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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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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”
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
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
ThisworkissponsoredbytheAirForceunderAirForceContractFA8721-05-C-0002.Opinions,interpretations,conclusions,andrecommendationsarethoseoftheauthorandarenotnecessarilyendorsedbytheUnitedStatesGovernment.
paradigmsforcomputing,sensing,andcommunicationsbasedonquantum-mechanicalprinciples.LasersourcesandphotonicdevicesarecriticaltothedevelopmentofQIStechnologiesinareasincludingatomcoolingandstatemanipulation,entangled-photongeneration,frequencytranslation,opticalsignalswitchinganddistribution,laserstabilizationandcontrol,integratedopticalisolation,andopticalsignaldetection.Therealizationofapracticalquantumcomputerwillrequiretheintegrationofatomicorsuperconductingqbits,photonics,andelectronics.Exampleresearchprojectsincludedevelopmentoflow-noisehigh-efficiencylasersatatomic-specificwavelengths,developmentofmonolithicorhybridphotonicintegratedcircuits(PICs),investigationofnovelphotonicmaterialsandmaterialplatforms,andelectronic-photonicintegration.