaginghasmanypotentialusesindefense,homelandsecurityandlocalsecurity.Recentopeningofthefrequencyspectrumtounlicensed,part15operationsprovidesthepotentialfordeploymentinbroadapplicationsandnewcircuittechnologieshavesignificantlyreducedthecostforradarsystems.Theresultisthatmanynewvehicleshaveradarsbuiltin.ForthisUROPoneoftheinterestsistoinvestigateradarthatcouldassistlawenforcementthatcurrentlyrelyonlyoncameravideotodeterminephysicalfeatures.Widebandradarimagingalgorithmdevelopmentatmanyuniversitiesisoftenstarvedfordata.Ashortrangewidebandimagingradarsystemcouldfillthatgap.UnderthisUROPalowcost,widebandimagingradarwillbedevelopedbyleveragingmicrowavemotionsensor,vehiclesafetyradar,orpersonalcommunicationservicestechnology.

“PhotonicsforQuantumInformationSystems”

FacultyAdvisor:R.Ram,D.Englund

LincolnMentor(s):R.Swint,S.Yegnanarayanan

Contacte-mail:[email protected],[email protected]

ResearchArea:

Thefieldofquantuminformationscience(QIS)isexploringnew

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paradigmsforcomputing,sensing,andcommunicationsbasedonquantum-mechanicalprinciples.LasersourcesandphotonicdevicesarecriticaltothedevelopmentofQIStechnologiesinareasincludingatomcoolingandstatemanipulation,entangled-photongeneration,frequencytranslation,opticalsignalswitchinganddistribution,laserstabilizationandcontrol,integratedopticalisolation,andopticalsignaldetection.Therealizationofapracticalquantumcomputerwillrequiretheintegrationofatomicorsuperconductingqbits,photonics,andelectronics.Exampleresearchprojectsincludedevelopmentoflow-noisehigh-efficiencylasersatatomic-specificwavelengths,developmentofmonolithicorhybridphotonicintegratedcircuits(PICs),investigationofnovelphotonicmaterialsandmaterialplatforms,andelectronic-photonicintegration.