2017-04-14 LincolnLab SuperUROP Projects Version 1...and assessing cyber systems, including red...

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

SuperUROPProjects

“WirelessAnomaliesHaveNoPlacetoHide”

FacultyAdvisor:

Mentor(s):W.MarkSmith,PhD

Contacte-mail:wireless-student@ll.mit.edu

ResearchArea(s):CyberSystemsandOperations

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

“HLT-BasedAdvancedAnalytics”

FacultyAdvisor:

Mentor(s):WilliamCampbell,PhD

Contacte-mail:wcampbell@ll.mit.edu

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:stsmith@ll.mit.edu,fwaugh@ll.mit.edu

ResearchArea(s):ComputingandAnalytics

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

“SecuringOurCyberFuture”

FacultyAdvisor:

Mentor(s):HamedOkhravi,RogerKhazan,KyleIngols

Contacte-mail:hamed.okhravi@ll.mit.edu,rkh@ll.mit.edu,kwi@ll.mit.edu

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:kevin.bush@ll.mit.edu

ResearchArea(s):CyberSystemsandOperations

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

Engagedinawiderangeofcybersecurity-relatedactivities,theCyber

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:franz@ll.mit.edu,evans@ll.mit.edu

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:jhallett@ll.mit.edu

ResearchArea:SmallSensorTechnologies

UROPresearcherswillperformanassessmentofsmallform-factortagsthatcanbeusedtodetect,locateandtrackmovinggroundobjectsofinterestfromlongphysicalranges.Differentsensormodalitiesshouldbeconsideredintheassessment.Strawmandesigns

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

“Soft-coreMicroprocessorInfrastructureforaGraphProcessingCluster”

FacultyAdvisor:TBD

LincolnMentor(s):VitaliyGleyzer,WilliamSong

Contacte-mail:vgleyzer@ll.mit.edu,song@ll.mit.edu

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:nickarmstrongcrews@ll.mit.eduResearchArea: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:rutledge@ll.mit.edu,sad@ll.mit.edu

ResearchArea:Model-AidedSoftwareArchitecture,Simulation,andVerification

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

“Multi-InputMulti-OutputProcessingforFeatureExtractionandDetection”

FacultyAdvisor:

LincolnMentor(s):HuyNguyen

Contacte-mail:hnguyen@ll.mit.edu

ResearchArea:MultipleApertureSensing

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

“3DSARImageFormationusingaUnmannedAirVehicle”

FacultyAdvisor:TBD

LincolnMentor(s):DanRabinkin

Contacte-mail:rabinkin@ll.mit.edu

ResearchArea:SmallFormFactorRadarandSARProcessing

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

“TheoreticalandPracticalMIMORadioCommunicationTechniquesinCongestedSpectrum”

FacultyAdvisor:

LincolnMentor(s):AdamMargetts

Contactemail:margetts@ll.mit.edu

ResearchArea:WirelessCommunications

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

“TheoreticalandPracticalMIMORadioCommunicationTechniquesinCongestedSpectrum”

FacultyAdvisor:

LincolnMentor(s):KeithForsythe

Contactemail:forsythe@ll.mit.edu

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:pfiore@ll.mit.edu

ResearchArea:SignalProcessingandCommunications

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

wirelesscommunications.Explorecombinationsofscale-recursiveconstellationdesigns,OFDM,andSTBCtoachievehigherthroughputthancurrentQAMapproaches.

“ReinforcementLearningforMulti-AgentMarkovGames”

FacultyAdvisor:

LincolnMentor(s):DavidBrowne

Contactemail:dbrowne@ll.mit.edu

ResearchArea:Communications,Robotics,MachineLearning

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

“SharpeningofTime-FrequencyRepresentations”

FacultyAdvisor:

LincolnMentor(s):PaulCalamia

Contacte-mail:pcalamia@ll.mit.edu

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:osimek@ll.mit.edu

ResearchArea:Crowdsourcing

ThisprojectwillcreateaprocessandtoolsforextractingandanalyzingrelevantinformationfromNon-GovernmentalOrganization(NGO)resourcecollectionsusingcrowdsourcing.NGOsproducedetailedreportsaboutthesituationonthegroundinplacesofinterest

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:fwaugh@ll.mit.edu

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

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:bea.yu@ll.mit.edu;danelle.shah@ll.mit.edu

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:peterm@ll.mit.edu

ResearchArea:ChangeandAnomalyDetection,ProbabilisticGraphicalModels

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

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:dan.griffith@ll.mit.edu,fwaugh@ll.mit.edu

ResearchArea:AutonomousSystems,ResourceOptimization

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

unmannedaircraftresourcesforsensing,theobjectiveistooptimizethedeploymentofresourcesinordertomaximizetheinformationcontentoftheresultingmap.

“MIMORadarSignalProcessing”

Facultyadvisor:TBD

LLMentor(s):JohnKay

Contacte-mail:jkay@ll.mit.edu

ResearchArea:AntennaArrays,Waveforms,SignalProcessing

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

“OscillatorTime/FrequencyTransfer”

FacultyAdvisor:TBD

LincolnMentor(s):JoshuaKantor

Contacte-mail:Joshua.kantor@ll.mit.edu

ResearchArea:WirelessCommunications,EmbeddedDigitalSystems

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

“Featuredetectionandclassificationalgorithmsfor3-dimensionaldata”

FacultyAdvisor:

LincolnMentor(s):LukeSkelly

Contacte-mail:skelly@ll.mit.edu

ResearchArea:ComputerSystems/Computervision

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

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

“Embeddedprocessingofladardata”

FacultyAdvisor:Prof.VivienneSze

LincolnMentor(s):DaleFried

Contacte-mail:dgf@ll.mit.edu

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:seth.trotz@ll.mit.edu

ResearchArea:

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

“MeasurementAssistedModelingofElectromagneticScattering”

FacultyAdvisor:TBD

LincolnMentor(s):HsiuHan,AndrewO'Donnell

Contacte-mail:hsiu@ll.mit.edu

ResearchArea:Electromagnetics

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

“OpticalPhasedArrays”

FacultyAdvisor:R.Ram,M.Watts

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

Contacte-mail:swint@ll.mit.edu,spector@ll.mit.edu

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:swint@ll.mit.edu,spector@ll.mit.edu

ResearchArea:Solidstatephotonics

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

power.Solutionstooneormoreofthesechallengeswillbeinvestigated.

“Microladar”

FacultyAdvisor:V.Szeand/orM.Watts

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

Contacte-mail:dgf@ll.mit.edu,drschuette@ll.mit.edu

ResearchArea:

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

“WidebandImagingRadar”

FacultyAdvisor:TBD

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

Contacte-mail:bperry@ll.mit.edu,robey@ll.mit.edu

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:swint@ll.mit.edu,siva.yegnanarayanan@ll.mit.edu

ResearchArea:

Thefieldofquantuminformationscience(QIS)isexploringnew

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

2017-04-14 LincolnLab SuperUROP Projects Version 1...and assessing cyber systems, including red...

Documents

“Teaming for Success”

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Profiling teaming

High Performance Teaming

Red Teaming

Collaborative Teaming

Purple teaming Cyber Kill Chain

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Business Teaming

OSCAR: Red Teaming

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SpecialQuest Teaming