The Trustees Of The Stevens Institute Of Technology

PARTNERSHIP TO IMPROVE STUDENT ACHIEVEMENT IN PHYSICAL SCIENCES: INTEGRATING STEM APPROACHES (PISA2)

STEVENS INSTITUTE OF TECHNOLOGY CARES ACT PART B

STEVENS INSTITUTE OF TECHNOLOGY CARES ACT

TRANSITIONING AT/FP TECHNOLOGIES THROUGH COLLABORATIVE R&D IN THE MARITIME ENVIRONMENT (SINTEL PHASE III)

RENEWAL: CYBERCORPS: SCHOLARSHIP FOR SERVICE PROGRAM AT STEVENS

THE PURPOSE OF THIS AGREEMENT IS TO FUND RESEARCH SUPPORTING THE DEFENSE ADVANCED RESEARCH PROJECTS AGENCY DARPA PERCEPTUALLY ENABLED TASK GUIDANCE PTG. THIS EFFORT SHALL BE CARRIED OUT GENERALLY AS SET FORTH IN EXHIBIT B, RESEARCH DESCRIPTION DOCUMENT, DATED NOVEMBER 9, 2021, AND IN THE RECIPIENTS PROPOSAL TITLED, MILLY MULTI DIRECTIONAL LOOSELY LINKED ARCHETYPE MODELS FOR PERCEPTUALLY-ENABLED TASK GUIDANCE, PROVIDED TO DARPA ON MAY 14, 2021, COPIES OF WHICH ARE IN THE POSSESSION OF BOTH PARTIES.

THE ATLANTIC CENTER FOR THE INNOVATIVE DESIGN AND CONTROL OF SMALL SHIPSSTUDIES ON SWACH TRIMARAN AND UNMANNED SURFACE VESSELS

BIGDATA: CAUSAL INFERENCE IN LARGE-SCALE TIME SERIES WITH RARE AND LATENT EVENTS

ABIDES: ADAPTIVE BINARY DEBLOATING AND SECURITY

IMPROVED VENTILATION OF THE EDEMATOUS LUNG

THE STEVENS INTEGRATED MARITIME SURVEILLANCE AND FORECAST SYSTEM

NJ ALLIANCE FOR ENGINEERING EDUCATION (NJAEE)

FOUNDATIONS: INTEGRATING EVIDENCE-BASED TEACHING AND LEARNING INTO THE CORE ENGINEERING CURRICULUM

SUSTAINED OCULAR DRUG DELIVERY SYSTEM FOR ANTI-VEGF AGENTS

CENTER OF EXCELLENCE FOR MARITIME RESEARCH

THE CENTER FOR MARITIME RESEARCH

ESE: IM EXTENSION SERVICES IN ENGINEERING: IMPROVING INSTRUCTION AND MENTORING TO RETAIN UNDERGRADUATE WOMEN

AUTOMATICALLY VERIFYING TEMPORAL ALIGNMENT OF TRANSFORMED SOFTWARE

BUILD IT UNDERWATER ROBOTICS SCALE UP FOR STEM LEARNING AND WORKFORCE DEVELOPMENT (BISU)

MUSICA: MUSICAL IMPROVISING COLLABORATIVE AGENT

CENTER FOR EXCELLENCE FOR MARITIME, ISLAND AND EXTREME/REMOTE ENVIRONMENTS SECURITY(CSR)

DYNAMIC TRACER KINETIC MODEL TO DETECT PRECLINICAL DIABETIC RETINOPATHY (DR) - PROJECT SUMMARY DIABETIC RETINOPATHY (DR) IS ONE OF THE MOST COMMON COMPLICATIONS ASSOCIATED WITH DIABETES. DETECTION OF CLINICAL DR SIGNS CAN TAKE SEVERAL YEARS FROM THE ONSET OF DIABETES; HENCE, THE LONG PRECLINICAL PHASE SHOULD PROVIDE A WINDOW TO APPLY INTERVENTIONS THAT CAN SLOW OR PREVENT PROGRESSION TO CLINICAL ENDPOINT (MILD TO SEVERE VISUAL IMPAIRMENT). IN FACT, EARLY DETECTION AND TREATMENT OF DR CAN PREVENT MORE THAN 90% OF VISION LOSS. HOWEVER, THE CURRENT UNMET CLINICAL CHALLENGE IS FINDING AN APPROPRIATE TOOL OR TECHNOLOGY TO DETECT PRECLINICAL SIGNS (BIOMARKERS) OF DR. SINCE THE RETINAL VESSELS ARE EARLY AND PREVALENT TARGETS OF DIABETIC DAMAGE, SENSITIVE IDENTIFIERS OF STRUCTURAL AND FUNCTIONAL BLOOD VESSEL CHANGES HOLD GREAT POTENTIAL AS BIOMARKERS. RECENT ADVANCES IN RETINAL IMAGING TECHNOLOGY HAVE ALLOWED A BETTER VISUALIZATION OF VESSEL CHARACTERISTICS. ADAPTIVE OPTICS SCANNING LASER OPHTHALMOSCOPY (AOSLO) AND OCT ANGIOGRAPHY (OCTA) STUDIES RECENTLY SUGGESTED THAT THERE MAY BE A TRANSITIONAL VASCULAR REMODELING DURING THE PRECLINICAL PHASE IN DIABETIC PATIENTS. THOUGH THE MAIN BENEFIT OF THESE TECHNOLOGIES IS THE NON-INVASIVE NATURE OF DATA ACQUISITION, THERE ARE LIMITATIONS (E.G., LONG SCAN TIMES, LIMITED FIELD-OF-VIEW, MOTION ARTIFACTS AND NEED FOR AN EXPERT OPERATOR) THAT PREVENT THESE TECHNOLOGIES TO BE EFFECTIVE PRECLINICAL DETECTION TOOLS TO BE USED IN A CLINICAL SETTING. THEREFORE, THERE IS A GREAT NEED FOR ENHANCED DETECTION SENSITIVITY AND QUANTITATIVE MEANS TO ANALYZE THE EARLY PRECLINICAL VASCULATURE CHANGES THAT CAN BE READILY TRANSLATED INTO CLINICAL PRACTICE. TO ADDRESS THIS CRITICAL UNMET CLINICAL NEED, WE HAVE DEVELOPED A NOVEL DYNAMIC TRACER KINETIC MODEL TO MEASURE QUANTITATIVELY VASCULAR PERMEABILITY AND BLOOD FLOW CHANGES BASED ON FLUORESCEIN VIDEO-ANGIOGRAPHY (FVA). THE APPROACH IS IMMEDIATELY TRANSLATABLE TO FVA DATA COLLECTED IN PATIENTS AS DEMONSTRATED BY OUR PRELIMINARY DATA. IN THIS PROPOSAL, WE WILL DEMONSTRATE THAT OUR DYNAMIC TRACER KINETIC MODEL CAN DETECT PRECLINICAL DR WITH A HIGHER SENSITIVITY AND SPECIFICITY THAN OTHER RETINAL IMAGING MODALITIES SUCH AS OCTA AND AOSLO. SPECIFIC AIM 1 WILL OPTIMIZE/VALIDATE THE RETINAL VASCULAR PERMEABILITY AND BLOOD FLOW MEASUREMENTS AGAINST GOLD STANDARD TECHNIQUES OF PERMEABILITY (EVANS-BLUE) AND BLOOD FLOW (MICROSPHERES). SPECIFIC AIM 2 WILL DEMONSTRATE THAT LONGITUDINAL PRECLINICAL CHANGES IN THE RETINAL VASCULAR PERMEABILITY AND BLOOD FLOW DETECTED BY OUR MODEL WILL OCCUR BEFORE CLINICAL RETINOPATHY IN DIABETIC RODENT MODEL. SPECIFIC AIM 3 WILL CHARACTERIZE LONGITUDINAL CHANGES IN RETINAL VASCULAR PERMEABILITY AND BLOOD FLOW IN BOTH NORMAL SUBJECTS AND DIABETIC PATIENTS. SPECIFIC AIM 4 WILL DEMONSTRATE HIGHER SENSITIVITY OF PRECLINICAL DR DETECTION BY THE DYNAMIC TRACER KINETIC MODEL OVER OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY (OCTA) AND ADAPTIVE OPTICS SCANNING LASER OPHTHALMOSCOPY (AOSLO) IN DIABETIC PATIENTS WITHOUT CLINICAL RETINOPATHY (DMNODR).

MARITIME SECURITY CENTER (YEAR 3)

BIOACTIVE NERVE GRAFTS FOR PERIPHERAL NERVE REGENERATION

MULTI-CONTRAST DYNAMIC OPTICAL IMAGING TO ADVANCE LIVE DEVELOPMENTAL BIOLOGY - PROJECT SUMMARY/ABSTRACT IMAGING IS ESSENTIAL FOR THE STUDY OF DEVELOPMENTAL BIOLOGY. IN PARTICULAR, OPTICAL IMAGING, WITH ITS HIGH RESOLUTION, HAS BEEN MAKING REVOLUTIONARY IMPACTS ON OUR UNDERSTANDING OF BIOLOGICAL DEVELOPMENT. TO A LARGE DEGREE, THE IMAGING CAPABILITY DEFINES WHAT CAN BE STUDIED IN DEVELOPMENTAL BIOLOGY. FROM 2D TO 3D, FROM STATIC TO DYNAMIC, ADVANCEMENTS IN OPTICAL IMAGING HAVE ENABLED US TO CONNECT MOLECULAR GENETICS WITH VOLUMETRIC MORPHOGENESIS AND HAVE MARKED AN EXCITING ERA OF STUDYING THE UNDERLYING MECHANISMS IN THE CONTEXT OF DYNAMIC DEVELOPMENTAL PROCESS. BIOLOGICAL DEVELOPMENT IS FASCINATING. FROM A SINGLE CELL TO A MULTI-BILLION CELL SYSTEM, CELLS WITH VIRTUALLY IDENTICAL GENES ACQUIRE DIFFERENT FATES AND ARE ABLE TO EXHIBIT DIVERSE BEHAVIORS AND FUNCTIONS. TO ELUCIDATE THIS COMPLEX PROCESS, TO DISSECT THE MECHANISTIC LINK BETWEEN GENOTYPES AND PHENOTYPES, AND TO DEFINE THE ROLES OF BIOPHYSICAL, BIOCHEMICAL AND BIOMECHANICAL FACTORS IN THE ORGANISMAL GROWTH AND PHYSIOLOGY, MULTI-CONTRAST IMAGING, CAPABLE OF PROBING AND BRIDGING A WIDE RANGE OF BIOLOGICAL INFORMATION, IS IMPERATIVE AND HOLDS THE PROMISE FOR THE NEXT REVOLUTION IN THE STUDY OF DEVELOPMENTAL BIOLOGY. UNDERSTANDING OF DEVELOPMENT REQUIRES DIFFERENT MODEL SYSTEMS, EACH WITH ADVANTAGES IN PURSUIT OF SPECIFIC QUESTIONS. AMONG THESE, THE MOUSE IS THE PREMIER MAMMALIAN MODEL WITH WELL-ESTABLISHED GENETIC TOOLS FOR MUTAGENESIS STRATEGIES AND MODELING OF HUMAN DISEASES. STUDIES ON MICE CAN PRODUCE INSIGHTS THAT ARE HIGHLY RELEVANT TO HUMAN; HOWEVER, MANY IMPORTANT DEVELOPMENTAL QUESTIONS CANNOT CURRENTLY BE STUDIED USING THE MOUSE MODEL, LARGELY BECAUSE IT IS DIFFICULT OR IMPOSSIBLE TO IMAGE THE REQUIRED INFORMATION. THIS LACK OF PROPER IMAGING APPROACH ACTS AS A CRITICAL HURDLE, ESPECIALLY FOR LIVE STUDIES OF THE DEVELOPING CELLS, TISSUES AND ORGANS, WHICH ARE ESSENTIAL FOR A COMPREHENSIVE UNDERSTANDING OF DEVELOPMENT. THE GOAL OF THIS RESEARCH PROGRAM IS TO ESTABLISH A MULTI-CONTRAST, HIGH-RESOLUTION DYNAMIC IMAGING PLATFORM TO ADVANCE LIVE DEVELOPMENTAL BIOLOGY, ESPECIALLY IN THE MOUSE MODEL. OUR TECHNICAL INNOVATIONS ARE BASED ON OPTICAL COHERENCE TOMOGRAPHY (OCT), A HIGH-SPEED IMAGING MODALITY WITH MICRO-SCALE RESOLUTION AND MILLIMETER-LEVEL DEPTH. RECENTLY, WE DEMONSTRATED LIVE 4D (3D+TIME) STRUCTURAL AND FUNCTIONAL OCT IMAGING OF MOUSE EMBRYOS AT A VARIETY OF TIME SCALES, REVEALING UNPRECEDENTED MAMMALIAN DEVELOPMENTAL DYNAMICS. BUILDING ON THIS, WE WILL PURSUE THREE PROJECTS TO PIONEER 3D-REGISTERED AND INTEGRATED STRUCTURAL, FUNCTIONAL, MOLECULAR AND BIOMECHANICAL CONTRASTS FOR LIVE AND DYNAMIC STUDIES OF MAMMALIAN DEVELOPMENT. THIS RESEARCH PROGRAM WILL GENERATE A NEW FRONTIER IN THE STUDY OF DEVELOPMENTAL BIOLOGY AND WILL MAKE A MAJOR STEP FORWARD IN UNDERSTANDING OF MAMMALIAN DEVELOPMENT.

THE ATLANTIC CENTER FOR THE INNOVATIVE DESIGN AND CONTROL OF SMALL SHIPS

FLOATING OSCILLATING SURGE WAVE ENERGY CONVERTER USING CONTROLLABLE EFFICIENT POWER TAKEOFF SYSTEM

CENTERS OF EXCELLENCE MARITIME SECURITY CENTER

NEW AWARD--MICHROCHANNEL REACTOR SYSTEM FOR CATALYTIC HYDROGENATION

SCC-IRG TRACK 1: ASSESSING THE POTENTIAL FOR TRANSACTIVE ENERGY COMMUNITIES IN RURAL NEW HAMPSHIRE -THIS PROJECT ADVANCES OUR KNOWLEDGE OF HOW TO DEVELOP AND IMPLEMENT TRANSACTIVE ENERGY SERVICES IN RURAL COMMUNITIES. A TRANSACTIVE ENERGY SERVICE IS AN ENERGY-SHARING, REAL-TIME PRICING MARKET THAT EXCHANGES ELECTRICITY AMONG RETAIL CUSTOMERS AND POWER PRODUCERS THAT COULD INCLUDE LARGE GENERATION COMPANIES AND HOUSEHOLDS WITH ROOFTOP OR BACKYARD SOLAR. TRANSACTIVE ENERGY SERVICES HAVE LONG BEEN RECOGNIZED AS POTENTIALLY USEFUL FOR DECARBONIZING THE ELECTRIC GRID, ENHANCING COMMUNITY RESILIENCE TO SUPPLY SHORTAGES, EXTREME WEATHER, AND NATURAL DISASTERS, AND REDUCING ELECTRICITY RATES FOR EVERYDAY CONSUMERS. THIS PROJECT AIMS TO ASSESS THE SOCIAL AND TECHNICAL FACTORS INFLUENCING THE POTENTIAL FOR IMPLEMENTING TRANSACTIVE ENERGY SERVICES. THE PROJECT IS INVESTIGATING THE POTENTIAL FOR A TRANSACTIVE ENERGY SERVICE IN RURAL NEW HAMPSHIRE WITH A COLLABORATION OF COMMUNITY POWER PARTNERS. THROUGH SURVEYS, FOCUS GROUPS, AND INTERVIEWS, THE RESEARCH TEAM IS STUDYING THE TECHNICAL AND SOCIAL PSYCHOLOGICAL FACTORS THAT WILL INFLUENCE RURAL NEW HAMPSHIRE RESIDENTS' WILLINGNESS TO ENROLL IN THE TRANSACTIVE ENERGY SERVICE. IT IS EXAMINING THE TECHNICAL AND SOCIAL FEATURES AND FACTORS THAT CAN PRODUCE A MARKET THAT IS SOCIALLY BENEFICIAL, TECHNICALLY RELIABLE, AND ENVIRONMENTALLY SUSTAINABLE. AND IT IS EXAMINING HUMAN-MACHINE INTERACTIONS TO PRODUCE AN ARTIFICIALLY-INTELLIGENT IN-HOME AUTOMATION SYSTEM THAT FACILITATES RURAL NEW HAMPSHIRE RESIDENTS' PARTICIPATION IN THE TRANSACTIVE ENERGY SERVICE. THE PROJECT IS ALSO ASSESSING IF THE KNOWLEDGE OF TRANSACTIVE ENERGY SERVICE DESIGN AND IMPLEMENTATION GENERATED IN NEW HAMPSHIRE COULD BE SCALED TO, TRANSFERRED TO, AND SUSTAINED BY OTHER COMMUNITY PARTNERSHIPS OR COALITIONS IN THE UNITED STATES. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

NOVEL ACYLBORONS AND ALPHA-HYDROXY BORONS TO ENABLE MODULAR, REGIO- AND STEREOCONTROLLED SYNTHESIS OF BIOACTIVE MOLECULES AND PROTEIN CONJUGATES - PROJECT SUMMARY/ABSTRACT THE LONG-TERM GOAL OF MY RESEARCH LABORATORY IS TO ESTABLISH STRATEGIES THAT ALLOW THE SYNTHESIS OF PREVIOUSLY INACCESSIBLE REGIO-/STEREODEFINED ORGANOBORONS TO ULTIMATELY ENABLE THE LEGO-LIKE CONSTRUCTION OF C(SP3)-RICH BIOACTIVE MOLECULES AND PROTEIN CONJUGATES. MODULAR SYNTHETIC STRATEGIES USING INTERCHANGEABLE BUILDING BLOCKS ARE EXPECTED TO ENABLE A GENERALIZED ROUTE TO THE TARGETED COMPOUND CLASS WHICH IS CRUCIAL FOR OPTIMIZING ITS BIOLOGICAL ACTIVITY. ORTHOGONALLY FUNCTIONALIZED VINYLIC OR AROMATIC HALO-ORGANOBORONS HAVE PLAYED A CRITICAL ROLE IN MANY MODULAR SYNTHETIC ROUTES TO NATURAL PRODUCTS. IN CONTRAST, STRATEGIES TO CONSTRUCT MULTIFUNCTIONAL AND STEREODEFINED ACYLBORONS/ALKYL BORON BUILDING BLOCKS AND THEIR APPLICATIONS FOR MODULAR SYNTHESIS OF C(SP3)-RICH MOLECULAR SCAFFOLDS AND BIOCONJUGATES REMAIN UNDEREXPLORED. THE RESEARCH PROJECTS DESCRIBED IN THIS PROPOSAL WILL PROVIDE A PLATFORM TO ACHIEVE THE ABOVE BROADER GOAL BY ESTABLISHING A VERSATILE ACYLBORON/ALPHA-HYDROXY BORON-BASED PARADIGM TO OPEN-UP ACCESS TO SEVERAL UNIQUE ORGANOBORONS HAVING BROAD APPLICATIONS IN MEDICINAL CHEMISTRY AND CHEMICAL BIOLOGY. ACYLBORONS REPRESENT AN UNDEREXPLORED CLASS OF ORGANOBORONS WHOSE EXISTENCE AND REMARKABLE SYNTHETIC UTILITY IS BEGINNING TO EMERGE ONLY RECENTLY. WE PREVIOUSLY REPORTED AN UNSYMMETRICAL DIBORON-BASED APPROACH TO CONSTRUCT RARE ACYLBORONS INCLUDING THE FIRST EXAMPLE OF AN ALPHA,BETA-UNSATURATED ACYL BORON. OUR RECENT PRELIMINARY DATA SUGGESTS THAT ALPHA,BETA-UNSATURATED ACYL BORONS AND ALPHA-HYDROXY BORONS ARE POWERFUL INTERMEDIATES TO ACCESS ORTHOGONALLY FUNCTIONALIZED, REGIO- AND STEREODEFINED ORGANOBORONS. BUILDING UPON OUR PUBLISHED WORK AND PRELIMINARY DATA, WE WILL DEVELOP GENERAL METHODS FOR SYNTHESIS AND APPLICATION OF SEVERAL NEW TYPES OF MULTIFUNCTIONAL ACYLBORONS AND ALPHA-HYDROXY BORONS TO ULTIMATELY PROVIDE ENANTIOENRICHED ORGANOBORONS THAT WOULD BE DIFFICULT TO PREPARE USING EXISTING METHODS. WE WILL DEMONSTRATE THE UNIQUE BENEFIT OF THESE NOVEL BUILDING BLOCKS TO INSTALL RARE SUBSTITUTION PATTERNS ON BIOACTIVE MOLECULES AND TO ENABLE A MODULAR SYNTHETIC APPROACH TO CHIRAL FRAMEWORKS FOUND IN MEDICINALLY IMPORTANT COMPOUNDS. IN A COMPLEMENTARY RESEARCH DIRECTION, WE WILL DEVELOP A NEW CLASS OF MUTUALLY ORTHOGONAL BIOCONJUGATION AGENTS THAT ARE EXPECTED TO ALLOW I) SIMULTANEOUS PROBING OF MULTIPLE PROTEIN- PROTEIN INTERACTIONS AND II) PREPARATION OF HOMOGENEOUS AND STABLE BIOCONJUGATES.

FOSTERING ADAPTIVE EXPERTISE TO INCREASE RETENTION AND GRADUATION OF LOW-INCOME STEM STUDENTS

TAS::57 3600::TAS 'RADIATIVE AND DISPERSIVE BEHAVIOR OF INSTABILITIES IN A HIGHLY-COOLED HYPERSONIC BOUNDARY LAYER'

STRUCTURE, SPECTRA, AND ROLES OF METAL AND ACTIVE SITE IN HNO HEME PROTEIN COMPLE

AN INVESTIGATION OF THE IMPACT OF STRENGTHENING THE "T" AND "E" COMPONENTS OF STEM IN HIGH SCHOOL BIOLOGY AND CHEMISTRY COURSES

COLLABORATIVE RESEARCH: GCR: INFECTION-RESISTING RESORBABLE SCAFFOLDS FOR ENGINEERING HUMAN TISSUE -TISSUE ENGINEERING IS A THOUGHT-PROVOKING CONCEPT MADE COMPELLING BY THE NEED TO REPLACE FAILED, DAMAGED, OR DEFECTIVE BODY PARTS. UNLIKE THE MORE MATURE FIELD OF TRADITIONAL MEDICAL-DEVICE DEVELOPMENT (E.G., JOINT REPLACEMENT), TISSUE ENGINEERING IS YOUNG AND EVOLVING. THIS PROJECT CAN THUS CHANGE THE ESTABLISHED TISSUE-ENGINEERING PARADIGM TO NOT ONLY ADDRESS THE DEVELOPMENT OF HEALTHY TISSUE (ASSOCIATED WITH HEALING) BUT SIMULTANEOUSLY ADDRESS THE NEED TO INHIBIT BACTERIAL COLONIZATION (ASSOCIATED WITH INFECTION). A CONVERGENT TEAM OF RESEARCHERS WITH EXPERTISE IN MICROBIOLOGY, POLYMER SCIENCE, BIOMATERIALS SCIENCE, COMPUTATIONAL CHEMISTRY, VETERINARY MEDICINE, AND MEDICAL-DEVICE DEVELOPMENT WILL DEVELOP A NEW AND FLEXIBLE APPROACH TO INFECTION CONTROL WITHIN A RESORBABLE SCAFFOLD FOR TISSUE ENGINEERING. THE RESEARCH PLAN ENCORPORATES THREE SYNERGISTIC RESEARCH THRUSTS WHICH WILL CONVERGE AROUND A SPECIFIC TESTBED, NAMELY A NEW SCAFFOLD DESIGNED TO REGROW HARD TISSUE THAT SIMULTANEOUSLY RESISTS BACTERIAL COLONIZATION. TO MIMIC THE EXTRACELLULAR MATRIX, THRUST 1 WILL EXPLOIT 3D PRINTING TO ADDITIVELY CREATE FIBER-BASED SCAFFOLDS WITH CONTROLLABLE FIBER SIZE/SPACING USING COMBINATIONS OF RESORBABLE POLYMERS TOGETHER WITH SIGNALING FACTORS TO INFLUENCE STEM-CELL DIFFERENTIATION. THRUST 2, USING SYNERGISTIC COMPUTATIONAL AND EXPERIMENTAL APPROACHES, WILL EXPLORE FUNDAMENTAL CONCEPTS OF POLYELECTROLYTE COMPLEXATION AND DIRECTED SELF-ASSEMBLY TO RENDER THESE SCAFFOLDS SELF-DEFENSIVE (ABLE TO RELEASE ANTIMICROBIALS ONLY IF, WHEN, AND WHERE THERE IS A BACTERIAL CHALLENGE). THRUST 3 WILL EMPLOY LAB-ON-A-CHIP CONCEPTS TO UNDERSTAND THE COMPETITION BETWEEN MAMMALIAN CELLS AND BACTERIA AND, IN PHASE 2 OF PROJECT, INCLUDE SMALL-ANIMAL INFECTION MODELS ABLE TO RECAPITULATE A COMPLEX PHYSIOLOGICAL RESPONSE. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

MACHINE LEARNING METHODS TO INDIVIDUALIZE POWERED ORTHOTIC INTERVENTION FOR IMPROVED FUNCTIONAL RECOVERY AFTER LOWER EXTREMITY TRAUMA

SFS CYBERSECURITY SCHOLARS PROGRAM

DEEP LEARNING-BASED DIAGNOSIS OF RETINOPATHY OF PREMATURITY - PROJECT SUMMARY RETINOPATHY OF PREMATURITY (ROP) IS A LEADING YET LARGELY PREVENTABLE CAUSE OF CHILDHOOD BLINDNESS GLOBALLY. THERE IS AN UNMET NEED FOR TIMELY AND CONSISTENT DIAGNOSIS OF TREATMENT-REQUIRED ROP, SUCH AS PLUS DISEASE OF ROP. A DEEP LEARNING-BASED DIAGNOSTIC TOOL WOULD BE ADVANTAGEOUS TO REDUCE THE DEPENDENCE ON CLINICAL EXPERTISE DURING THE DIAGNOSTIC PHASE. HOWEVER, THERE ARE TWO SIGNIFICANT CHALLENGES IN TRAINING DEEP LEARNING- BASED APPROACHES. THE FIRST CHALLENGE IS THAT THE PERFORMANCE OF DEEP LEARNING-BASED DIAGNOSIS IS HINDERED BY LIMITED DATA AVAILABILITY IN THE TRAINING PHASE. THE SIZE OF THE TRAINING DATA SET DIRECTLY INFLUENCES TRAINING EFFICIENCY AND THE ABILITY TO GENERALIZE. SINCE PREMATURE BABIES ARE VULNERABLE POPULATIONS, IMAGES FROM THESE BABIES ARE INHERENTLY LIMITED AND INSUFFICIENT TO COVER ALL POTENTIAL SCENARIOS OF ROP FOR TRAINING. THE SECOND CHALLENGE IS THE VARIATION IN IMAGE QUALITY DUE TO DIFFERENCES IN ACQUISITION SYSTEMS. THE DIFFERENCES IN QUALITY DATA SETS WILL IMPACT THE DEEP LEARNING MODEL. THEY WILL LIKELY FAIL TO PRODUCE ACCURATE DIAGNOSES DUE TO THE LACK OF ALIGNMENT BETWEEN THE TRAINING DATA AND DATA ACQUIRED FROM OTHER PLATFORMS. THEREFORE, THERE IS A GREAT NEED FOR NEW METHODS AND TECHNOLOGY TO INCREASE THE TRAINING SET AND IMPROVE OR NORMALIZE THE IMAGE QUALITY TO DEVELOP A DIAGNOSTIC DEEP LEARNING MODEL FOR ROP. TO ADDRESS THIS CRITICAL UNMET CLINICAL NEED, WE HAVE DEVELOPED TECHNOLOGY TO AUGMENT THE TRAINING DATASET USING ANIMAL-TO-HUMAN (A2H) TRANSLATED IMAGES AND IMPLEMENT QUALITY CONTROL BY CROSS-PLATFORM RETINAL IMAGE STANDARDIZATION PROCESS (CRISP). IN THIS STUDY, WE WILL DEMONSTRATE THAT OUR A2H TRANSLATED IMAGES WILL EXHIBIT RETINAL VASCULAR PATTERNS OF PLUS DISEASE OF ROP. THESE TRANSLATED IMAGES CAN BE USED TO TRAIN THE DEEP LEARNING-BASED ROP DIAGNOSTIC MODEL. WE WILL DEMONSTRATE THAT OUR CRISP MODEL CAN RESOLVE THE DIFFERENCE BETWEEN DIFFERENT IMAGING ACQUISITION SYSTEMS AND/OR OVERALL IMAGE QUALITY. WE WILL EVALUATE THE IMPACT OF QUALITY CONTROL ON THE PERFORMANCE OF ROP DIAGNOSIS. SPECIFIC AIM 1 IS TO OPTIMIZE AND TEST AN ANIMAL-TO-HUMAN MODEL USING AN EXISTING RETINAL IMAGE DATASET. SPECIFIC AIM 2 IS TO ACQUIRE A ROBUST SET OF LONGITUDINAL ANIMAL ROP IMAGES USING TWO ANIMAL MODELS AND THREE DIFFERENT IMAGING PLATFORMS AND MANUALLY ANNOTATE THE IMAGES FOR THE TRAINING. SPECIFIC AIM 3 IS TO DEVELOP AND TEST A CRISP MODEL ON QUALITY CONTROL. SPECIFIC AIM 4 IS TO VALIDATE THE A2H MODEL TO DIAGNOSE ROP AND EVALUATE THE COMBINATION OF A2H AND CRISP AS A UNIVERSAL TOOL TO IMPROVE LEARNING PERFORMANCE. OUR PROPOSED METHOD COULD POTENTIALLY IMPROVE THE DIAGNOSIS OF ROP. FURTHERMORE, OUR INNOVATIVE APPROACH OF USING ANIMAL DATA TO ENHANCE HUMAN STUDIES COULD ALSO BE APPLIED TO OTHER CLINICAL STUDIES WHERE HUMAN DATA AND CLINICAL LABELING RESOURCES ARE LIMITED. FINALLY, OUR QUALITY CONTROL TOOL THAT CAN STANDARDIZE THE IMAGE QUALITY WILL ALLOW OPPORTUNITIES FOR MORE ROBUST IMAGE ANALYSIS AND POTENTIALLY APPLICABLE IN TELEMEDICINE.

COOPERATIVE AGREEMENTS ARE AWARDED TO NONPROFIT INSTITUTIONS OF HIGHER EDUCATION UNDER THE COMPETITIVE ACADEMIC AGREEMENT PROGRAM (CAAP). GRANT FUNDING IS USED TO RESEARCH INNOVATIVE SOLUTIONS IN VARIOUS PIPELINE SAFETY TOPIC AREAS, THAT ARE EXPECTED TO BENEFIT THE ENTIRE NATION BY ENHANCING PIPELINE SAFETY. NORTH DAKOTA STATE UNIVERSITY AND RUTGERS UNIVERSITY HAVE BEEN IDENTIFIED AS SUBRECIPIENTS. ''ENHANCING KNOWLEDGE AND TECHNOLOGY TO PREVENT AND MITIGATE RISKS OF STRESS CORROSION CRACKING (SCC) FOR PIPELINE INTEGRITY MANAGEMENT''

DUAL LAYER MONOLITH ATR OF PYROLYSIS OIL FOR DISTRIBUTED SYNTHESIS GAS PRODUCTION

EXPLORING MULTIDIMENSIONAL SPATIAL-TEMPORAL HYDROPOWER OPERATIONAL FLEXIBILITIES BY MODELING AND OPTIMIZING WATER-CONSTRAINED CASCADING HYDROELECTRIC SYSTEMS

HIGH PERFORMANCE COMPUTER CLUSTER ENABLING FLOOD MITIGATION AND COASTAL RESILIENCE THROUGHOUT NEW JERSEY

THE NEW YORK BIGHT SHELF - HARBOR DYNAMICS STUDY

SCH: INT: COLLABORATIVE RESEARCH: AGING IN PLACE THROUGH ENHANCED MOBILITY AND SOCIAL CONNECTEDNESS: AN INTEGRATED ROBOT AND WEARABLE SENSOR APPROACH

SCH: INT: COLLABORATIVE RESEARCH: UNITING CAUSAL AND MENTAL MODELS FOR SHARED DECISION-MAKING IN DIABETES

RISK-AVERSE LEARNING AND CONTROL FOR DISTRIBUTED DYNAMICAL SYSTEMS WITH PARTIAL INFORMATION

PREDICTING AND MANAGING COASTAL FLOODING AND ITS IMPACTS ON NATURAL AND BUILT INFRASTRUCTURE IS IMPORTANT TO REDUCE LIFE, ECONOMIC AND ECOLOGICAL LOSSES. THE PROPOSED PROJECT WILL LEVERAGE STEVENS INSTITUTE OF TECHNOLOGYS EXPERTISE IN ASSESSING AND MONITORING FLOOD HAZARDS AND ENHANCE ITS DYNAMIC UNDERWATER COASTAL KINEMATIC SURVEYING SYSTEM (DUCKS) AND OPERATIONAL STEVENS FLOOD ADVISORY SYSTEM (SFAS) TO CREATE A HIGH-RESOLUTION, MULTI-PLATFORM, RAPIDLY DEPLOYABLE, COASTAL EXTREME EVENT OBSERVING SYSTEM. THE STEVENS EXTREME EVENT COASTAL PREPAREDNESS AND RESPONSE SYSTEM (SEECPRS) WOULD ENABLE THE COLLECTION OF CRITICAL, PERISHABLE DATA BEFORE, DURING, AND AFTER EXTREME COASTAL FLOODING EVENTS. AS A STORM APPROACHES, SEECPRS LIGHT DETECTION AND RANGING (LIDAR) ASSETS WILL BE DEPLOYED IN CRITICAL AREAS TO COLLECT ELEVATION DATA TO IMPROVE THE ACCURACY OF FORECAST FLOOD DEPTHS AND EXTENTS. DURING A STORM, THESE SAME ASSETS WILL BE USED TO HELP ASSESS AND IMPROVE FUTURE MODEL PREDICTIONS. AFTER A STORM, SEECPRS WILL BE USED TO RAPIDLY ASSESS THE DAMAGE TO NATURAL AND BUILT INFRASTRUCTURE ON BOTH LAND AND WATER, WHICH CAN BE CRITICAL FOR RESUMING NORMAL ACTIVITIES AND REDUCING ECONOMIC LOSSES.

PERSISTENT MARITIME QUANTUM KEY DISTRIBUTION

CAREER: ADAPTIVE SONIFICATION TO IMPROVE BALANCE DURING EVERYDAY MOBILITY

HARNESSING PATIENT GENERATED DATA TO FIND CAUSES AND EFFECTS OF DIET IN PREGNANCY

IUCRC PHASE I STEVENS: CENTER FOR RESEARCH TOWARD ADVANCING FINANCIAL TECHNOLOGIES (CRAFT)

TURBULENCE QUANTITIES IN SUPERSONIC AND HYPERSONIC FLOWS

ADAPTING TESTED SPATIAL SKILLS CURRICULUM TO ON-LINE FORMAT FOR COMMUNITY COLLEGE INSTRUCTION: A CRITICAL LINK TO RETAIN TECHNOLOGY STUDENTS

CENTER FOR EXCELLENCE FOR MARITIME, ISLAND AND EXTREME/REMOTE ENVIRONMENTS SECURITY

COLLABORATIVE RESEARCH: SHF: MEDIUM: CO-OPTIMIZING SPECTRAL ALGORITHMS AND SYSTEMS FOR HIGH-PERFORMANCE GRAPH LEARNING -EMERGING GRAPH LEARNING TECHNIQUES HAVE SHOWN PROMISING RESULTS FOR VARIOUS IMPORTANT APPLICATIONS SUCH AS COMMUNITY DETECTION, DRUG DISCOVERY, AND ELECTRONIC DESIGN AUTOMATION (EDA). HOWEVER, EVEN THE STATE-OF-THE-ART GRAPH LEARNING METHODS CANNOT SCALE TO LARGE DATA SETS DUE TO THEIR HIGH ALGORITHM COMPLEXITY. FOR EXAMPLE, THE LATEST GRAPH NEURAL NETWORK (GNN) ALGORITHMS COLLECTIVELY AGGREGATE FEATURE INFORMATION FROM THE NEIGHBORHOOD OF EACH NODE, WHICH NOT ONLY DRASTICALLY INCREASES THE NUMBER OF COMPUTATIONS AMONG NODES BUT ALSO LEADS TO HIGH MEMORY USAGE FOR STORING THE INTERMEDIATE RESULTS. HENCE MOST GRAPH LEARNING ALGORITHMS CANNOT EFFICIENTLY HANDLE LARGE-SCALE PROBLEMS DUE TO THEIR HIGH COMPUTATION AND STORAGE COSTS, NOT TO MENTION THE REAL-WORLD GRAPHS THAT MAY INVOLVE BILLIONS OF EDGES. THIS PROJECT AIMS AT ADDRESSING THE MOST PRESSING CHALLENGES IN MODERN GRAPH LEARNING TASKS BY INVESTIGATING HIGH-PERFORMANCE SPECTRAL GRAPH ALGORITHMS AND SYSTEMS BASED ON THE LATEST THEORETICAL BREAKTHROUGHS. UNLIKE PRIOR THEORETICAL STUDIES ON SPECTRAL GRAPH THEORY THAT PUT LESS FOCUS ON PRACTICAL ALGORITHM IMPLEMENTATIONS AND APPLICATIONS, THE INVESTIGATORS OF THIS PROJECT WILL DEVELOP PRACTICALLY-EFFICIENT SPECTRAL GRAPH COMPRESSION ALGORITHMS TO BOOST THE EFFICIENCY AND SOLUTION QUALITY OF EXISTING GRAPH LEARNING METHODS THROUGH ALGORITHM AND SYSTEM CO-OPTIMIZATIONS BY TAKING ADVANTAGE OF THE LATEST HETEROGENEOUS COMPUTING DEVICES, SUCH AS GPUS, FPGAS, AND COMPUTATIONAL STORAGE DEVICES. THE OUTCOME OF THIS PROJECT WILL POTENTIALLY ADVANCE THE STATE OF THE ART IN SPECTRAL GRAPH THEORY, MACHINE LEARNING, DATA ANALYTICS, EDA, AS WELL AS HIGH-PERFORMANCE COMPUTING. THIS PROJECT IS ALSO LIKELY TO SPARK NEW RESEARCH IN OTHER RELATED COMPUTER SCIENCE AND ENGINEERING FIELDS SUCH AS COMPLEX SYSTEM/NETWORK MODELING, COMPUTATIONAL BIOLOGY, PRECISION MEDICINE, AND TRANSPORTATION NETWORKS. THE INVESTIGATORS WILL PARTNER WITH THE STEM AMBASSADOR PROGRAM AT STEVENS, AND THE DIVERSITY PROGRAMS IN ENGINEERING OFFICE AT CORNELL TO RECRUIT HIGHLY DIVERSIFIED UNDERGRADUATE AND GRADUATE STUDENTS TO PARTICIPATE IN THIS PROJECT, WHILE THE LATEST RESEARCH RESULTS WILL BE INTEGRATED INTO SEVERAL GRADUATE AND UPPER-DIVISION UNDERGRADUATE COURSES TO PREPARE A NEW GENERATION OF RESEARCHERS AND PRACTITIONERS IN HIGH-PERFORMANCE MACHINE LEARNING. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

PURPOSE: THROUGH THIS LEAD AND HEALTHY HOMES TECHNICAL STUDIES (LHHTS) AWARD, HUD IS FUNDING STUDIES TO IMPROVE HUD'S AND THE PUBLIC'S KNOWLEDGE OF HOUSING-RELATED HEALTH AND SAFETY HAZARDS AND TO IMPROVE OR DEVELOP NEW HAZARD ASSESSMENT AND CONTROL METHODS, WITH A FOCUS ON LEAD AND OTHER KEY RESIDENTIAL HEALTH AND SAFETY HAZARDS. HUD IS ESPECIALLY INTERESTED IN APPLICATIONS THAT WILL ADVANCE OUR KNOWLEDGE ON PRIORITY HEALTHY HOMES ISSUES BY ADDRESSING IMPORTANT GAPS IN THE SCIENCE RELATED TO THE ACCURATE AND EFFICIENT IDENTIFICATION OF HAZARDS AND THE IMPLEMENTATION OF COST-EFFECTIVE HAZARD MITIGATION. A LIST OF ALL OFFICE OF LEAD HAZARD CONTROL AND HEALTHY HOMES (OLHCHH) CITY AND STATE GRANTEES CAN BE FOUND BY SELECTING THE LINK BELOW, ON THE WEBSITE UNDER GRANTEE RESOURCES, SELECT OLHCHH GRANTEE CONTACT LIST FOR A LIST OF SELECTED GRANTEES. HTTPS://WWW.HUD.GOV/PROGRAM_OFFICES/HEALTHY_HOMES/PROGRAMS_DIVISION LEAD TECHNICAL STUDIES (LTS) THE OVERALL GOAL OF THE LEAD TECHNICAL STUDIES (LTS) GRANT PROGRAM IS TO GAIN KNOWLEDGE TO IMPROVE THE EFFICACY AND COST-EFFECTIVENESS OF METHODS FOR EVALUATION AND CONTROL OF RESIDENTIAL LEAD-BASED PAINT HAZARDS. THROUGH THIS PROGRAM, HUD IS WORKING TO FULFILL THE REQUIREMENTS OF SECTIONS 1051 AND 1052 OF THE RESIDENTIAL LEAD-BASED PAINT HAZARD REDUCTION ACT OF 1992 (TITLE X) (42 U.S.C. §§ 4854 AND 4854A) WHICH DIRECTS HUD TO CONDUCT RESEARCH ON TOPICS WHICH INCLUDE THE DEVELOPMENT OF IMPROVED METHODS FOR EVALUATING AND REDUCING LEAD-BASED PAINT HAZARDS IN HOUSING, AMONG OTHERS. THE RESULTS OF THE APPLICABLE ASPECTS OF LTS WILL BE USED IN PART TO UPDATE HUD'S GUIDELINES FOR THE EVALUATION AND CONTROL OF LEAD-BASED PAINT HAZARDS IN HOUSING (GUIDELINES) AND OTHER HUD POLICY GUIDANCE.; ACTIVITIES TO BE PERFORMED: LEAD TECHNICAL STUDIES (LTS): THE OVERALL GOAL OF THE LTS GRANT PROGRAM IS TO GAIN KNOWLEDGE TO IMPROVE THE EFFICACY AND COST-EFFECTIVENESS OF METHODS FOR EVALUATION AND CONTROL OF RESIDENTIAL LEAD-BASED PAINT HAZARDS. THE OVERALL OBJECTIVES INCLUDE BUT ARE NOT LIMITED TO THE STATUTORY REQUIREMENTS LISTED IN 1052 OF THE RESIDENTIAL LEAD-BASED PAINT HAZARD REDUCTION ACT OF 1992 (TITLE X) (42 U.S.C. §§ 4854 AND 4854A) WHICH DIRECTS HUD TO CONDUCT RESEARCH ON TOPICS WHICH INCLUDE THE DEVELOPMENT OF IMPROVED METHODS FOR EVALUATING AND REDUCING LEAD-BASED PAINT HAZARDS IN HOUSING, AMONG OTHERS. 1. DEVELOP IMPROVED METHODS FOR EVALUATING LEAD-BASED PAINT HAZARDS. 2. DEVELOP IMPROVED METHODS FOR REDUCING LEAD-BASED PAINT HAZARDS. 3. DEVELOP IMPROVED METHODS FOR MEASURING LEAD IN PAINT FILMS, DUST, AND SOIL. 4. ESTABLISH PERFORMANCE STANDARDS FOR VARIOUS DETECTION METHODS, INCLUDING SPOT TEST KIT. 5. ESTABLISH PERFORMANCE STANDARDS FOR LEAD-BASED PAINT HAZARD REDUCTION METHODS, INCLUDING THE USE OF ENCAPSULANTS. 6. ESTABLISH APPROPRIATE CLEANUP STANDARDS. 7. EVALUATE THE EFFICACY OF INTERIM CONTROLS IN VARIOUS SITUATIONS. 8. EVALUATE THE RELATIVE PERFORMANCE OF VARIOUS ABATEMENT TECHNIQUES. 9. EVALUATE THE LONG-TERM COST-EFFECTIVENESS OF INTERIM CONTROL AND ABATEMENT STRATEGIES. 10. ASSESS THE EFFECTIVENESS OF HAZARD EVALUATION AND REDUCTION ACTIVITIES. PREPARATION AND SUBMISSION OF A MINIMUM OF ONE REPORT OR A MANUSCRIPT FOR THE PUBLICATION IN A PEER-REVIEWED ACADEMIC JOURNAL FOLLOWING HUD ACCEPTANCE.; EXPECTED OUTCOMES: LEAD TECHNICAL STUDIES (LTS): EVALUATION OF THE EFFECTIVENESS OF SPECIFIC RESIDENTIAL LEAD HAZARD CONTROL INTERVENTIONS. THE EFFECTIVENESS OF LEAD HAZARD CONTROL INTERVENTIONS (I.E., INTERIM CONTROLS OR A COMBINATION OF INTERIM CONTROLS AND ABATEMENT) OVER VARIOUS TIME PERIODS FOLLOWING IMPLEMENTATION IS A TOPIC THAT HAS BEEN PRIMARILY COVERED THROUGH HUD’S EVALUATION OF THE HUD LEAD HAZARD CONTROL GRANT PROGRAM. RESEARCH THE VALUE OF LEAD RISK ASSESSMENTS WHEN TRIGGERED BY CHILDREN WITH BLOOD LEAD LEVELS (BLLS) AT OR NEAR CDC’S BLOOD LEAD REFERENCE VALUE OF 3.5 ΜG/DL. THE FREQUENCY AT WHICH LEAD BASED PAINT (LBP) HAZARDS ARE IDENTIFIED IN THE HOMES OF CHILDREN WITH THESE BLLS HAS NOT BEEN WELL DOCUMENTED. HUD IS INTERESTED IN SUPPORTING RESEARCH FOR CHILDREN WITH BLLS NEAR OR ABOVE THE CURRENT CDC BLOOD-LEAD REFERENCE VALUE OF 3.5 ΜG/DL (E.G., BLLS ? 3 ΜG/DL AND < 5 ΜG/DL). ANALYSIS OF AVAILABLE DATA AND DATABASES. HUD IS INTERESTED IN SUPPORTING RESEARCH USING EXISTING DATA TO ADDRESS KEY SCIENTIFIC ISSUES RELATED TO THE IDENTIFICATION AND CONTROL OF LEAD-BASED PAINT HAZARDS. HUD IS ALSO INTERESTED IN THE CREATIVE USE OF EXISTING DATABASES (E.G., CENSUS DATA, BLOOD-LEAD SCREENING DATA, ETC.) TO IMPROVE THE EFFICACY OF LEAD HAZARD CONTROL PROGRAMS. HUD ANTICIPATES THAT THE RESULTS OF PROGRAM-SUPPORTED STUDIES WILL HELP TO DEVELOP EVIDENCE-BASED APPROACHES THAT ARE COST-EFFECTIVE AND EFFICIENT AND WILL RESULT IN THE REDUCTION OF HEALTH THREATS FOR THE MAXIMUM NUMBER OF RESIDENTS AND CHILDREN AND OTHER VULNERABLE POPULATIONS (E.G., THE ELDERLY) IN LOW-INCOME HOUSEHOLDS. STUDY RESULTS ARE ALSO EXPECTED TO IMPROVE OUR UNDERSTANDING OF HOW SPECIFIC ASPECTS OF THE INDOOR ENVIRONMENT CAN AFFECT THE HEALTH OF RESIDENTS.; INTENDED BENEFICIARIES: FOR BOTH LTS AND HHTS, HUD ANTICIPATES THAT THE RESULTS OF PROGRAM-SUPPORTED STUDIES WILL HELP TO DEVELOP EVIDENCE-BASED APPROACHES THAT ARE COST-EFFECTIVE AND EFFICIENT AND WILL RESULT IN THE REDUCTION OF HEALTH THREATS FOR THE MAXIMUM NUMBER OF RESIDENTS AND CHILDREN AND OTHER VULNERABLE POPULATIONS (E.G., THE ELDERLY) IN LOW-INCOME HOUSEHOLDS (E.G., HOMEOWNERS, RENTAL PROPERTY OWNERS, RENTAL, AND PUBLIC HOUSING RESIDENTS. HUD IS ESPECIALLY INTERESTED IN APPLICATIONS THAT WILL ADVANCE OUR KNOWLEDGE ON PRIORITY HEALTHY HOMES ISSUES BY ADDRESSING IMPORTANT GAPS IN THE SCIENCE RELATED TO THE ACCURATE AND EFFICIENT IDENTIFICATION OF HAZARDS AND THE IMPLEMENTATION OF COST-EFFECTIVE HAZARD MITIGATION.; SUBRECIPIENT ACTIVITIES: THE SUBRECIPIENT ACTIVITIES ARE UNKNOWN AT THE TIME OF AWARD.

SEISMIC DETECTION OF BURIED LANDMINES

GENERATING ALTERNATIVES: ENHANCING CREATIVITY IN THE DESIGN OF INFORMATION SYSTEMS

PROACTIVE CONTROL OF THE METAL-CERAMIC INTERFACE BEHAVIOR OF THERMAL BARRIER COATINGS USING AN ARTIFICIAL ALPHA-ALUMINA TEMPLATE

TIME-RESOLVED, NON-INTRUSIVE MEASUREMENTS IN UNSTEADY HYPERSONIC FLOWS

ACES 2.0 EXPANDING STEVENS ACES: ACCESSING CAREERS IN ENGINEERING AND SCIENCE

DESIGNING CHEMICAL DISORDER IN SOLID-STATE SUPERIONIC CONDUCTORS

SPECEES: COOPERATIVE GREEN RF SENSING OVER SHARED SPECTRUM

RAISE-EQUIP: A CHIP-INTEGRATED PLATFORM FOR PHOTON-EFFICIENT QUANTUM COMMUNICATIONS

SOCS: CROWDSOURCING CREATIVITY: EXPERIMENTS IN DESIGN

COMPLEXATION PHENOMENA IN POLYELECTROLYTE MICROGELS

ENSURING THAT FOOD PRODUCTS ARE SAFE, NUTRITIOUS, AND OF HIGH QUALITY IS A CRITICAL PRIORITY FOR U.S. AGRICULTURE AND FOOD SYSTEMS. HOWEVER, CURRENT METHODS FOR ASSESSING FOOD QUALITY OFTEN RELY ON SLOW, LABOR-INTENSIVE, AND/OR DESTRUCTIVE TESTING. THESE CHALLENGES AFFECT PRODUCERS, PROCESSORS, RETAILERS, AND CONSUMERS, WITH IMPLICATIONS FOR ECONOMIC EFFICIENCY, FOOD SECURITY, AND ENVIRONMENTAL SUSTAINABILITY. THE GOAL OF THIS PROJECT IS TO ADDRESS THE NEED FOR A RAPID, NON-DESTRUCTIVE APPROACH TO FOOD QUALITY ASSESSMENT AND PREDICTION THAT CAN SUPPORT TIMELY DECISION-MAKING AND REDUCE LOSSES FROM WASTE AND INEFFICIENCIES.IN THIS PROJECT, WE PROPOSE TO COMBINE DATA SCIENCE AND ULTRA-WIDEBAND MICROWAVE IMAGING TO ENABLE EFFICIENT AND EFFECTIVE ANALYSIS OF LARGE-SCALE FOOD DATA. THIS APPROACH WILL ALLOW FOOD PRODUCTS TO BE EVALUATED WITHOUT CUTTING OR DAMAGING THEM, ENABLING RAPID ASSESSMENT OF FRESHNESS, INTERNAL STRUCTURE, AND EARLY SIGNS OF DETERIORATION. WE WILL USE MULTIPLE IMAGE RESOURCES AND DEVELOP TRUSTWORTHY DEEP LEARNING TECHNOLOGY THAT IS ROBUST ENOUGH TO BE APPLIED TO MULTIPLE FOOD TYPES. BY ANALYZING LARGE VOLUMES OF DATA AND CREATING DIGITAL REPRESENTATIONS (DIGITAL TWINS) OF FOOD PRODUCTS, THE SYSTEM WILL HELP PREDICT QUALITY CHANGES OVER TIME AND PROVIDE GUIDANCE FOR IMPROVED STORAGE AND PRESERVATION PRACTICES. WE EXPECT TO DEVELOP A SCALABLE, EFFICIENT TOOL THAT SUPPORTS DATA-INFORMED FOOD QUALITY MANAGEMENT, REDUCES FOOD WASTE, ENHANCES FOOD SAFETY, AND STRENGTHENS THE RESILIENCE AND SUSTAINABILITY OF AGRICULTURAL AND FOOD SYSTEMS.

ADVANCED AUTONOMY FOR UNMANNED SURFACE VEHICLES VIA DISTRIBUTIONAL REINFORCEMENT LEARNING

IMPROVED VENTILATION OF THE EDEMATOUS LUNG - PROJECT SUMMARY ACUTE RESPIRATORY DISTRESS SYNDROME (ARDS) IS TREATED BY MECHANICAL VENTILATION. MECHANICAL VENTILATION IS A LIFESAVING THERAPY BUT ALSO CAUSES ADDITIONAL VENTILATION INDUCED LUNG INJURY (VILI). IT IS NOT KNOWN WHETHER VILI IS ATTRIBUTABLE TO OVEREXPANSION OR CYCLIC COLLAPSE AND REOPENING OF LUNG TISSUE. IN THIS BIOENGINEERING PROJECT, WE AIM TO ELUCIDATE THE MICROMECHANICS OF THE VENTILATION INJURY MECHANISM. WE PROPOSE TO TEST VENTILATION SETTINGS THAT KEEP THE LUNG TISSUE EXPANDED, ALLOW COLLAPSE AND REOPENING OR PERMIT COLLAPSE WITHOUT REOPENING, AND THEN APPLY A NEW ELECTRICAL DETERMINATION OF ALVEOLAR-CAPILLARY BARRIER PERMEABILITY. THE NEW METHOD IS HIGHLY LOCALIZED AND INDEPENDENT OF REGIONAL EDEMA DEGREE. COMBINING INFORMATION FROM VENTILATION HISTORY AND PERMEABILITY CHARACTERIZATION, WE WILL DETERMINE CAUSE AND LOCATION OF INJURY.

SWIFT-SAT: UNLIMITED RADIO INTERFEROMETRY: A HARDWARE-ALGORITHM CO-DESIGN APPROACH TO RAS-SATELLITE COEXISTENCE -RADIO ASTRONOMY HAS TRANSFORMED THE PERCEPTION OF THE UNIVERSE, PROVIDING VALUABLE INSIGHTS INTO THE PROPERTIES AND BEHAVIORS OF GALAXIES, STARS, AND OTHER COSMIC EVENTS. AN ESSENTIAL REQUIREMENT OF RADIO ASTRONOMY SERVICE (RAS) IS ACCESS TO A SPECTRUM DEVOID OF RADIO FREQUENCY INTERFERENCE (RFI) FROM OTHER SOURCES. RFI CAN OBSCURE FAINT ASTRONOMICAL OBJECTS, CREATE FALSE SIGNALS, REDUCE THE SENSITIVITY OF RADIO TELESCOPES, AND LEAD TO SIGNIFICANT LOSS OF DATA AND BANDWIDTH LIMITATION. TRADITIONALLY, RAS OPERATES IN SECLUDED REGIONS, USING THE SURROUNDING TERRAIN TO SHIELD IT FROM POPULATED AREAS, OR INSIDE A RADIO QUIET ZONE THAT ENFORCES STRICT REGULATIONS ON HUMAN-GENERATED RFI. WHILE THESE MEASURES ARE EFFECTIVE IN MITIGATING TERRESTRIAL RFI, SUCH AS TV/RADIO STATIONS, MOBILE PHONES, AND WIFI NETWORKS, THEY ARE UNABLE TO PROTECT RAS AGAINST RFI ORIGINATING FROM SATELLITES IN SPACE. WITH AN INCREASING NUMBER OF MEGA-CONSTELLATION SATELLITES BEING LAUNCHED INTO SPACE BY COMPANIES LIKE SPACEX, SATELLITE RFI PRESENTS A GRAVE THREAT TO RAS. ON THE ONE HAND, IT IS IMPERATIVE FOR SATELLITE OPERATORS TO COOPERATE, AVOIDING ILLUMINATING GROUND RAS RECEIVERS AND MINIMIZING THE RFI. ON THE OTHER, THE RAS WILL HAVE TO STRENGTHEN ITS ABILITY TO OPERATE AMIDST STRONG UNAVOIDABLE RFI. BY LEVERAGING A NOVEL MODULO SAMPLING APPROACH, THIS PROJECT AIMS TO DEVELOP CUTTING-EDGE CIRCUIT DESIGNS AND SIGNAL PROCESSING ALGORITHMS THAT WILL BOLSTER THE RESILIENCE OF RADIO TELESCOPES AGAINST RFI. IT HOLDS GREAT POTENTIAL FOR OPTIMIZING THE COLLECTION AND PROCESSING OF RAS DATA, WHILE ALSO FOSTERING THE COEXISTENCE OF SATELLITE COMMUNICATIONS AND SCIENTIFIC RESEARCH IN THE RADIO SPECTRUM. THE PRIMARY GOAL OF THIS PROJECT IS TO ENHANCE THE OPERATIONAL CAPABILITIES OF RADIO ASTRONOMY SERVICE (RAS) IN THE PRESENCE OF STRONG RADIO FREQUENCY INTERFERENCE (RFI) ARISING FROM SATELLITE TRANSMITTERS THAT CANNOT BE AVOIDED GEOGRAPHICALLY. TO PROTECT RAS SYSTEMS ELECTRONICALLY, A CRUCIAL STEP IS TO ENSURE THE LINEARITY OF RAS RECEIVERS. NONLINEARITY OR SATURATION IN RECEIVERS GENERATES INTERMODULATION PRODUCTS THAT CAN WIPE OUT THE ENTIRE OBSERVING BAND. IT IS COSTLY TO USE CONVENTIONAL TECHNOLOGIES, E.G., HIGH-DYNAMIC RANGE (HDR) LOW-NOISE AMPLIFIERS AND HIGH-RESOLUTION ANALOG-TO-DIGITAL CONVERTERS (ADCS) FOR AMPLIFICATION AND DIGITIZATION, TO ENHANCE THE LINEARITY OF RAS RECEIVERS. THIS IS BECAUSE SUCH ENHANCEMENTS CAN RESULT IN AN AVALANCHE OF RAS DATA, WHICH IS KNOWN FOR ITS VERY LARGE SIZE. THE PROPOSED RESEARCH TAKES A MODULO SAMPLING-BASED APPROACH TO OPERATE RADIO INTERFEROMETRY ROBUSTLY AGAINST RFI. SPECIFICALLY, MODULO SAMPLING FOLDS THE OUT-OF-RANGE INPUT SIGNAL TO WITHIN THE DYNAMIC RANGE BEFORE TAKING SAMPLES USING A REGULAR-RESOLUTION ADC. THIS ALLOWS THE RECOVERY OF HDR INFORMATION FROM LOW-DYNAMIC RANGE (LDR) MEASUREMENTS. BUILDING ON THE MODULO SAMPLING APPROACH, THE PROPOSED RESEARCH ENCOMPASSES THREE THRUSTS: (1) A SIGNAL PROCESSING FRAMEWORK FOR ROBUST AND SUPER-RESOLUTION RADIO INTERFEROMETRY, WHICH ENABLES THE RECEIVER TO OPERATE WITHOUT BEING LIMITED BY A FIXED DYNAMIC RANGE; (2) SCALABLE MODULO ADC DESIGN FOR DEMONSTRATION OF UNLIMITED INTERFEROMETRY CAPABILITY IN THE PRESENCE OF RFI; AND (3) EXPERIMENTATION INCORPORATING THE MODULO ADCS FOR COMPREHENSIVE TESTING AND EVALUATION. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

CHAIN DYNAMICS AND LAYERING WITHIN POLYELECTROLYTE MULTILAYER FILMS

MRI: ACQUISITION OF A FIELD EMISSION CRYO-SCANNING ELECTRON MICROSCOPE FOR NANOCHARACTERIZATION AND PATTERNING OF SOFT MATERIALS

SATC: CORE: MEDIUM: PRIVACY FOR ALL: ENSURING FAIR PRIVACY PROTECTION IN MACHINE LEARNING

COLLABORATIVE RESEARCH: CPS: MEDIUM: MUTUALISTIC CYBER-PHYSICAL INTERACTION FOR SELF-ADAPTIVE MULTI-DAMAGE MONITORING OF CIVIL INFRASTRUCTURE -THIS PROJECT AIMS TO ENABLE MUTUALISTIC INTERACTION OF CYBER DAMAGE PROGNOSTICS AND PHYSICAL RECONFIGURABLE SENSING FOR MUTUALISTIC AND SELF-ADAPTIVE CYBER-PHYSICAL SYSTEMS (CPS). DRAWING INSPIRATION FROM MUTUALISM IN BIOLOGY WHERE TWO SPECIES INTERACT IN A WAY THAT BENEFITS BOTH, THE CYBER AND THE PHYSICAL INTERACT IN A WAY THAT THEY SIMULTANEOUSLY BENEFIT FROM AND CONTRIBUTE TO EACH OTHER TO ENHANCE THE ABILITY OF THE CPS TO PREDICT, RECONFIGURE, AND ADAPT. SUCH INTERACTION IS GENERALIZABLE, ALLOWING IT TO ENHANCE CPS APPLICATIONS IN VARIOUS DOMAINS. IN THE CIVIL INFRASTRUCTURE SYSTEMS DOMAIN, THE MUTUALISTIC INTERACTION-ENABLED CPS WILL ALLOW FOR RECONFIGURING A SINGLE TYPE OF SENSOR, ADAPTIVELY BASED ON DAMAGE PROGNOSTICS, TO MONITOR MULTIPLE CLASSES OF INFRASTRUCTURE DAMAGES ? THEREBY IMPROVING THE COST-EFFECTIVENESS OF MULTI-DAMAGE INFRASTRUCTURE MONITORING BY REDUCING THE TYPES AND NUMBER OF SENSORS NEEDED AND MAXIMIZING THE TIMELINESS AND ACCURACY OF DAMAGE ASSESSMENT AND PREDICTION AT THE SAME TIME. ENABLING COST-EFFECTIVE MULTI-DAMAGE MONITORING IS PROMISING TO LEAPFROG THE DEVELOPMENT OF SAFER, MORE RESILIENT, AND SUSTAINABLE INFRASTRUCTURE, WHICH WOULD STIMULATE ECONOMIC GROWTH AND SOCIAL WELFARE FOR THE BENEFIT OF THE NATION AND ITS PEOPLE. THIS PROJECT WILL ALSO CONTRIBUTE TO NSF?S COMMITMENT TO BROADENING PARTICIPATION IN ENGINEERING (BPE) BY DEVELOPING INNOVATIVE, INTERDISCIPLINARY, AND INCLUSIVE BPE PROGRAMS TO ATTRACT, TRAIN, AND REWARD THE NEXT-GENERATION ENGINEERING RESEARCHERS AND PRACTITIONERS WHO ARE CAPABLE CREATORS OF CPS TECHNOLOGY AND NOT ONLY PASSIVE CONSUMERS, THEREBY ENHANCING THE U.S. ECONOMY, SECURITY, AND WELL-BEING. THE ENVISIONED CPS INCLUDES THREE INTEGRATED COMPONENTS: (1) DATA-DRIVEN, KNOWLEDGE-INFORMED DEEP LEARNING METHODS FOR GENERALIZABLE DAMAGE PROGNOSTICS TO PREDICT THE ONSET AND PROPAGATION OF INFRASTRUCTURE DAMAGES, PROVIDING INFORMATION ABOUT TARGET DAMAGES TO INFORM RECONFIGURABLE SENSING, (2) SIGNAL DIFFERENCE MAXIMIZATION THEORY-BASED RECONFIGURABLE SENSING METHODS TO OPTIMIZE AND PHYSICALLY CONTROL THE CONFIGURATIONS OF THE SENSORS TO ACTIVELY SEEK TO MONITOR EACH OF THE PREDICTED TARGET DAMAGES, PROVIDING DAMAGE-SEEKING FEEDBACK TO INFORM DAMAGE PROGNOSTICS, AND (3) QUALITY-AWARE EDGE CLOUD COMPUTING METHODS FOR EFFICIENT AND EFFECTIVE DAMAGE INFORMATION EXTRACTION FROM RAW SENSING SIGNALS, SERVING AS THE BRIDGE BETWEEN DAMAGE PROGNOSTICS AND RECONFIGURABLE SENSING. THE PROPOSED CPS WILL BE TESTED IN MULTI-DAMAGE MONITORING OF BRIDGES USING SIMULATION-BASED AND ACTUAL CPS PROTOTYPES, AND WOULD BE GENERALIZED TO MONITORING OTHER CIVIL INFRASTRUCTURE IN THE FUTURE. THE PROPOSED CPS METHODS HAVE THE POTENTIAL TO TRANSFORM THE WAY WE DESIGN, CREATE, AND OPERATE CPS TO ENABLE THE NEXT-GENERATION CPS THAT HAVE GREATER PREDICTIVE ABILITY, RECONFIGURABILITY, AND ADAPTABILITY. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

MAKING SCWO TREATMENT OF PFAS-CONTAMINATED WATER MORE SUSTAINABLE

MUSIC-BASED BIOFEEDBACK TO IMPROVE BALANCE CONTROL IN ADULTS WITH PARKINSON'S DISEASE - PROJECT SUMMARY REDUCING FALL RISK IS A DIRE SOCIETAL NEED FOR THOSE WITH BRAIN DISORDERS OF AGING. FOR PERSONS WITH PARKINSON’S DISEASE, FALLS ARE COMMON IN DAILY MOBILITY TASKS. ONE SUCH TASK IS TURNING WHILE WALKING, WHICH PRESENTS A UBIQUITOUS CHALLENGE TO GENERATE THE REQUISITE CHANGES IN BODY MOMENTA WHILE MAINTAINING BALANCE. CONTROLLING BALANCE DURING TURNS IS A MECHANICALLY CHALLENGING AND ESSENTIAL EVERYDAY SKILL. TURNS COMPRISE UP TO HALF OF WALKED STEPS EACH DAY, AND ISSUES REGULATING MEDIOLATERAL STABILITY DURING TURNS IS WELL DOCUMENTED IN PERSONS WITH PARKINSON’S DISEASE. THUS, INTERVENTIONS THAT FOCUS ON TURNING BEHAVIOR AND LEVERAGE BENEFITS OF EMERGING PRACTICES, SUCH AS MUSIC-BASED INTERVENTIONS, MAY BE TRANSFORMATIVE. OUR LONG-TERM HYPOTHESIS IS THAT TRAINING WITH “MUSICAL BIOFEEDBACK” WILL IMPROVE BALANCE AND REDUCE THE RISK OF FALLS IN PERSONS WITH PARKINSON’S DISEASE, WHEN USED DURING TRAINING THAT FOCUSES ON TURNS PERFORMED IN EVERYDAY MOBILITY. MUSICAL BIOFEEDBACK CONVEYS BIOLOGICAL SENSOR DATA FROM THE PARTICIPANT THROUGH SPECIFIC MUSICAL SOUND PARAMETERS IN REAL-TIME. THE GOAL OF THE PROPOSED RESEARCH IS EVALUATING THE FEASIBILITY OF AN INTERVENTION USING MUSICAL BIOFEEDBACK TO TRAIN BALANCE DURING TURNS. WE ENVISION ITS FUTURE USE AS INTEGRATIVE WITH CURRENT PHYSICAL THERAPY PRACTICES. WE PROPOSE TO EVALUATE THE FEASIBILITY OF AN INTERVENTION USING MUSICAL BIOFEEDBACK TO INCREASE POSTURAL CONTROL DURING TURNING WHILE WALKING. THE FEASIBILITY STUDY WILL HAVE THREE ARMS: ONE WITH BOTH MUSICAL BIOFEEDBACK DURING TURNS (GROUP 1), ONE WITH ONLY TURNS (GROUP 2), AND ONE WITH “ACTIVITY AS USUAL” AND NO ADDITIONAL INTERVENTION (CONTROL; GROUP 3). OUR OBJECTIVES ARE TO: (AIM 1) DETERMINE THE FEASIBILITY OF RECRUITMENT, RETENTION, AND DATA COLLECTION PROCEDURES AND (AIM 2) EVALUATE MEASURES OF IMPLEMENTATION FIDELITY (ADHERENCE, DELIVERY, RECEIPT, AND ENACTMENT). OUR GOAL IS TO IMPROVE THE BALANCE CONTROL PATTERNS OF PERSONS WITH PARKINSON’S DISEASE WHILE SUPPORTING AND BUILDING THEIR SELF-EFFICACY. WE ENVISION PERSONS WITH PARKINSON’S DISEASE TRAINING WITH MUSICAL BIOFEEDBACK TO SAFELY (AND ENJOYABLY) PREPARE THEMSELVES TO AMBULATE IN THEIR COMMUNITY – IMPROVING AND PRESERVING THEIR MOBILITY. THE PROPOSED RESEARCH WILL PIONEER USING AN EMERGING CLINICAL TECHNOLOGY – MUSICAL BIOFEEDBACK – TO TRAIN BALANCE DURING TURNING GAIT TASKS. THE PROPOSED RESEARCH INNOVATES HOW MUSICAL BIOFEEDBACK AND TURNING- FOCUSED MOVEMENT TRAINING CAN BE LEVERAGED TO CHALLENGE COGNITIVE AND PHYSICAL BODY SYSTEMS DURING BALANCE REHABILITATION. BY DEVELOPING A NEW INTEGRATIVE THERAPY OPTION AND RIGOROUSLY EVALUATING ITS FEASIBILITY, THIS RESEARCH SUPPORTS FUTURE INTERVENTIONS TO HELP THOSE WITH PARKINSON’S DISEASE IMPROVE THEIR DYNAMIC BALANCE CONTROL.

COASTAL ADAPTATION IMPACTS ON JAMAICA BAY WATER QUALITY, WAVES, AND FLOODING POST-HURRICANE SANDY, NEW YORK

THE MAIN GOAL OF THE PROPOSED RESEARCH IS TO DELIVER A NOVEL METHODOLOGY BASED ON SCIENTIFIC MACHINE LEARNING (SML) METHODS TO PROVIDE HIGH QUALITY ESTIMATION OF WATER INHERENT OPTICAL PROPERTIES (IOPS).

CENTER FOR EXCELLENCE FOR MARITIME, ISLAND AND EXTREME/REMOTE ENVIRONMENTS SECURITY (CSR)

FIELD EVALUATION AND VALIDATION OF REMOTE WIND SENSING TECHNOLOGIES - SHORE-BASED AND BUOY MOUNTED LIDAR SYSTEMS

NRI: AN EGOCENTRIC COMPUTER VISION BASED ACTIVE LEARNING CO-ROBOT WHEELCHAIR

CAREER: HUMAN-PHYSICAL INTERACTION-DRIVEN COADAPTATION FOR RESILIENT HUMAN-CYBER-INFRASTRUCTURE SYSTEMS -THIS CAREER PROJECT ESTABLISHES THE SCIENTIFIC FOUNDATIONS OF HUMAN-PHYSICAL INTERACTION AND INTERACTION-DRIVEN COADAPTATION WITHIN HUMAN-CYBER-PHYSICAL SYSTEMS (HCPS). HUMANS AND PHYSICAL SYSTEMS INTERACT BIDIRECTIONALLY IN HCPS, ACTIVELY INFLUENCING AND BEING INFLUENCED BY EACH OTHER. UNDER EXTERNAL DISRUPTIONS, COORDINATED ADAPTATIONS DRIVEN BY BIDIRECTIONAL INTERACTIONS ? WHERE ADAPTATIONS IN EACH DOMAIN BOTH INFORM AND RESPOND TO THOSE IN THE OTHER ? ENHANCE COLLECTIVE RESILIENCE BEYOND ONE-SIDED OR INDEPENDENT ADAPTATIONS. BIOLOGICAL SYSTEMS UNDERSCORE INTERACTION-DRIVEN COADAPTATION AS A FUNDAMENTAL ORGANIZING PRINCIPLE: INTERACTING SPECIES COORDINATE ADAPTATIONS BASED ON INTERACTION TRAITS TO THRIVE UNDER CHANGING CONDITIONS. TO ACHIEVE THIS GOAL, THE PROJECT FORMALIZES INTERACTION-DRIVEN COADAPTATION BETWEEN HUMANS AND CIVIL INFRASTRUCTURE SYSTEMS (E.G., TRANSPORTATION, POWER, AND WATER SYSTEMS). THIS FORMALIZATION STRENGTHENS COLLECTIVE RESILIENCE TO INCREASINGLY FREQUENT AND SEVERE DISASTERS BY ENABLING COORDINATED ADAPTATIONS BETWEEN HUMANS AND INFRASTRUCTURE SYSTEMS, REDUCING DISRUPTION LOSSES AND ACCELERATING RECOVERY. THE PROJECT WILL ADVANCE THE U.S. NATIONAL INTERESTS BY IMPROVING LIFE STABILITY, INFRASTRUCTURE OPERABILITY, ECONOMIC CONTINUITY, AND RESPONSE TO DISASTER-INDUCED DISRUPTIONS. IT WILL ALSO PROMOTE HCPS EDUCATION THROUGH AN ATTRACT-TRAIN-REWARD PIPELINE, RESEARCH-EDUCATION INTEGRATION, AND PUBLIC ENGAGEMENT. THE PROJECT ADVANCES THE SCIENCE OF HCPS BY MOVING BEYOND PREVAILING PARADIGMS ? SUCH AS HUMAN-IN/ON-THE-LOOP AND HUMAN-AWARE SYSTEMS ? THAT OFTEN MODEL HUMANS AS PASSIVE OR EXOGENOUS AGENTS. INSTEAD, IT ESTABLISHES BIDIRECTIONAL HUMAN-PHYSICAL INTERACTION AS THE FOUNDATION FOR SYNERGISTIC COADAPTATION BETWEEN HUMAN AND PHYSICAL AGENTS UNDER UNCERTAINTY IN COUPLED HUMAN-PHYSICAL DYNAMICS. DRAWING INSPIRATION FROM BIOLOGICAL MODELS OF COADAPTATION, INCLUDING REPLICATOR DYNAMICS AND EVOLUTIONARILY STABLE STRATEGIES, THE PROJECT EXTENDS THESE PRINCIPLES TO HCPS TO ENABLE ROBUST MODELING AND CONTROL OF INTERACTIVE AND COADAPTIVE HUMAN-PHYSICAL DYNAMICS FOR GREATER SYSTEM ADAPTABILITY AND RESILIENCE. TO MODEL AND CONTROL THESE DYNAMICS, THE PROJECT INTRODUCES FOUR KEY INNOVATIONS: 1) A SPATIOTEMPORAL, GENERATIVE, AND CONTEXT-AWARE LEARNING FRAMEWORK THAT ENABLES RELIABLE AND SCALABLE MODELING OF HUMAN AND INFRASTRUCTURE STATES UNDER SPARSE AND UNCERTAIN OBSERVATIONS; 2) AN ASYNCHRONOUS, CROSS-DOMAIN, AND ADAPTIVE LEARNING FRAMEWORK THAT ENABLES RELIABLE AND GENERALIZABLE MODELING OF LAGGED, DISTRIBUTED, AND CONTEXT-DEPENDENT HUMAN-INFRASTRUCTURE INTERACTION DYNAMICS BASED ON INFERRED HUMAN AND INFRASTRUCTURE STATES; 3) A HYBRID COADAPTATION MODELING FRAMEWORK THAT ENABLES INTEGRATION OF DETERMINISTIC INFRASTRUCTURE ADAPTATION WITH BEHAVIORALLY GROUNDED STOCHASTIC HUMAN ADAPTATION TO SIMULATE COADAPTATION DYNAMICS UNDER UNCERTAINTY; AND 4) A REPLICATOR-INSPIRED, EQUILIBRIUM-AWARE MULTI-AGENT REINFORCEMENT LEARNING FRAMEWORK THAT ENABLES STABLE AND ANTICIPATORY INTERACTION-DRIVEN COADAPTATION POLICY OPTIMIZATION UNDER MULTI-AGENT COMPETITION AND NON-STATIONARY DYNAMICS. COLLECTIVELY, THESE CONTRIBUTIONS TRANSFORM HOW HCPS ARE MODELED, SIMULATED, AND OPTIMIZED ? OPENING NEW SCIENTIFIC PATHWAYS FOR INTERACTIVE, COADAPTIVE, AND RESILIENT SYSTEM DESIGN ACROSS CPS, INFRASTRUCTURE, AND DISASTER RESILIENCE DOMAINS TO ADVANCE HCPS THEORY AND THE RESILIENCE OF REAL-WORLD SYSTEMS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

PT-BASED BI-METALLIC MONOLITH CATALYSTS FOR PARTIAL UPGRADING OF MICROALGAE OIL

CAREER: NON-LOCAL METAMATERIALS AND METASURFACES FOR NEXT GENERATION NON-RECIPROCAL ACOUSTIC DEVICES -THIS FACULTY EARLY CAREER DEVELOPMENT (CAREER) AWARD WILL FUND RESEARCH THAT ENABLES ACOUSTIC METAMATERIALS AND METASURFACES LEVERAGING NON-LOCAL UNIT CELL INTERACTIONS. THE NON-RECIPROCAL ACOUSTIC DEVICES WILL ENABLE INDEPENDENT MODIFICATION OF TRANSMITTED AND REFLECTED WAVES, WITH TRANSFORMATIVE IMPACT IN APPLICATIONS SUCH AS BIOMEDICAL ULTRASOUND, ULTRASONIC IMAGING, UNDERWATER COMMUNICATION, AND THE DESIGN OF AEROSPACE STRUCTURES, THEREBY PROMOTING THE PROGRESS OF SCIENCE. THIS RESEARCH WILL ESTABLISH A NOVEL CLASS OF METAMATERIALS AND METASURFACES WHOSE CONSTITUENT UNIT CELLS CAN INTERACT NON-LOCALLY AND IMPLEMENT ARBITRARY NON-RECIPROCAL (I.E., ASYMMETRIC) WAVE BEHAVIORS, FUNDAMENTALLY EXPANDING THE POSSIBILITIES FOR ACOUSTIC WAVE MANIPULATION. THESE NON-LOCAL SYSTEMS ACHIEVE NON-RECIPROCAL ACOUSTIC BEHAVIORS IN A SIMPLER WAY THAN EXISTING METHODS, SHIFTING THE PARADIGM FOR HOW ACOUSTIC WAVES CAN BE USED TO SOLVE ENGINEERING PROBLEMS. THE EDUCATIONAL COMPONENT OF THE PROJECT WILL FOCUS ON THE CREATIVE MANIPULATION OF SOUND, INTRODUCING CONCEPTS OF NOISE AND VIBRATION CONTROL FROM THE RESEARCH COMPONENT OF THE PROJECT, TO INCREASE STUDENT PARTICIPATION IN STEM AND ACOUSTICS. IN COLLABORATION WITH THE STEVENS TEACHING AND LEARNING CENTER, THE PROJECT WILL INITIATE AN ?ACOUSTICS DAY? OUTREACH PROGRAM HOSTED IN THE STEVENS ANECHOIC CHAMBER. THE PROGRAM WILL HOST MIDDLE SCHOOL STUDENTS FROM THE LOCAL AREA, EMPHASIZING THE CONNECTIONS BETWEEN SOUND, URBAN ENVIRONMENTS, AND DIFFERENT ENGINEERING CAREERS. THIS RESEARCH AIMS TO ENABLE COMPLETE CONTROL OVER ACOUSTIC WAVES BY INVESTIGATING NON-LOCAL ACOUSTIC METAMATERIALS AND METASURFACES THAT BREAK ACOUSTIC RECIPROCITY. UNLIKE LOCAL, PHASE-DELAYED INTERACTIONS, NON-LOCAL INTERACTIONS CAN HAVE A DIRECTIONAL BIAS, RESULTING IN BROKEN SYMMETRY AND NON-RECIPROCAL BEHAVIOR. CONVENTIONAL MATERIALS DO NOT INTERACT NON-LOCALLY; INSTEAD, THIS PROJECT WILL BUILD UPON RESEARCH IN ACOUSTIC METAMATERIALS AND METASURFACES, WHICH USE A SMALL-SCALE REPEATED UNIT CELL TO MANIPULATE WAVE PROPAGATION, REFLECTION, AND TRANSMISSION. THIS PROJECT WILL SHIFT THE PARADIGM OF CONVENTIONAL ACOUSTIC METAMATERIALS AND METASURFACES THROUGH A COMPREHENSIVE THEORETICAL AND EXPERIMENTAL INVESTIGATION OF NON-LOCAL ACOUSTIC METAMATERIALS AND METASURFACES, LEVERAGING PIEZOELECTRIC TRANSDUCERS THAT INTERACT NON-LOCALLY VIA ELECTRICAL CIRCUITRY. THE RESULTS OF THIS RESEARCH WILL UNLOCK NEW TYPES OF ACOUSTIC PHENOMENA, PROVIDE FUNDAMENTAL INSIGHT INTO NON-HERMITIAN PHYSICS, AND INITIATE NEW RESEARCH DIRECTIONS IN ACOUSTIC CIRCUITS THAT FREELY MANIPULATE ACOUSTIC WAVES. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

TISSUE-ENGINEERED NANOFIBROUS NERVE GRAFTS FOR ENHANCING THE RATE OF NERVE REGENERATION

ENGINEERING COMPOSITE NANOFIBROUS SCAFFOLDS FOR REPAIRING SEGMENTAL BONE DEFECT

QUANTUM ENTANGLEMENT SCIENCE AND TECHNOLOGY

SOFTWARE ENGINEERING MASTER'S PROGRAM FOR LIBERAL ARTS GRADUATES

TWC: MEDIUM: COLLABORATIVE: FLEXIBLE AND PRACTICAL INFORMATION FLOW ASSURANCE FOR MOBILE APPS

A MULTISCALE SURFACE-STRUCTURING APPROACH TO CONTROL THE INFECTION OF ORTHOPAEDIC IMPLANTS

COLLABORATIVE RESEARCH: SHF: MEDIUM: OASIS: AN OPEN-SOURCE AI-DRIVEN EDA TOOL FOR REAL-TIME SYNTHESIS OF SHORT-DISTANCE WIRELESS INTERCONNECTS ON SILICON -PHYSICS-INFORMED NEURAL NETWORKS (PINNS) ARE AN EMERGING CLASS OF ARTIFICIAL INTELLIGENCE (AI) MODELS THAT INCORPORATE PHYSICAL LAWS DIRECTLY INTO THEIR ARCHITECTURE, ENABLING FAST AND ACCURATE SIMULATIONS EVEN WITH LIMITED OR NOISY DATA. THEY SHOW SIGNIFICANT PROMISE FOR ELECTROMAGNETIC (EM) SIMULATIONS, PARTICULARLY IN MANAGING PARAMETER VARIATIONS IN REAL TIME. HOWEVER, ENSURING BOTH ACCURACY AND STABILITY IN PINN TRAINING REMAINS A MAJOR CHALLENGE, OFTEN REQUIRING LARGE DATASETS AND EXHIBITING SENSITIVITY TO MINOR INPUT CHANGES. TO ADDRESS THESE LIMITATIONS, RESEARCHERS FROM STEVENS INSTITUTE OF TECHNOLOGY (SIT) AND THE OHIO STATE UNIVERSITY (OSU) ARE DEVELOPING AN OPEN-SOURCE AI-DRIVEN ELECTRONIC DESIGN AUTOMATION (EDA) TOOL FOR REAL-TIME SYNTHESIS OF SHORT-DISTANCE WIRELESS INTERCONNECTS ON SILICON (OASIS), THE FIRST OPEN-SOURCE, AI-POWERED EDA TOOL FOR REAL-TIME PARAMETRIC EM SIMULATION. OASIS WILL EXPLORE SCALABLE STRATEGIES FOR TRAINING LARGE-SCALE PINNS EFFICIENTLY AND ROBUSTLY. THIS RESEARCH WILL FOCUS ON THE DESIGN OF SHORT-RANGE (~10 MM) WIRELESS INTERCONNECTS ON SILICON FOR TWO CUTTING-EDGE APPLICATIONS: (1) CONTACTLESS CONNECTORS THAT LEVERAGE SPATIAL MULTIPLEXING TO MINIMIZE INTERFERENCE AND ENHANCE DATA THROUGHPUT, AND (2) BATTERYLESS BRAIN-MACHINE INTERFACES (BMIS) THAT DEPEND ON REAL-TIME SIGNAL CANCELLATION AND SENSITIVITY OPTIMIZATION. BY REPLACING TRADITIONAL SLOW SOLVERS WITH A FASTER, AI-DRIVEN ALTERNATIVE, OASIS AIMS TO TRANSFORM NEXT-GENERATION EM DESIGN. TO ACHIEVE THE PROJECT?S OBJECTIVES, THE INVESTIGATORS WILL PURSUE SIX KEY RESEARCH DIRECTIONS. FIRST, THE TEAM OF RESEARCHERS WILL DEVELOP A GRAPH-BASED IMPORTANCE SAMPLING FRAMEWORK TO ACCELERATE THE TRAINING AND CONVERGENCE OF PHYSICS-INFORMED NEURAL NETWORKS (PINNS) ON LARGE-SCALE POINT CLOUDS. SECOND, THEY WILL IMPLEMENT A STABILITY-GUIDED TRAINING APPROACH TO ENABLE ROBUST AND EFFICIENT PARAMETRIC EM SIMULATIONS USING PINNS. THIRD, THE TEAM WILL DESIGN A NOVEL PROXIMITY COMMUNICATION METHOD CAPABLE OF MULTI-GIGABIT DATA TRANSFER IN DENSE, LOW-POWER ENVIRONMENTS WHERE TRADITIONAL EM SOLVERS ARE INEFFECTIVE. FOURTH, THEY WILL INVESTIGATE SPATIAL MULTIPLEXING TECHNIQUES TO SCALE INTERCONNECT BANDWIDTH. FIFTH, THE PROJECT WILL EXPLORE A NEW CLASS OF WIRELESS, BATTERYLESS BRAIN IMPLANTS THAT UTILIZE SIGNAL BACKSCATTERING AND AI-DRIVEN LEAKAGE CANCELLATION TO IMPROVE SENSITIVITY. SIXTH, THE RESEARCHERS WILL INTRODUCE REAL-TIME ADAPTIVE SPECIFICATIONS FOR BRAIN-MACHINE INTERFACES (BMIS) TO ACCOMMODATE DYNAMIC ENVIRONMENTAL CONDITIONS. TO BROADEN THE PROJECT?S IMPACT, THE INVESTIGATORS AT SIT AND OSU WILL ALSO DEVELOP NEW COURSES THAT INTEGRATE ADVANCED MACHINE LEARNING CONCEPTS INTO SOFTWARE-HARDWARE CO-DESIGN EDUCATION. COLLECTIVELY, THIS RESEARCH AIMS TO ADVANCE THE FRONTIERS OF MILLIMETER-WAVE AND RF INTEGRATED CIRCUIT DESIGN, COMPUTER-AIDED DESIGN (CAD), MACHINE LEARNING, SCIENTIFIC COMPUTING, AND BIOMEDICAL ENGINEERING. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

SHF: SMALL: HIGH-PERFORMANCE INCREMENTAL SPECTRAL ALGORITHMS FOR EFFICIENT MODELING AND SIMULATION OF LARGE-SCALE INTEGRATED CIRCUITS -MODERN INTEGRATED CIRCUITS (ICS) INTEGRATE BILLIONS OF TRANSISTORS INTO A SINGLE CHIP. EVEN KEY SUBSYSTEMS SUCH AS CLOCK DISTRIBUTION NETWORKS, POWER DELIVERY NETWORKS (PDNS), EMBEDDED MEMORY ARRAYS, AND ANALOG AND MIXED-SIGNAL SYSTEMS CAN BECOME INCREDIBLY COMPLEX, CONSISTING OF HUNDREDS OF MILLIONS OF CIRCUIT COMPONENTS. AS A CONSEQUENCE, IT HAS BECOME EXCEEDINGLY DIFFICULT TO MODEL, SIMULATE, OPTIMIZE, AND VERIFY FUTURE ICS AT A LARGE SCALE USING EXISTING DESIGN METHODOLOGIES. RECENT RESEARCH IN SPECTRAL GRAPH SPARSIFICATION HAS MADE IT POSSIBLE TO CONSTRUCT MUCH SPARSER SUBGRAPHS WHILE PRESERVING IMPORTANT GRAPH SPECTRAL PROPERTIES SUCH AS THE FIRST FEW EIGENVALUES AND EIGENVECTORS OF THE GRAPH LAPLACIAN. THESE FINDINGS HAVE ALREADY LED TO THE DEVELOPMENT OF HIGHLY EFFICIENT ALGORITHMS FOR SOLVING LARGE SPARSE MATRICES, PARTIAL DIFFERENTIAL EQUATIONS (PDES), AND SIMULATING LARGE-SCALE CIRCUIT SYSTEMS. HOWEVER, EXISTING SPECTRAL SPARSIFICATION METHODS DO NOT EFFICIENTLY ALLOW FOR UPDATING THE SPARSIFIED GRAPH WHEN ONLY INCREMENTAL CHANGES ARE MADE TO THE ORIGINAL NETWORK. THE ALGORITHMS AND METHODOLOGIES TO BE DEVELOPED IN THIS PROJECT WILL BE TRANSFERRED TO TECHNOLOGY COMPANIES, SUCH AS SEMICONDUCTOR AND ELECTRONIC DESIGN AUTOMATION (EDA) COMPANIES, AS WELL AS SOCIAL AND NETWORK COMPANIES FOR POTENTIAL INDUSTRIAL APPLICATIONS. FURTHERMORE, THE SOURCE CODE OF THE DEVELOPED EDA ALGORITHMS WILL BE MADE AVAILABLE TO OTHER RESEARCHERS THROUGH COLLABORATIONS. THE PROJECT ALSO INCLUDES COMPELLING EDUCATION, OUTREACH, AND COURSE DEVELOPMENT PLAN. THE PRIMARY RESEARCH INVESTIGATOR PLANS TO RECRUIT K-12 STUDENTS FROM LOCAL SCHOOLS AND GET THEM INVOLVED IN THE LATEST RESEARCH PROJECTS. THIS RESEARCH PROJECT AIMS TO INVESTIGATE SCALABLE ALGORITHMS FOR INCREMENTAL SPECTRAL SPARSIFICATION OF LARGE GRAPH LAPLACIANS AND INTEGRATED CIRCUIT NETWORKS. THE FRAMEWORK WILL ALLOW FOR EFFICIENTLY HANDLING LARGE GRAPHS THAT EXPERIENCE STREAMING EDGE INSERTIONS/DELETIONS IN SUBLINEAR TIME, AND SIGNIFICANTLY ACCELERATING SPICE-ACCURATE MODELING AND SIMULATIONS OF LARGE CIRCUIT DESIGNS THAT UNDERGO FREQUENT UPDATES. THIS RESEARCH WILL ALSO INVESTIGATE EFFICIENT APPROACHES FOR INCREMENTAL MODELING AND SIMULATION OF INTEGRATED CIRCUITS LEVERAGING INCREMENTAL SPECTRAL SPARSIFICATION AND INVOLVE CLOSE COLLABORATIONS WITH LEADING INDUSTRIAL EXPERTS IN CIRCUIT SIMULATION TO EVALUATE THE PROPOSED RESEARCH. THE SUCCESS OF THE PROPOSED RESEARCH WILL POTENTIALLY CONTRIBUTE TO THE ADVANCEMENTS IN SPECTRAL GRAPH THEORY AND EDA, LEADING TO THE DEVELOPMENT OF HIGHLY SCALABLE INCREMENTAL ALGORITHMS FOR SOLVING PARTIAL DIFFERENTIAL EQUATIONS, SPARSE MATRIX PROBLEMS, SPECTRAL GRAPH PARTITIONING, AND DESIGN AUTOMATION OF LARGE-SCALE ICS. THIS PROJECT IS CO-FUNDED BY THE SOFTWARE AND HARDWARE FOUNDATIONS (SHF) AND DISCOVERY RESEARCH PREK-12 (DRK12) PROGRAMS. DRK12 IS AN APPLIED RESEARCH PROGRAM THAT SUPPORTS STEM EDUCATION PREK-12. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

CIF: SMALL: UBIQUITOUS RF SENSING WITH SMART METASURFACES -RADIO FREQUENCY (RF) SENSING IS BECOMING INCREASINGLY PERVASIVE DUE TO THE PROLIFERATION OF WIRELESS COMMUNICATIONS. REMARKABLY, THE UPCOMING WIFI STANDARD IEEE802.11BF WILL ENABLE WIRELESS DEVICES TO FUNCTION AS RADARS TO SENSE THE SURROUNDINGS AND DETERMINE THE POSITION OF NEARBY OBJECTS. MOST RF SENSORS, HOWEVER, ARE UNABLE TO LOOK AROUND THE CORNER AND LOCATE NON-LINE-OF-SIGHT TARGETS. TO ADDRESS THIS PROBLEM, A COMMONLY EMPLOYED APPROACH INVOLVES DEPLOYING MULTIPLE RF TRANSMITTERS AND RECEIVERS ACROSS THE SURVEILLANCE AREA, SO THAT THE TARGET CAN BE OBSERVED BY AT LEAST ONE TRANSMITTER-RECEIVER PAIR. UNFORTUNATELY, SUCH A DISTRIBUTED RF SENSING SYSTEM IS BULKY, COSTLY, OPERATIONALLY BURDENSOME, AND ENVIRONMENTALLY UNFRIENDLY DUE TO EXCESSIVE RADIATION. TO OVERCOME THESE SHORTCOMINGS, THIS PROJECT AIMS TO DEVELOP AN ALTERNATIVE DISTRIBUTED RF SENSING PARADIGM THAT CAN EFFECTIVELY ?LOOK? AROUND THE CORNER BY LEVERAGING A RECONFIGURABLE INTELLIGENT SURFACE (RIS), WHICH IS A THIN PLANAR STRUCTURE COMPRISING NUMEROUS SMALL LOW-COST METAMATERIAL ELEMENTS THAT CAN BE INDEPENDENTLY ADJUSTED TO CONTROL THE REFLECTION OF INCIDENT RF SIGNALS. LIKE WALLPAPER, RIS CAN COVER PARTS OF BUILDINGS, WALLS, AND CEILINGS, ALLOWING RF ENGINEERS TO PROACTIVELY CUSTOMIZE THE RADIO ENVIRONMENT BASED ON SPECIFIC NEEDS. THIS WORK WILL ADVANCE FUNDAMENTAL THEORY AND PRACTICAL METHODS FOR RF SENSING AIDED BY RIS. RESEARCH OUTCOMES OF THIS PROJECT WILL HAVE THE POTENTIAL TO BE INTEGRATED WITH FUTURE WIRELESS NETWORKS, EMPOWERING SERVICE PROVIDERS TO OFFER INTELLIGENT RF SENSING AND COMMUNICATION SERVICES TO THEIR CUSTOMERS. THE OBJECTIVE OF THIS PROJECT IS TO ESTABLISH A SYSTEMATIC SIGNAL PROCESSING FRAMEWORK FOR UBIQUITOUS RF SENSING AIDED BY RIS IN DISTRIBUTED ENVIRONMENTS. IN THESE SETTINGS, THE TRANSMITTER AND RECEIVER MAY BE CO-LOCATED OR SPATIALLY DISTRIBUTED, WITH RISS DEPLOYED TO ASSIST IN TARGET ILLUMINATION AND/OR OBSERVATION. THE PROPOSED FRAMEWORK ENCOMPASSES BOTH ACTIVE SENSING, WHERE A DEDICATED TRANSMITTER IS JOINTLY OPTIMIZED AS A PART OF THE SYSTEM, AND PASSIVE SENSING, WHICH EMPLOYS AMBIENT WIRELESS SOURCES, SUCH AS CELLULAR AND WIFI SIGNALS, TO PROBE THE ENVIRONMENT. THE RESEARCH EFFORTS ARE STRUCTURED INTO THREE THRUSTS. THRUST 1 FOCUSES ON SYSTEM DESIGN AND OPTIMIZATION, TAKING INTO ACCOUNT MULTIPATH AND ASYNCHRONOUS PROPAGATION INHERENT IN THE DISTRIBUTED SENSING SYSTEM. THRUST 2 DEVELOPS TRAINING-EFFICIENT CHANNEL ESTIMATION TECHNIQUES, INCLUDING METHODS TO ESTIMATE THE CASCADE CHANNEL THAT SERIALLY LINKS THE TRANSMITTER, RIS, TARGETS, AND RECEIVER, AS WELL AS APPROACHES FOR ESTIMATING THE STATISTICS OF THE CASCADE CHANNEL. LASTLY, THRUST 3 EXPLORES RF SENSING USING RIS WITH A MULTI-LAYER STRUCTURE, WHICH PROVIDES ADDITIONAL RF SIGNAL PROCESSING CAPABILITIES, WHILE SIMULTANEOUSLY REDUCING HARDWARE COMPLEXITY AND ENERGY CONSUMPTION. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

CICI: UCSS: PROGRAMMABLE WIRELESS INFRASTRUCTURE WITH FORMAL ASSURANCE FOR CROSS-CAMPUS RESEARCH -SCIENTIFIC PROGRESS RELIES ON COLLABORATIVE ACCESS TO DATA, INSTRUMENTS, AND COMPUTING ACROSS INSTITUTIONS. HOWEVER, WIRELESS INFRASTRUCTURE AT RESEARCH INSTITUTIONS OFTEN PRESENTS A TRADEOFF: RESEARCHERS REQUIRE FLEXIBILITY TO EXPERIMENT, WHILE CAMPUS IT TEAMS MUST ENFORCE STRICT SECURITY AND COMPLIANCE POLICIES. THIS MISALIGNMENT CAN SLOW INNOVATION AND INTRODUCE VULNERABILITIES. THE WIRELESS RESEARCH ACCESS PROGRAMMABLE (WRAP) PROJECT ADDRESSES THIS BY CREATING A PROGRAMMABLE WIRELESS ARCHITECTURE THAT ALLOWS RESEARCHERS TO MANAGE DOMAIN SPECIFIC POLICIES WHILE PROVIDING IT TEAMS WITH LIGHTWEIGHT, FORMALLY VERIFIABLE MECHANISMS TO ENSURE COMPLIANCE. WRAP ENABLES SECURE, CROSS CAMPUS COLLABORATION IN FIELDS SUCH AS QUANTUM COMPUTING AND NEUROSCIENCE, INTEGRATING SEAMLESSLY WITH EXISTING INFRASTRUCTURE. DEVELOPED WITH DOMAIN RESEARCHERS, IT ENSURES ALIGNMENT WITH SCIENTIFIC WORKFLOWS AND ADVANCES SCALABLE, POLICY COMPLIANT WIRELESS SYSTEMS FOR NATIONAL CYBERINFRASTRUCTURE. WRAP INTEGRATES PROGRAMMABLE WIRELESS NETWORKING, LIGHTWEIGHT FORMAL VERIFICATION, AND USABILITY CENTERED DESIGN INTO A UNIFIED ARCHITECTURE. BUILT ON OPENWIFI AND OPEN RADIO ACCESS NETWORK (O-RAN), IT INTRODUCES THREE KEY INNOVATIONS: (1) PROGRAMMABLE WIRELESS ENCLAVES USING DYNAMIC RADIO ACCESS SLICING FOR CROSS-CAMPUS COLLABORATION, (2) A POLICY ASSURANCE LAYER WITH FORMAL VERIFICATION FOR COMPLIANCE AND REAL-TIME MONITORING VIA AN IT DASHBOARD, AND (3) A DECLARATIVE INTERFACE FOR RESEARCHERS TO EXPRESS HIGH-LEVEL INTENT WITH ACTIONABLE FEEDBACK. PILOTED AT THE PRINCIPAL INVESTIGATORS' INSTITUTIONS, WRAP IS TESTED IN REAL WORKFLOWS FOR USABILITY, POLICY ENFORCEMENT, AND LEGACY INTEGRATION. THE PROJECT PROVIDES OPEN SOURCE MODULES, VERIFIED TEMPLATES, AND TRAINING RESOURCES TO SUPPORT BROADER ADOPTION, ENABLING SECURE, ADAPTABLE WIRELESS SYSTEMS THAT ACCELERATE SCIENTIFIC DISCOVERY WHILE ENSURING COMPLIANCE AND TRUST. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE PLANNED FOR THIS AWARD.

CAREER: LEARNING HIERARCHICAL GENERATIVE MODELS FOR EXPRESSIVE, CONTROLLABLE, AND CROSS-DOMAIN REPRESENTATIONS -DATA IN VARIOUS DOMAINS TYPICALLY EXHIBIT MULTIPLE LEVELS OF ABSTRACTION, RANGING FROM REPRESENTATIONS BASED ON LANGUAGE (I.E., SEMANTIC REPRESENTATIONS) TO LOW-LEVEL SAMPLE-SPECIFIC DETAILS. EXAMPLES INCLUDE IN FACIAL IMAGES, RANGE FROM OVERALL FACIAL STRUCTURE TO SPECIFIC FEATURES LIKE EYES AND MOUTH, DOWN TO TEXTURES LIKE SKIN AND HAIR, AND THE LAYERED ORGANIZATION IN LANGUAGE DATA, FROM TOPICS TO PARAGRAPHS, SENTENCES, AND WORDS. LEARNING AND UNDERSTANDING THESE DATA TO EFFECTIVELY GENERATE NOVEL CONTENT PRESENTS A CHALLENGE FOR MODERN ARTIFICIAL INTELLIGENCE (AI). GENERATIVE AI, WHICH HAS GARNERED INCREASED ATTENTION IN RECENT YEARS, PROVIDES PRINCIPLED METHODS TO BEGIN TO ADDRESS THIS CHALLENGE. UNFORTUNATELY, EXISTING MODELS OFTEN OVERLOOK THE STRUCTURAL INFORMATION WITHIN DATA. THEY ALSO LACK CONTROLLABILITY BECAUSE MUCH OF WHAT HAPPENS IS NOT TRANSPARENT. FINALLY, MANY MODELS ARE DOMAIN-SPECIFIC, LIMITING THEIR CAPACITY IN NEW AREAS AND HINDERING THEIR USE IN SAFETY-CRITICAL AND CROSS-DOMAIN APPLICATIONS. THIS PROJECT AIMS TO GO BEYOND EXISTING GENERATIVE FRAMEWORKS BY DEVELOPING NEW MODELS THAT EXCEED THEIR CURRENT CAPACITIES WHILE MAINTAINING THE EASE OF CONTROLLABILITY. THE PROJECT WILL ALSO SUPPORT CURRICULUM DEVELOPMENT FOR BOTH GRADUATE AND UNDERGRADUATE PROGRAMS IN ARTIFICIAL INTELLIGENCE. FURTHERMORE, THE PRINCIPAL INVESTIGATOR WILL CONTINUE TO MENTOR UNDERGRADUATE AND GRADUATE STUDENTS AND WILL BE ACTIVELY INVOLVED IN PRE-COLLEGE PROGRAMS FOR K-12 STEM EDUCATION. THE TECHNICAL OBJECTIVE OF THIS PROJECT IS TO DESIGN NEW STRUCTURED GENERATIVE MODELING AND LEARNING FRAMEWORKS TO ADVANCE EXISTING ARTIFICIAL INTELLIGENCE FOR MORE INFORMATIVE, CONTROLLABLE, AND CROSS-DOMAIN REPRESENTATIONS. SPECIFICALLY, THIS PROJECT WILL STUDY AND ESTABLISH CORE METHODOLOGICAL FOUNDATIONS FOR HIERARCHICAL GENERATIVE MODELING IN THREE KEY THRUSTS. THE FIRST THRUST DEVELOPS CONTEXT-AWARE GENERATIVE MODELS THAT INCORPORATE THE MODELING OF STRUCTURAL INFORMATION AND CONTEXTUAL DEPENDENCIES FOR EXPRESSIVE HIERARCHICAL REPRESENTATION. THE SECOND THRUST DEVELOPS NEW STRUCTURED AND SEMANTIC-INDUCING SCHEMES FOR CONTROLLABLE MODELS. THE THIRD THRUST DEVELOPS MULTIMODAL GENERATIVE MODELS FOR EFFECTIVE CROSS-DOMAIN REPRESENTATIONS. THE COMPREHENSIVE INVESTIGATION OF THE PROJECT WILL LEAD TO THE DESIGN OF MORE POWERFUL AND RELIABLE GENERATIVE ARTIFICIAL INTELLIGENCE SYSTEMS THAT ARE EASILY UNDERSTANDABLE AND EFFECTIVELY MANAGEABLE BY USERS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

MOLECULAR STRUCTURE COLLISIONAL DISSOCIATION AND IONIZATION

CAREER: REINFORCEMENT-LEARNING ASSIST-AS-NEEDED CONTROL FOR ROBOT-ASSISTED GAIT TRAINING

LEAP-HI: TACKLING BRAIN DISEASES WITH MECHANICS: A DATA-DRIVEN APPROACH TO MERGE ADVANCED NEUROIMAGING AND MULTI-PHYSICS MODELING

CISE-ANR: SHF: SMALL: SCENARIO-BASED FORMAL PROOFS FOR CONCURRENT SOFTWARE -MODERN SOFTWARE INCREASINGLY EMPLOYS CONCURRENT PROGRAMMING IN ORDER TO EXPLOIT THE PERFORMANCE BENEFITS OFFERED BY MULTICORE ARCHITECTURES. UNFORTUNATELY, CONCURRENT PROGRAMMING IS NOTORIOUSLY DIFFICULT AND CONCURRENCY BUGS EXIST EVEN IN CODE WRITTEN BY THE MOST SEASONED PROGRAMMERS. CONSEQUENTLY, RESEARCHERS HAVE DEVELOPED MATHEMATICAL REASONING TECHNIQUES IN ATTEMPT TO PROVE THESE PROGRAMS CORRECT BUT EXISTING TECHNIQUES RELY ON THE USER TO PROVIDE COMPLEX INVARIANTS THAT ARE OFTEN NOT VERY INTUITIVE. BY CONTRAST, ALGORITHM DESIGNERS FROM THE DISTRIBUTED COMPUTING COMMUNITY FREQUENTLY PROVIDE MORE UNDERSTANDABLE ARGUMENTS FOR THE CORRECTNESS OF THEIR IMPLEMENTATIONS, BY FOCUSING ON DESCRIBING A FEW KEY EXAMPLE SCENARIOS OF HOW THREADS MAY BE INTERLEAVED. THIS PROJECT WILL BRIDGE THIS GAP BY ELEVATING SCENARIO-BASED REASONING FROM INTUITIVE ARGUMENTS TO FORMALLY RIGOROUS PROOFS. THE PROJECT?S NOVELTIES ARE NEW FOUNDATIONS, ALGORITHMS AND AUTOMATED TOOLS FOR VERIFYING CONCURRENT SOFTWARE THAT DEMONSTRATE HOW SCENARIO-BASED REASONING CAN BE FORMAL, YET ALSO APPROACHABLE TO EVERYDAY PROGRAMMERS. THE PROJECT?S IMPACTS ARE (1) THEORIES, ALGORITHMS AND AUTOMATED VERIFICATION TOOLS FOR CONCURRENT SOFTWARE THAT CAN BE USED BY PROGRAMMERS, WITHOUT THE NEED FOR A BACKGROUND IN FORMAL METHODS, (2) DEMONSTRATED APPLICABILITY TO REAL-WORLD CONCURRENT PROGRAMS SUCH AS WEB OR DATABASES SERVERS, (3) PUBLICATIONS AND PUBLIC OPEN-SOURCE RELEASE OF THESE VERIFICATION TOOLS, AND (4) BROADER IMPACTS ON EDUCATION THROUGH NOVEL COURSE MATERIALS AND PARTICIPATION OF UNDER-REPRESENTED GROUPS. OVERALL, THE PROJECT WILL MAKE VERIFICATION MORE ACCESSIBLE AND, THROUGH OUR ADVOCATION IN ACADEMIA AND IN INDUSTRY, LEAD TO ADOPTION AND ULTIMATELY SAFER CONCURRENT SOFTWARE. TECHNICALLY THE PROJECT FORMALIZES SCENARIOS AS A PROGRAM'S EXECUTION QUOTIENT, WHICH CAPTURES A SMALL SET OF REPRESENTATIVE INTERLEAVED EXECUTIONS THAT NONETHELESS GENERALIZE---VIA COMMUTATIVITY---TO THE SET OF ALL EXECUTIONS, EVEN WITH UNBOUNDEDLY MANY THREADS AND INFINITE STATE SPACES. THE PROJECT AIMS TO DEMONSTRATE THAT THESE QUOTIENTS CAN BE DESCRIBED SUCCINCTLY IN A CONVENIENT LANGUAGE; THAT THE PROOF OF QUOTIENT SOUNDNESS (I.E., THAT THE ABSTRACTION COVERS ALL EXECUTIONS) CAN BE SYSTEMATIZED THROUGH NEW FORMS OF INDUCTION THAT INTERACT WITH COMMUTATIVITY; THAT IT IS POSSIBLE TO AUTOMATICALLY DERIVE QUOTIENTS DIRECTLY FROM SOURCE CODE; AND THAT PROGRAMMERS CAN USE THESE DERIVATIONS AND QUERY THEM TO BETTER UNDERSTAND THE CONCURRENT BEHAVIOR OF THEIR IMPLEMENTATIONS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

COLLABORATIVE RESEARCH: SIZING UP PHYSICAL COMPUTING TO EXPLORE THRESHOLD CONCEPTS IN CYBER-PHYSICAL SYSTEMS -AS THE APPLICATIONS OF CYBER-PHYSICAL SYSTEMS (CPS) CONTINUE TO ADVANCE, IT IS BECOMING CRITICAL TO ADDRESS THE EDUCATIONAL CHALLENGES AND NEEDS ASSOCIATED WITH CULTIVATING A COMPETITIVE U.S. WORKFORCE WITH COMPETENCE IN CPS. HOWEVER, GIVEN THE RELATIVE YOUTH OF CPS TECHNOLOGY, A CRUCIAL CHALLENGE LIES IN CHARACTERIZING WHAT KEY CONCEPTS ARE NECESSARY FOR CPS MASTERY. FURTHERMORE, THE LACK OF COLLABORATIVE CPS LEARNING TOOLS HAS RESULTED IN A TREND OF SOLITARY LEARNING PRACTICES AMONG STUDENTS, WHICH CONTRADICTS THE COLLABORATIVE NATURE OF CPS DESIGN PRACTICE. THIS PROJECT SEEKS TO OVERCOME THESE CHALLENGES BY DESIGNING AND IMPLEMENTING A PHYSICAL COMPUTING TESTBED THAT WILL FOSTER PROBLEM-BASED, COLLABORATIVE LEARNING OF CPS CONCEPTS. THE TESTBED WILL ALLOW GROUPS OF STUDENTS, CO-LOCATED AROUND A TABLE, TO INTERACT WITH CPS USING A TANGIBLE-USER INTERFACE. AS A GENERATIVE SOURCE OF INFORMAL LEARNING AND SENSE-MAKING, THE TESTBED WILL HELP FOSTER A SOCIAL APPROACH TO CPS EDUCATION, WHILE ADVANCING OUR UNDERSTANDING OF THE DISCIPLINE-SPECIFIC CONCEPTS REQUIRED FOR CPS MASTERY. THE PROJECT AIMS TO DEVELOP A PHYSICAL COMPUTING TESTBED FOR COLLABORATIVE, PROBLEM-BASED CPS LEARNING TO EXPLORE AND CHARACTERIZE THE CPS DISCIPLINE?S THRESHOLD CONCEPTS ? WHICH REPRESENT TRANSFORMATIVE, AND POTENTIALLY DIFFICULT-TO-GRASP, IDEAS THAT INTEGRATE MULTIPLE CONCEPTS IN A GIVEN DISCIPLINE. THE PROJECT WILL FIRST ENGAGE CPS EXPERTS IN ACADEMIA AND INDUSTRY THROUGH A DELPHI STUDY TO SEEK CONSENSUS ON THE FUNDAMENTAL CONCEPTS NECESSARY FOR CPS MASTERY. NEXT, THE RESEARCH APPROACH WILL INTERSECT THRESHOLD CONCEPTS WITH COLLABORATIVE PROBLEM-BASED LEARNING (PBL) TO IDENTIFY KEY FORMATIVE LEARNING EXPERIENCES NECESSARY FOR MASTERING CPS DESIGN CONCEPTS. THESE KEY FORMATIVE LEARNING EXPERIENCES, ANCHORED IN STUDENT-CENTERED THRESHOLD CONCEPTS, WILL BE INVESTIGATED BY ENGAGING STUDENTS IN MULTI-STAGE PROBLEM SCENARIOS CALLED MODEL-ELICITING ACTIVITIES. DURING THE MODEL-ELICITING ACTIVITIES, THEIR INTERACTIONS WITH ONE ANOTHER AND THE TESTBED WILL BE ANALYZED USING CONSTRUCTIVIST GROUNDED THEORY. A COMPREHENSIVE CPS CONCEPT INVENTORY AND INNOVATIVE CLASSIFICATION OF THRESHOLD CONCEPTS WILL BE CREATED BY INTEGRATING THE VARIOUS DATA SOURCES, LEADING TO A NEW UNDERSTANDING OF HOW BEST TO LEVERAGE PBL AND PHYSICAL COMPUTING IN CPS EDUCATION. THE FINDINGS WILL IMPROVE CPS LEARNING CAPABILITIES IN ACADEMIA AND ENHANCE CPS DESIGN CAPABILITIES FOR PRACTITIONERS, STRENGTHENING THE CORE FUNCTION OF U.S. FEDERAL AGENCIES IN ADMINISTERING CPS ECOSYSTEMS WITH BROAD SOCIETAL IMPACTS. THE TESTBED WILL EMPOWER UNDERGRADUATE STUDENTS TO ENGAGE IN CPS LEARNING THROUGH COLLABORATIVE PLAY, AND THE KNOWLEDGE GENERATED WILL BENEFIT INDUSTRY, DEFENSE, AND CRITICAL INFRASTRUCTURE. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

CCRI: MEDIUM: COLLABORATIVE RESEARCH: HARDWARE-IN-THE-LOOP AND REMOTELY-ACCESSIBLE/CONFIGURABLE/PROGRAMMABLE INTERNET OF THINGS (IOT) TESTBEDS

IN VIVO IMAGING PLATFORM FOR ECTOPIC PREGNANCY RESEARCH IN MOUSE MODELS

PFI: STEVENS ENVIRONMENTAL ENTREPRENEURSHIP PROGRAM

CAREER: BIOMECHANICS OF TENSION-INDUCED LUNG TISSUE FRACTURE AND SUBSEQUENT PULMONARY AIR LEAK

CAREER: TOWARDS DEEP INTERPRETABLE PREDICTIONS FOR MULTI-SCOPE TEMPORAL EVENTS

NONLINEAR-OPTICAL PSEUDO ATOMS ON CHIP

VIBRATION ANALYSIS OF ENGINEERING STRUCTURES WITH FRICTIONAL CONTACT USING A NOVEL EQUALITY-BASED FRAMEWORK -MANY CRITICAL ENGINEERING SYSTEMS, RANGING FROM AIRCRAFT ENGINES AND POWER TURBINES TO ROBOTIC DEVICES AND PRECISION INSTRUMENTS, CONTAIN COMPONENTS THAT INTERACT THROUGH FRICTION AND CONTACT. THESE INTERACTIONS ARE DIFFICULT TO MODEL, YET THEY PLAY A VITAL ROLE IN DETERMINING THE RELIABILITY, EFFICIENCY, AND DURABILITY OF SUCH SYSTEMS. INACCURATE VIBRATION PREDICTIONS CAN LEAD TO FATIGUE, WEAR, OR EVEN FAILURE, WITH SIGNIFICANT SAFETY AND ECONOMIC CONSEQUENCES. THE RESEARCH FUNDED BY THIS AWARD AIMS TO PROVIDE NEW MATHEMATICAL TOOLS AND COMPUTATIONAL METHODS TO MORE ACCURATELY SIMULATE THE COMPLEX DYNAMIC BEHAVIOR OF STRUCTURES WITH FRICTIONAL CONTACT. BY REFORMULATING HOW THESE INTERACTIONS ARE REPRESENTED, THIS RESEARCH AIMS TO ELIMINATE LONGSTANDING SIMPLIFICATIONS AND APPROXIMATIONS THAT LIMIT CURRENT ANALYSIS TECHNIQUES. THESE ADVANCES WILL HELP ENGINEERS BETTER UNDERSTAND AND PREDICT THE PERFORMANCE OF ENGINEERING SYSTEMS, ENABLING SAFER AND MORE EFFICIENT DESIGNS AND LONGER-LASTING TECHNOLOGIES. THE OUTCOMES ARE EXPECTED TO BENEFIT MULTIPLE INDUSTRIES AND SUPPORT BROADER NATIONAL GOALS RELATED TO ECONOMIC PROSPERITY, ENERGY EFFICIENCY, AND SECURITY. THE PROJECT ALSO SUPPORTS THE TRAINING OF GRADUATE AND UNDERGRADUATE STUDENTS AND WILL BE INTEGRATED INTO ENGINEERING CURRICULA. OUTREACH ACTIVITIES WILL INTRODUCE ENGINEERING TOPICS TO HIGH SCHOOL STUDENTS THROUGH HANDS-ON DEMONSTRATIONS AND MENTORING, THUS FOSTERING INTEREST IN STEM CAREERS. THE RESEARCH OBJECTIVE OF THIS PROJECT IS TO CREATE A NOVEL EQUALITY-BASED FRAMEWORK FOR MODELING AND ANALYZING THE VIBRATIONS OF LARGE-SCALE STRUCTURAL SYSTEMS WITH NONLINEARITIES ARISING FROM FRICTION AND UNILATERAL CONTACT. UNLIKE TRADITIONAL METHODS THAT HANDLE NON-SMOOTH BEHAVIOR BY INTRODUCING PENALIZATION, REGULARIZATION, MASSLESS INTERFACE, OR TIME-DOMAIN APPROXIMATIONS, THE APPROACH IN THIS PROJECT REFORMULATES FRICTION AND UNILATERAL CONTACT LAWS AS EXACT NON-SMOOTH EQUALITIES. THIS ALLOWS THE APPLICATION OF ESTABLISHED FREQUENCY-DOMAIN TECHNIQUES, SUCH AS WEIGHTED RESIDUAL AND HARMONIC BALANCE METHODS, TO COMPUTE PERIODIC RESPONSES, ASSESS STABILITY, AND PERFORM NONLINEAR MODAL ANALYSIS. THE METHODOLOGY WILL BE EXTENDED TO HANDLE A VARIETY OF CONTACT AND FRICTION LAWS, TWO- AND THREE-DIMENSIONAL FRICTIONAL CONTACT, INTERFACES WITH MULTIPLE CONTACT POINTS, AND FINITE ELEMENT DISCRETIZATIONS. IN ADDITION, REDUCED-ORDER MODELS FOR THE VIBRATION OF LARGE-SCALE STRUCTURES WILL BE CONSTRUCTED BY DEFINING INVARIANT MANIFOLDS FOR SYSTEMS WITH FRICTIONAL CONTACT CONSTRAINTS, ENABLING HIGHLY EFFICIENT SIMULATIONS OF COMPLEX DYNAMICS. NON-SMOOTH MODAL ANALYSIS WILL ALSO BE GENERALIZED TO SYSTEMS UNDER PERIODIC EXCITATION, YIELDING COMPACT MODELS FOR FORCED RESPONSE PREDICTION. THE NEW FORMULATIONS WILL BE BENCHMARKED AGAINST CONVENTIONAL TECHNIQUES AND APPLIED TO LARGE-SCALE ENGINEERING ASSEMBLIES, SUCH AS BLADED DISKS WITH SHROUDS, FRICTION DAMPERS, AND BLADE ROOT INTERFACES, DEMONSTRATING THE EFFECTIVENESS AND VERSATILITY OF THE APPROACH. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

CAREER: MULTIDISCIPLINARY AND LIFE CYCLE HOLISTIC SUSTAINABLE DESIGN

THIS GRANT SHALL BE PERFORMED IN ACCORDANCE WITH THE STATEMENT OF WORK ENTITLED, "STOCHASTIC COGNITIVE LINGUISTIC BEHAVIOR MODELS FOR SEMANTIC SENSIN

COLLABORATIVE RESEARCH: CSR: CORE: MEDIUM: SCALING UNIX/LINUX SHELL PROGRAMS -THE ?SHELL? IS THE GLUE THAT HOLDS MODERN COMPUTER SYSTEMS TOGETHER: IT IS THE PROGRAMMING LANGUAGE THAT CONNECTS COMPONENTS AND MANAGES SYSTEMS; IT IS THE QUICK-AND-DIRTY LANGUAGE FOR WRITING SCIENTIFIC WORKFLOWS AND DATA ANALYSIS; IT IS THE CONTROL HATCH THAT OFFERS SKILLED USERS DIRECT ACCESS TO THEIR COMPUTER'S INNER-WORKINGS. SHELL PROGRAMMING REMAINS UBIQUITOUS ?STEADILY IN THE TOP 10 MOST POPULAR PROGRAMMING LANGUAGES? PARTLY BECAUSE IT ALLOWS NON-EXPERT DEVELOPERS TO COMBINE COMPONENTS AVAILABLE IN ANY PROGRAMMING LANGUAGE WITH LITTLE-TO-NO UNDERSTANDING OF THEIR INTERNALS. UNFORTUNATELY, THIS BLACK-BOX, LANGUAGE-AGNOSTIC COMPOSITION HINDERS AUTOMATED ACCELERATION OF SHELL PROGRAMS. THIS PROJECT WILL DEVELOP TECHNIQUES TO ACCELERATE SHELL PROGRAMS WITHOUT REQUIRING INPUT FROM SHELL PROGRAMMERS AND LITTLE-TO-NO INPUT FROM THE AUTHORS OF INDIVIDUAL COMPONENTS. THIS WORK'S APPROACH (1) BUILDS ON THE REAL-WORLD SUCCESS OF PRIOR RESEARCH BY THE PIS (THAT REQUIRES MORE USER INPUT), (2) BRINGS TOGETHER EXPERTISE IN SEVERAL SUBFIELDS OF COMPUTER SCIENCE ?PARALLEL AND DISTRIBUTED SYSTEMS, PROGRAMMING LANGUAGES, AND FORMAL METHODS? AND (3) OFFERS SYNERGY. THE INDIVIDUAL TECHNIQUES EACH OFFER SIGNIFICANT BENEFITS, BUT YIELD A TRANSFORMATIVE WHOLE. BY ENABLING PRACTICAL, PUSH-BUTTON ENHANCEMENT OF A REAL-WORLD, PERVASIVELY-USED PROGRAMMING LANGUAGE, THE PROPOSED WORK PROMISES TO SIGNIFICANTLY ACCELERATE EXISTING AND NEW SHELL PROGRAMS WITHOUT ANY EFFORT FROM THEIR DEVELOPERS, WITHOUT ANY CHANGES TO EXISTING INFRASTRUCTURE, AND WHILE MAINTAINING COMPATIBILITY WITH PRIOR RESULTS. THE SHELL'S UBIQUITY MEANS THESE SPEEDUPS WILL HAVE BROAD IMPACT, ESPECIALLY IN DISCIPLINES THAT USE COMPUTING AS A TOOL TO SOLVE PROBLEMS IN THEIR RESPECTIVE FIELDS, E.G., BIOINFORMATICS, DATA SCIENCE, AND ECONOMICS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

CAREER: DATA-DRIVEN PRIORITIZATION AND CONTROL OF DISINFECTION BYPRODUCTS IN DRINKING WATER -DRINKING WATER IS IMPORTANT FOR OUR HEALTH. DISINFECTION HELPS KEEP THE WATER SAFE AND CLEAN. HOWEVER, SOME DISINFECTION BYPRODUCTS (DBPS) CAN BE HARMFUL. THESE DBPS FORM WHEN WATER TREATMENT PLANTS USE CHEMICALS LIKE CHLORINE TO KILL GERMS. THERE ARE MANY DIFFERENT DBPS, AND IDENTIFYING ALL OF THEM WOULD BE COSTLY AND DIFFICULT FOR WATER TREATMENT PLANTS. THIS PROJECT WILL USE MACHINE LEARNING (ML) TO IDENTIFY THE TOXICITY OF DBPS IN DRINKING WATER AND DEVELOP STRATEGIES FOR REDUCING THE PRESENCE OF HIGH-RISK DBPS IN DRINKING WATER TREATMENT. THE RESULTS FROM THE PROJECT WILL IMPROVE DRINKING WATER SAFETY AND PUBLIC HEALTH. THE PROJECT WILL TRAIN STUDENTS TO USE AI AND DATA TO SOLVE PROBLEMS OF WATER QUALITY. THE PROJECT WILL MENTOR GRADUATE AND UNDERGRADUATE STUDENTS AT SOUTH DAKOTA SCHOOL OF MINES AND TECHNOLOGY, PREPARING THEM FOR FUTURE CAREERS IN SCIENCE, ENGINEERING, AND DATA SCIENCE. DISINFECTION BYPRODUCTS (DBPS) ARE A GROUP OF CHEMICALS FORMED DURING THE WATER DISINFECTION PROCESS WHEN DISINFECTANTS SUCH AS CHLORINE REACT WITH ORGANIC MATTER IN WATER. THESE CHEMICALS ARE OFTEN TOXIC AND PRESENT IN TREATED DRINKING WATER. THE CONSIDERABLE NUMBER OF DBPS, COUPLED WITH LIMITED DATA ON THEIR OCCURRENCE AND TOXICITY, COMPLICATES EFFORTS TO DETERMINE WHICH DBPS SHOULD BE PRIORITIZED FOR FUTURE STUDIES AND REGULATIONS. CURRENT METHODS FOR ASSESSING DBP RISKS RELY ON LIMITED OCCURRENCE AND TOXICOLOGICAL DATA AND THUS FACE CHALLENGES IN EFFECTIVELY IDENTIFYING WHICH DBPS NEED THE MOST ATTENTION. THIS PROJECT WILL INTEGRATE MACHINE LEARNING (ML) AND LABORATORY EXPERIMENTS TO (1) CREATE A DATABASES FOR BOTH REGULATED AND UNREGULATED DBPS, ADDRESSING CRITICAL GAPS IN AVAILABLE OCCURRENCE AND TOXICITY DATA, (2) PRIORITIZE HIGH-RISK DBPS BY ANALYZING THEIR OCCURRENCE FREQUENCY, LEVELS, AND TOXICITY, BASED ON THEIR POTENTIAL HEALTH IMPACTS, AND (3) DEVELOP PREDICTIVE TOOLS FOR HIGH-RISK DBPS, ENABLING MORE INFORMED DECISION-MAKING FOR FUTURE REGULATIONS AND WATER TREATMENT STRATEGIES. THE RESULTS OF THE PROJECT WILL CONTRIBUTE TO MINIMIZING HARMFUL DBPS IN DRINKING WATER AND IMPROVING PUBLIC HEALTH. THE EDUCATIONAL ACTIVITIES FROM THIS PROJECT INCLUDE CREATING STUDENT-LED STEM SUMMER CAMPS FOR K-12 STUDENTS, DEVELOPING SCAFFOLDED EDUCATIONAL MODULES TO DEVELOP ML LITERACY IN STUDENTS, AND CONDUCTING WORKSHOPS FOR STUDENTS ON NAVIGATING GRADUATE STUDIES. THE SUCCESSFUL COMPLETION OF THIS PROJECT WILL HELP ADVANCE THE DESIGN AND IMPLEMENTATION OF DATA-DRIVEN SOLUTIONS IN ENVIRONMENTAL ENGINEERING, CONTRIBUTING TO IMPROVED WATER QUALITY, PUBLIC HEALTH, AND THE DEVELOPMENT OF FUTURE SCIENTIFIC LEADERS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

SHF: SMALL: LEARNING CIRCUIT NETWORKS FROM MEASUREMENTS -RECENT GRAPH-LEARNING TECHNIQUES EXPLOIT BOTH GRAPH TOPOLOGICAL PROPERTIES AND NODE-FEATURE (ATTRIBUTE) INFORMATION TO ACHIEVE PROMISING RESULTS FOR VARIOUS IMPORTANT APPLICATIONS SUCH AS VERTEX (DATA) CLASSIFICATION, LINK PREDICTION (RECOMMENDATION SYSTEMS), COMMUNITY DETECTION, DRUG DISCOVERY, PARTIAL DIFFERENTIAL EQUATION (PDE) SOLVERS, AND ELECTRONIC DESIGN AUTOMATION (EDA). ON THE OTHER HAND, GRAPH LEARNING CAN STILL BE EXTREMELY CHALLENGING WHEN THERE EXISTS ONLY PARTIAL OR NO KNOWLEDGE ABOUT THE UNDERLYING GRAPH TOPOLOGIES. FORTUNATELY, RECENT RESEARCH SHOWS THAT IT IS POSSIBLE TO LEARN GRAPH TOPOLOGIES FROM NODE-FEATURE (ATTRIBUTE) DATA SO THAT EXISTING GRAPH-LEARNING ALGORITHMS CAN BE APPLIED SUBSEQUENTLY. HOWEVER, EVEN THE STATE-OF-THE-ART GRAPH-TOPOLOGY-LEARNING ALGORITHMS DO NOT SCALE TO LARGE DATA SETS DUE TO THEIR HIGH COMPUTATIONAL COMPLEXITY, WHICH MAY PROHIBIT THEIR APPLICATIONS IN REAL-WORLD LARGE-SCALE GRAPH-LEARNING TASKS, SUCH AS THOSE ADOPTED FOR INTEGRATED-CIRCUIT NETWORKS INVOLVING BILLIONS OF COMPONENTS. THIS PROJECT IS ALSO LIKELY TO SPARK NEW RESEARCH IN MANY OTHER RELATED FIELDS, SUCH AS COMPLEX SYSTEM/NETWORK MODELING, MODEL ORDER REDUCTION, COMPUTATIONAL BIOLOGY, PRECISION MEDICINE, AND TRANSPORTATION NETWORKS. THE SOURCE CODE OF THE DEVELOPED ALGORITHMS WILL BE RELEASED ON A PUBLIC WEBSITE MANAGED BY THE PI TO FACILITATE TECHNOLOGY TRANSFERS TO THE INDUSTRY, ESPECIALLY TO THE LEADING EDA COMPANIES. THIS RESEARCH PROJECT WILL INVESTIGATE HIGHLY SCALABLE YET SAMPLE-EFFICIENT SPECTRAL METHODS FOR LEARNING GRAPH TOPOLOGIES FROM POTENTIALLY HIGH-DIMENSIONAL DATA SAMPLES, SUCH AS VOLTAGE AND CURRENT MEASUREMENTS IN CIRCUIT NETWORKS. THE PROPOSED APPROACH IS BASED ON A NOVEL SPECTRAL-GRAPH DENSIFICATION FRAMEWORK TO ALLOW FOR MORE EFFICIENT ESTIMATIONS OF ATTRACTIVE GAUSSIAN MARKOV RANDOM FIELDS (GMRFS). A UNIQUE PROPERTY OF THE LEARNED GRAPHS IS THAT THE EFFECTIVE-RESISTANCE DISTANCES ON THE LEARNED GRAPH WILL ENCODE THE SIMILARITIES BETWEEN THE ORIGINAL DATA SAMPLES. THE SUCCESS OF THIS RESEARCH PLAN WILL IMMEDIATELY LEAD TO THE DEVELOPMENT OF MORE SCALABLE DATA-DRIVEN, PHYSICS-INFORMED EDA ALGORITHMS FOR MODELING, SIMULATION, OPTIMIZATION, AND VERIFICATION OF INTEGRATED CIRCUITS (ICS). THE ACCOMPLISHED THEORETICAL RESULTS WILL LIKELY ADVANCE STATE OF THE ART IN SPECTRAL GRAPH THEORY, DIMENSIONALITY REDUCTION, SCIENTIFIC COMPUTATION, DATA VISUALIZATION, AND MACHINE LEARNING (ML). THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

TC: SMALL: DISTRIBUTED PRIVACY-PRESERVING POLICY RECONCILIATION

CAREER: MODELING TRUST DYNAMICS AND SYSTEM ADAPTATION FOR HUMAN-AI COLLABORATION IN ENGINEERING DESIGN -THIS FACULTY EARLY CAREER DEVELOPMENT PROGRAM (CAREER) PROJECT SUPPORTS RESEARCH AND EDUCATION FOCUSED ON TRUST IN HUMAN-ARTIFICIAL INTELLIGENCE (AI) COLLABORATION DURING EARLY-STAGE ENGINEERING DESIGN. IN OPEN-ENDED, CREATIVE DESIGN CONTEXTS, TRUST GOVERNS HOW DESIGNERS ENGAGE WITH AND RELY ON AI-GENERATED SUGGESTIONS, YET THIS RELIANCE IS OFTEN IMPLICIT, CONTEXT-DEPENDENT, AND DIFFICULT TO CAPTURE BY TRADITIONAL ACCEPTANCE-BASED OR POST-HOC SURVEY MEASURES. THIS PROJECT ADVANCES FUNDAMENTAL KNOWLEDGE BY MODELING TRUST AS A CONTINUOUS, TIME-VARYING LATENT STATE VARIABLE GROUNDED IN DESIGNERS? AFFECTIVE AND COGNITIVE PROCESSES, CREATING A FOUNDATION FOR TRUST-AWARE HUMAN-AI INTERACTION IN EARLY-STAGE DESIGN. THIS CAREER AWARD ADVANCES THEORY AND METHODS FOR TRUST IN HUMAN-AI COLLABORATION THROUGH TWO INTEGRATED RESEARCH ACTIVITIES: (1) DEVELOPING EMPIRICAL DATASETS AND COMPUTATIONAL INFERENCE MODELS THAT ESTIMATE TRUST DYNAMICS AS A CONTINUOUS, NORMALIZED QUANTITY FROM SYNCHRONIZED BEHAVIORAL, SELF-REPORT, AND PSYCHOPHYSIOLOGICAL INDICATORS DURING REAL-TIME DESIGN INTERACTION; AND (2) FORMALIZING TRUST-AWARE AI ADAPTATION STRATEGIES THAT SPECIFY HOW AI FEEDBACK BEHAVIOR SHOULD ADJUST TO SUPPORT CALIBRATED RELIANCE AND EFFECTIVE COLLABORATION. EDUCATION AND OUTREACH ACTIVITIES WILL DEPLOY AI-ASSISTED DESIGN TOOLS IN UNDERGRADUATE ENGINEERING DESIGN COURSES AND PRE-COLLEGE DESIGN BOOTCAMPS, AND WILL INTEGRATE MULTIMODAL SENSING TO ENABLE ADAPTIVE, PERSONALIZED FEEDBACK THAT SUPPORTS COGNITIVELY DEMANDING LEARNING. THIS RESEARCH INCLUDES ADVANCING THE DESIGN AND DEPLOYMENT OF TRUST-AWARE AI SYSTEMS THAT IMPROVE ENGINEERING DECISION QUALITY AND RELIABILITY, REDUCE DESIGN CYCLE TIME AND DOWNSTREAM REWORK, AND SUPPORT EFFECTIVE HUMAN-AI COLLABORATION ACROSS HIGH-STAKES INDUSTRIAL DOMAINS SUCH AS MANUFACTURING, HEALTHCARE, AND INFRASTRUCTURE. IN PARALLEL, THE PROJECT WILL ENHANCE STEM EDUCATION AND WORKFORCE DEVELOPMENT BY INTEGRATING AI-ASSISTED DESIGN AND PERSONALIZED LEARNING TOOLS INTO UNDERGRADUATE AND PRE-COLLEGE PROGRAMS, BROADENING PARTICIPATION AND PREPARING AN AI-LITERATE ENGINEERING WORKFORCE. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

COLLABORATIVE RESEARCH: FW-HTF-R: THE FUTURE OF NEWS WORK: HUMAN-TECHNOLOGY COLLABORATION FOR JOURNALISTIC RESEARCH AND NARRATIVE DISCOVERY

CAREER: LEARNING FROM OBSERVATIONAL DATA WITH KNOWLEDGE

ADVANCING UNDERSTANDING OF AND PREDICTIVE MODELING CAPABILITIES FOR HIGH-SPEED SHOCK-INDUCED DROPLET AEROBREAKUP AND SURFACE DAMAGE

THE PROPERTIES OF MIXED PHASE- AND ICE CLOUDS IN THE ARCTIC USING A TETHERED BALLOON SYSTEM DEPLOYED IN SUPPORT OF THE INTERNATIONAL POLAR YEAR (IPY)

ADVANCE STEVENS: CREATING A SUSTAINABLE CULTURE THAT FACILITATES RECRUITMENT, RETENTION AND ADVANCEMENT OF WOMEN FACULTY IN STEM

"MULTI-SCALE SIMULATION ASSISTED DESIGN OF HYBRID OXIDATION TOLERANT COMPOSITES"

CAREER: INVESTIGATION OF THERMAL TRANSPORT IN MOIR? PATTERN STRUCTURED MATERIALS TO PUSH THE EXTREMES OF THERMAL MODULATION -THIS AWARD IS FUNDED IN WHOLE OR IN PART UNDER THE AMERICAN RESCUE PLAN ACT OF 2021 (PUBLIC LAW 117-2). WEARABLE DEVICES MADE OF TWO-DIMENSIONAL (2D) MATERIALS BASED ON ATOMICALLY THIN CRYSTALS SUCH AS GRAPHENE PROMISE TO REVOLUTIONIZE MODERN MICROELECTRONICS BY ENABLING HIGH FLEXIBILITY, INTRINSIC THINNESS, AND UNPRECEDENTED DEVICE PERFORMANCE. HOWEVER, ONE SIGNIFICANT CHALLENGE TO THE ADVANCEMENT OF DIVERSE AND TRANSFORMATIVE APPLICATIONS IS GAINING CONTROL OVER THERMAL TRANSPORT. FOR EXAMPLE, THERMAL TRANSPORT NEEDS TO BE INCREASED TO COMPENSATE FOR THE HEATING ISSUE CAUSED BY THE REDUCED THERMAL CONDUCTIVITY AT HIGH LEVELS OF STRESS AND DECREASED FOR EFFICIENT THERMOELECTRIC ENERGY CONVERSION AND THERMAL INSULATION DEVICES. THE OVERARCHING GOAL OF THIS RESEARCH IS TO ACHIEVE EFFICIENT, IN-SITU, AND REVERSIBLE THERMAL CONTROL VIA MANIPULATING 2D MATERIALS? MOIR? PATTERNS, WHICH ARE CREATED BY ADJUSTING THE RELATIVE TWIST ANGLE OF MISMATCHING CRYSTAL LATTICE BETWEEN THE TWO 2D MATERIALS. THE KNOWLEDGE LEARNED WILL POTENTIALLY PUSH THE THERMAL MODULATION LIMITS IN SKIN-LIKE WEARABLE DEVICES MADE OF ATOMICALLY THIN 2D MATERIALS, AND ENABLE MODERN DEVICES FROM BEYOND-SI ELECTRONICS AND SENSORS TO SUPERCONDUCTING THERMAL SWITCHES. THIS PROJECT WILL TIGHTLY INTEGRATE RESEARCH, EDUCATION AND OUTREACH, WITH INTERACTIVE GAMES, WORKSHOPS, NOVEL CURRICULUM, HANDS-ON RESEARCH MENTORING, AND RESEARCH TOOL SHARING TO ENGAGE STUDENTS IN THERMAL TECHNOLOGY. THE PROPOSED RESEARCH AIMS TO CREATE NEW KNOWLEDGE ABOUT CRYSTAL LATTICE ORDER ENABLED THERMAL TRANSPORT AND DEVELOP TWIST ANGLE TUNING AS A POWERFUL STRATEGY FOR THERMAL MODULATION. THE TWIST ANGLE TUNING METHOD APPLIED TO 2D MOIR? PATTERN STRUCTURED MATERIALS PROVIDES AN IN-SITU, CONTINUOUS AND REVERSIBLE TUNING STRATEGY WITHOUT THE NEED FOR CHANGING THE MATERIALS? CHEMICAL COMPOSITION, THEREBY BYPASSING THE CHALLENGES ASSOCIATED WITH TRADITIONAL WEARABLE DEVICES. EXPERIMENTAL APPROACHES OF MATERIALS SYNTHESIS, DEVICE NANOFABRICATION AND THERMAL CHARACTERIZATION ARE EMPHASIZED AND REINFORCED BY ANALYTICAL MODELING. BY SYSTEMATICALLY VARYING TWIST ANGLE AS WELL AS THE 2D MOIR? PATTERNS? MECHANICAL DEFORMATION AND GLOBAL GEOMETRY, IN-DEPTH UNDERSTANDING OF LATTICE ORDERS, LATTICE CONSTANTS, GEOMETRY AND THERMAL CONDUCTIVITY WILL BE UNCOVERED. SUCH KNOWLEDGE WILL BE A MAJOR LEAP IN FUNDAMENTAL UNDERSTANDING OF THERMAL PHYSICS, ESTABLISH THERMAL MODULATION PRINCIPLES TO ACHIEVE DESIRED THERMAL TRANSPORT OUTCOMES, AND REVOLUTIONIZE FUTURE WEARABLE DEVICE PLATFORMS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

NANO-ENGINEERING OF SUPERHYDROPHOBIC SURFACES FOR LIGHT METAL ANTI-CORROSION

DISTRIBUTIONAL REINFORCEMENT LEARNING FOR SAFE AUTONOMOUS NAVIGATION

CAREER: EASE: ENHANCING THE SECURITY OF PERVASIVE WIRELESS NETWORKS BY EXPLOITING LOCATION

FIA: COLLABORATIVE RESEARCH: NEBULA: A FUTURE INTERNET THAT SUPPORTS TRUSTWORTHY CLOUD COMPUTING

CAREER: NOVEL REPRESENTATIONS FOR DISTRIBUTED CONTROL OF STRING NETWORKS IN VEHICLE PLATOONING AND SUPPLY CHAIN MANAGEMENT

DEVELOPMENT OF WIRELESS ARTIFICIAL INTELLIGENCE-POWERED MULTI-FUNCTIONAL FIBER OPTIC SENSORS FOR HYDROGEN PRODUCTION IN GASIFICATION-BASED SYSTEMS. THE AWARD AIMS TO DEVELOP AND TEST THE PERFORMANCE OF A WIRELESS ARTIFICIAL INTELLIGENCE (AI)-POWERED MULTI-FUNCTIONAL FIBER OPTIC SENSOR SYSTEM FOR GASIFICATION-BASED SYSTEMS. A SENSOR SYSTEM WILL BE DESIGNED TO SENSE HIGH TEMPERATURE, PRESSURE, STRAIN, HYDROGEN CONCENTRATION, CARBON MONOXIDE CONCENTRATION, CARBON DIOXIDE CONCENTRATION, AND FOULING SEVERITY, SIMULTANEOUSLY, AND IS KNOWN AS A MULTI-FUNCTIONAL SENSOR SYSTEM.

CAREER: CONSECUTIVE ASSEMBLY-AND-MINERALIZATION PROCESSED CALCIUM-SILICATE-HYDRATE NACRE WITH HIGH SPECIFIC FLEXURAL STRENGTH AND FRACTURE TOUGHNESS

SHF: SMALL: SPECTRAL REDUCTION OF LARGE GRAPHS AND CIRCUIT NETWORKS

COE MARITIME SECURITY CENTER

SATC: CORE: SMALL: TOWARD USABLE AND UBIQUITOUS TRUST INITIALIZATION AND SECURE NETWORKING IN WIRELESS AD HOC NETWORKS

CAREER: SYNTHETIC ULTRA-WIDEBAND MILLIMETER-WAVE IMAGING FOR TISSUE DIAGNOSTICS

CAREER: ADDITIVE BIOMANUFACTURING AN ENGINEERED STEM CELL MICROENVIRONMENT

SATC: CORE: SMALL: SECURING NETWORK EMBEDDING AGAINST PRIVACY ATTACKS

CHS: SMALL: EXPLORING DESIGN AND EVALUATION SPACE THROUGH CROWDS AND COMMUNITIES

CAREER: BELIEF SPACE PLANNING AND LEARNING FOR UNCERTAINTY-IMMERSED UNDERWATER ROBOTS

VIRTUAL ENVIRONMENTS FOR COLLABORATIVE LEARNING

MRI: ACQUISITION OF A TRANSMISSION ELECTRON MICROSCOPE FOR MATERIALS RESEARCH

III: SMALL: MOVING BEYOND KNOWLEDGE TO ACTION: EVALUATING AND IMPROVING THE UTILITY OF CAUSAL INFERENCE

MARITIME CYBERSECURITY - BUILDING CAPACITY IN CRITICAL INFRASTRUCTURE PROTECTION

CHS: SMALL: COLLECTIVE DESIGN THROUGH REMIXING

TWC: SMALL: WORKFLOWS AND RELATIONSHIPS FOR END-TO-END DATA SECURITY IN COLLABORATIVE APPLICATIONS

DURIP: SMALL ANGLE X-RAY SCATTERING (SAXS) INSTRUMENT FOR NON-DESTRUCTIVE CHARACTERIZATIONS OF NANOBUBBLE KINETICS AND DYNAMICS ON NANOSTRUCTURED SUR

CAREER: PERSONALIZING SENSORY-DRIVEN COMPUTERIZED INTERFACES TO OPTIMIZE MOTOR REHABILITATION -PERSONS WITH AN INJURY TO THE BRAIN OR SPINAL CORD OFTEN UNDERGO PHYSICAL TRAINING TO RECOVER MOVEMENT ABILITIES NEEDED FOR DAILY ACTIVITIES. TO MOTIVATE PARTICIPATION IN THIS ?MOTOR THERAPY,? VIRTUAL REALITY (VR) TECHNOLOGIES ARE INCREASINGLY USED. VR CAN BE PROGRAMMED TO BE HIGHLY REALISTIC OR LOOK LIKE A GAME TO ENCOURAGE PARTICIPANTS. STILL, PERSONS WHO USE VR MOTOR THERAPY DO NOT ALWAYS ACHIEVE BETTER OUTCOMES THAN TRADITIONAL METHODS, PARTIALLY BECAUSE THEY ARE NOT PERSONALIZED TO EACH USER. IMPROVING VR THERAPY REQUIRES A GREATER UNDERSTANDING OF HOW PERSONS RESPOND TO PROGRAMMABLE FEATURES. TWO FEATURES THAT CAN IMPROVE VR MOTOR THERAPY ARE THE DIFFICULTY OF THE TRAINING TASK AND THE GUIDANCE (FEEDBACK) PROVIDED DURING TRAINING. VR INTERFACES THAT STIMULATE SENSES FOR GREATER IMMERSION CAN READILY PROVIDE TRAINING GUIDANCE USING AUGMENTED SENSORY FEEDBACK (ASF). THE METHOD OF ASF INVOLVES PROVIDING SENSORY (E.G., VISUAL, HAPTIC) CUES ABOUT THE DIRECTION AND MAGNITUDE IN WHICH A PERSON SHOULD MOVE DURING TRAINING. THIS PROJECT WILL EXAMINE HOW IMPAIRMENT IN FUNCTION AFFECTS PERSONAL PERFORMANCE, PHYSIOLOGIC RESPONSES, AND PERCEPTIONS DURING VR TRAINING THAT ADAPTS THE TASK DIFFICULTY AND ASF. THIS PROJECT WILL ADVANCE EDUCATION THROUGH SUPERVISED TRAINING OF HIGH-SCHOOL STUDENTS TO CUSTOM-DEVELOP VR REHABILITATION APPLICATIONS. THESE STUDENTS WILL FURTHER ENGAGE THE COMMUNITY BY PRESENTING THEIR WORK AT LABORATORY DEMONSTRATIONS TO K-12 STUDENTS FROM UNDER-RESOURCED DISTRICTS. IN ADDITION, THEY WILL RECEIVE CONSTRUCTIVE FEEDBACK ABOUT THEIR APPLICATIONS FROM CAREGIVERS, CLINICIANS, AND, MOST IMPORTANTLY, PERSONS WITH A SPINAL CORD INJURY (SCI) SERVING AS END-USER MENTORS. THE PROJECT WILL TEST THE HYPOTHESIS THAT MOTOR PERFORMANCE IMPROVES WHEN ADAPTING VR TRAINING FEATURES (I.E., TASK COMPLEXITY, ASF FOR GUIDANCE) BASED ON MEASURES INDICATING WELL-BEING AND PHYSICAL READINESS FOR TRAINING. THIS PROJECT?S TECHNICAL OBJECTIVES ARE: (1) CREATING REGRESSION-TYPE MODELS RELATING PERFORMANCE TO PERCEPTIONAL AND PHYSIOLOGIC MEASURES DURING VR MOTOR TRAINING AND AS A FUNCTION OF VARYING DISABILITY, AND (2) LEVERAGING THESE MODELS IN AN ADAPTIVE CONTROL SYSTEM USING POSITIVE REINFORCEMENT TO PERSONALIZE VR TRAINING FEATURES. EXPERIMENTS WILL INCLUDE PERSONS WITH SCI PERFORMING VR MOTOR REHABILITATION TASKS WITH A ROBOT-ARM AVATAR. THIS PROJECT FOCUSES ON THE SCI POPULATION, UNDER-SERVED BY VR MOTOR REHABILITATION YET IDEAL FOR FUNDAMENTAL SCIENTIFIC STUDY SINCE SCI CAN PRESENT AS A PHYSICAL DISABILITY WITH OR WITHOUT COGNITIVE IMPAIRMENT. PARTICIPANTS WILL GENERATE MUSCLE-ACTIVATION SIGNALS, MEASURED AT THE SKIN SURFACE, SERVING AS INPUTS TO A MACHINE-LEARNING ALGORITHM THAT DETECTS COMMAND INTENTION IN CONTROLLING THE AVATAR. DATA FROM THE VR ENVIRONMENT, BODY-MOUNTED SENSORS, AND SURVEYS WILL BE USED TO ASSESS CHANGES IN PERFORMANCE, PHYSIOLOGIC RESPONSES, AND PERCEPTIONS DURING TRAINING. AS SUCH, THIS PROJECT PROMOTES HUMAN-CENTERED TRAINING THAT CONSIDERS BOTH BODY AND MIND IN PROVIDING CLINICIANS WITH NEW AND DIVERSE DIMENSIONS OF PATIENT-SPECIFIC DATA TO PERSONALIZE HEALTHCARE FOR BETTER FUNCTION. THIS PROJECT HAS THE POTENTIAL TO GENERATE CRITICAL INSIGHTS INTO HOW USER-DEVICE INTERFACES ARE BEST ADAPTED FOR FUNCTION, INCLUDING HOW TO DELIVER SENSORY-DRIVEN TRAINING FOR MORE INTUITIVE CONTROL OF DEVICES (E.G., SMARTPHONES, VEHICLES, REMOTE-CONTROLLED ROBOTS). THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

SHF: SMALL: SYMBOLIC COMMUTATIVITY ANALYSIS FOR MULTICORE CONCURRENCY

FY2021 DARPA YFA: EFFECTIVE SOFTWARE MONITORING LEVERAGING HARDWARE DEBUGGING EXTENSIONS

FUNDING OPPORTUNITY NUMBER: DARPA-RA-21-03THE DEFENSE ADVANCED RESEARCH PROJECTS AGENCY (DARPA) YOUNG FACULTY AWARD (YFA) PROGRAM AIMS TO IDENTIFY AND ENGAGE RISING STARS IN JUNIOR RESEARCH POSITIONS IN ACADEMIA AND EQUIVALENT POSITIONS AT NON-PROFIT RESEARCH INSTITUTIONS, PARTICULARLY THOSE WITHOUT PRIOR DARPA FUNDING, TO EXPOSE THEM TO DEPARTMENT OF DEFENSE (DOD) NEEDS AND DARPA'S MISSION TO CREATE AND PREVENT TECHNOLOGICAL SURPRISE. YFA WILL PROVIDE HIGH-IMPACT FUNDING TO ELITE RESEARCHERS EARLY IN THEIR CAREERS TO DEVELOP INNOVATIVE NEW RESEARCH THAT ENABLES TRANSFORMATIVE DOD CAPABILITIES. ULTIMATELY, YFA IS DEVELOPING THE NEXT GENERATIONS OF RESEARCHERS FOCUSED ON NATIONAL SECURITY ISSUES.

DURIP: CONFIGURABLE AND MULTI-MODAL THIN FILM DEPOSITION SYSTEM FOR MULTI-FUNCTIONAL NANOSTRUCTURED SURFACES

CAREER: DEVELOPING ALGORITHMS FOR OBJECT-ADAPTIVE SUPER-RESOLUTION IN BIOMEDICAL IMAGING -ADVANCED BIOMEDICAL IMAGING TECHNOLOGY HAS REVOLUTIONIZED DIAGNOSIS AND TREATMENT BY PROVIDING STRUCTURAL AND FUNCTIONAL DETAILS. SPATIAL RESOLUTION OF BIOMEDICAL IMAGES, HOWEVER, SOMETIMES DO NOT SUFFICE FOR SPECIFIC APPLICATIONS DUE TO CONSTRAINTS OF IMAGE ACQUISITION TIME. CONVENTIONAL SOFTWARE-BASED IMPROVEMENT BEARS HIGH COSTS IN COMPUTATION AND VISUALIZATION, OPENING A NICHE TO OPTIMIZE THE FRAMEWORK TOWARDS SUPER-RESOLUTION AT REASONABLE COSTS. IT ALIGNS WITH NSF?S MISSION TO PROMOTE THE PROCESS OF COMPUTER SCIENCE AND TO ADVANCE THE NATIONAL HEALTH. THIS PROJECT IS TO INVESTIGATE NOVEL ALGORITHM DEVELOPMENT TO ADAPTIVELY IMPROVE DIGITAL RESOLUTION AND MINIMIZE THE COST OF COMPUTATION IN SUPER-RESOLUTION PROCESS. TECHNICALLY, THIS METHOD COMBINES THE EFFORT OF OBJECT DETECTION AND SUPER-RESOLUTION TO BRING A GENERALIZABLE TOOL TO POTENTIALLY BENEFIT MULTIPLE BIOMEDICAL IMAGING MODALITIES, SUCH AS OPTICAL COHERENCE TOMOGRAPHY (OCT), HISTOLOGICAL MICROSCOPY, CONFOCAL IMAGES, MRI, ULTRASOUND, ETC. THE EDUCATIONAL EMPHASIZES ACTIVITIES TO BROADEN THE PARTICIPATION OF UNDERREPRESENTED GROUPS IN BIOMEDICAL PURSUITS. THIS PROJECT AIMS TO DEVELOP INTELLIGENT OBJECT-ADAPTIVE SUPER-RESOLUTION ALGORITHMS TO IMPROVE RESOLUTIONS OF BIOMEDICAL IMAGES IN A ROBUST, EFFICIENT, AND GENERALIZABLE MANNER. THIS PROJECT WILL DEVELOP ROBUST OBJECT DETECTION NEURAL NETWORK TO IDENTIFY REGIONS TO BE SUPER-RESOLVED. A SCALE FACTOR WILL BE DETERMINED FOR ADAPTIVE SUPER-RESOLUTION. THIS PROJECT WILL INVESTIGATE ON COMPUTATIONALLY EFFICIENT ALGORITHMS TO SUPER-RESOLVE BIOMEDICAL IMAGES TO MULTIPLE SCALE FACTORS DURING A COMPLEX-VALUED IMAGE RECONSTRUCTION PROCESS. THIS PROJECT WILL ALSO DEVELOP A TRANSFERRABLE FRAMEWORK SUCH THAT THE SUPER-RESOLUTION TECHNOLOGY DEVELOPED IN ONE IMAGE MODALITY CAN BE ADAPTED INTO THE SUPER-RESOLUTION TECHNOLOGY DEVELOPED BY A DIFFERENT IMAGING MODALITY. THE APPROACHES WILL BE VALIDATED USING OCT DATA AND THE DOMAIN ADAPTION WILL BE VALIDATED BY TRANSFERRING FROM OCT DOMAIN TO HISTOPATHOLOGICAL DOMAIN. THE RESEARCH OUTCOME WILL ALSO RESULT IN ARTIFICIAL INTELLIGENCE-BASED EDUCATIONAL MATERIALS AND SOFTWARE TO REDUCE THE NEED OF BIOMEDICAL FACILITIES THAT ARE CONVENTIONALLY REQUIRED BUT NOT COST-EFFECTIVE TO UNDERREPRESENTED GROUPS. IN ADDITION, THIS PROJECT INCLUDES OUTREACH ACTIVITIES TO PROMOTE BIOMEDICAL PARTICIPATION IN REGIONS WITH LIMITED ACCESS TO BIOMEDICAL RESOURCES AND A NEW MODEL TO MENTOR A DIVERSE AND INCLUSIVE TEAM AND CREATE MOTIVATION TO THE NEXT GENERATION OF RESEARCHERS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

CAREER: AN AI EMPOWERED ARCHITECTURE-CENTRIC FRAMEWORK FOR SYSTEMATIC SOFTWARE-PERFORMANCE OPTIMIZATION

WE PROPOSE TO USE AND FURTHER DEVELOP ADVANCED RADIATIVE TRANSFER (RT) TOOLS FOR POLARIZED RADIATION IN COUPLED ATMOSPHERE-SURFACE SYSTEMS TO SYSTEMA

CAREER: NON-COMMUTATIVE CRYPTOGRAPHY FROM HARD LEARNING PROBLEMS: THEORY AND PRACTICE

FUNDING OPPORTUNITY NUMBER DARPA RA 21 03THE DEFENSE ADVANCED RESEARCH PROJECTS AGENCY DARPA YOUNG FACULTY AWARD YFA PROGRAM AIMS TO IDENTIFY AND ENGAGE RISING STARS IN JUNIOR RESEARCH POSITIONS IN ACADEMIA AND EQUIVALENT POSITIONS AT NON PROFIT RESEARCH INSTITUTIONS, PARTICULARLY THOSE WITHOUT PRIOR DARPA FUNDING, TO EXPOSE THEM TO DEPARTMENT OF DEFENSE DOD NEEDS AND DARPA S MISSION TO CREATE AND PREVENT TECHNOLOGICAL SURPRISE YFA WILL PROVIDE HIGH IMPACT FUNDING TO ELITE RESEARCHERS EARLY IN THEIR CAREERS TO DEVELOP INNOVATIVE NEW RESEARCH THAT ENABLES TRANSFORMATIVE DOD CAPABILITIES ULTIMATELY, YFA IS DEVELOPING THE NEXT GENERATIONS OF RESEARCHERS FOCUSED ON NATIONAL SECURITY ISSUES

TRANSCRIPTIONAL REGULATION OF ONCOGENIC CELLULAR PLASTICITY IN THE INTESTINAL EPITHELIUM

US IGNITE: FOCUS AREA 1: AN INTEGRATED RECONFIGURABLE CONTROL AND SELF-ORGANIZING COMMUNICATION FRAMEWORK FOR ADVANCED COMMUNITY RESILIENCE MICROGRIDS

NETSE:SMALL: HUMAN BEHAVIOR INSPIRED COGNITIVE RADIO NETWORK DESIGN

CAREER: VERIFIABLE OUTSOURCING OF DATA MINING COMPUTATIONS

A NOVEL CLASS OF ANTAGONISTS FOR ROBUST INHIBITION OF MUTANT ESTROGEN RECEPTOR ACTION IN EDOCRINE RESISTANT METASTATIC BREAST CANCER

SCALING AND STRUCTURE IN TRANSITIONAL AND TURBULENT HYPERVELOCITY FLOWS

ADAPTING STATIC AND DYNAMIC PROGRAM ANALYSIS TO EFFECTIVELY HARDEN DEBLOATED SOFTWARE

COLLABORATIVE RESEARCH: CHEMICAL ECOLOGY OF HOST SPECIALIZATION IN PHORID PARASITOIDS OF ANTS: AN EXPERIMENTAL ANALYSIS

CAREER: RANDOMIZED MULTISCALE METHODS FOR HETEROGENEOUS NONLINEAR PARTIAL DIFFERENTIAL EQUATIONS

EXECUTE A BALANCED SCIENCE PROGRAM BASED ON DISCIPLINE-SPECIFIC GUIDANCE FROM THE NATIONAL ACADEMIES OF SCIENCES ENGINEERING AND MEDICINE ADMINISTRATION PRIORITIES AND DIRECTION FROM CONGRESS. PARTICIPATE AS A KEY PARTNER AND ENABLER IN THE AGENCY S EXPLORATION INITIATIVE FOCUSING ON SCIENTIFIC RESEARCH OF ON AND FROM THE MOON LUNAR ORBIT MARS AND BEYOND. ADVANCE DISCOVERY IN EMERGING FIELDS BY IDENTIFYING AND EXPLOITING CROSS-DISCIPLINARY OPPORTUNITIES BETWEEN TRADITIONAL SCIENCE DISCIPLINES DEVELOP A DIRECTORATE-WIDE TARGET-USER FOCUSED APPROACH TO APPLIED PROGRAMS INCLUDING EARTH SCIENCE APPLICATIONS SPACE WEATHER PLANETARY DEFENSE AND SPACE SITUATIONAL AWARENESS.

MODULAR APPROACHES TO UNUSUAL BORYLATED HETEROCYCLES USING NOVEL ACYLBORONS AND ALPHA-HYDROXY BORONS AS ENABLING TOOLS

CAREER: MULTI-FUNCTIONAL PARTICLE ASSEMBLIES IN POLYMER NANOCOMPOSITES

CAREER: MULTITRACK READ CHANNEL DESIGNS FOR MODERN TWO-DIMENSIONAL MAGNETIC RECORDING -THIS PROJECT DEVELOPS EFFICIENT NOISE PREDICTION, SYNCHRONIZATION, AND SYMBOL DETECTION ALGORITHMS THAT SUPPORT MODERN AND FUTURE GENERATIONS OF ULTRA-HIGH DENSITY TWO-DIMENSIONAL MAGNETIC RECORDING. TWO-DIMENSIONAL MAGNETIC RECORDING IS A NOVEL TECHNOLOGY IN HARD DISK DRIVES THAT ALLOWS A DRASTIC INCREASE IN THE DATA DENSITY TO UP TO 10 TERABITS PER SQUARE INCH, ON ALREADY-EXISTING HEAD AND MEDIA DESIGNS. THIS IS ACHIEVED THROUGH SHINGLED WRITING, WHERE THE ADJACENT DATA TRACKS ARE WRITTEN WITH PARTIAL OVERLAP ON TOP OF EACH OTHER, LIKE ROOF SHINGLES, IN ORDER TO SQUEEZE MANY MORE TRACKS ON THE DISK. POWERFUL SIGNAL PROCESSING ALGORITHMS ENABLE EFFICIENT DATA RECOVERY FROM HIGHLY INTERFERENCE-LADEN AND NOISY READBACK SIGNALS. THIS PROJECT INVESTIGATES POWERFUL SIGNAL PROCESSING ALGORITHMS, FROM PURELY COMMUNICATION-THEORETIC TO MACHINE LEARNING MODELS, AND THEIR COMBINATIONS, FOR DATA RECOVERY IN SUCH CHANNELS. THE RESULTS OF THIS PROJECT ARE EXPECTED TO INCREASE THE DATA DENSITY OF TWO-DIMENSIONAL MAGNETIC RECORDING WELL BEYOND THE CURRENT STATE-OF-THE-ART. THE PROJECT INTEGRATES AN EDUCATIONAL COMPONENT IN SIGNAL PROCESSING AND COMMUNICATION THEORY IN THE FORM OF 1) GRADUATE STUDENT TRAINING, 2) RESEARCH-ORIENTED UNDERGRADUATE STUDENT EDUCATION, AND 3) COLLABORATIVE PARTICIPATION WITH INDUSTRIAL RESEARCH. THE NOVEL ELEMENTS OF THIS PROJECT ARE THAT: 1) IT ADOPTS A MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO) MODEL IN ACCORDANCE WITH THE INDUSTRY EXPECTATION FOR LOW-LATENCY IMPLEMENTATION; 2) IT DEVELOPS MULTITRACK DETECTION STRATEGIES AS OPPOSED TO THE CURRENT INDUSTRY STANDARD OF SINGLE-TRACK DETECTION, IN ORDER TO REACH HIGHER AREAL DENSITIES AS WELL AS THROUGHPUT; AND 3) IN ADDITION TO CONSIDERING ALL THE CHANNEL IMPEDIMENTS THAT ARE OFTEN CONSIDERED SEPARATELY IN EARLIER WORKS, THIS PROJECT ALSO ADDRESSES THE PROBLEM OF TIMING ASYNCHRONY BETWEEN THE ADJACENT TRACKS AND THE ANALOG-TO-DIGITAL CONVERTER SAMPLING RATE. TO ACHIEVE THE ABOVE GOALS, FOUR RESEARCH THRUSTS WILL BE PURSUED. IN THE FIRST THRUST, REDUCED-STATE REDESIGNS OF THE TRELLIS-BASED MULTITRACK SYMBOL DETECTORS WILL BE INVESTIGATED. THE SECOND THRUST DEVELOPS MEDIA NOISE MITIGATION TECHNIQUES FOR ASYNCHRONOUS MULTITRACK DETECTION. HERE, BOTH THE MIMO EXTENSION OF THE PATTERN-DEPENDENT NOISE PREDICTION ALGORITHM AND NEURAL NETWORK NOISE PREDICTOR MODELS WILL BE STUDIED. IN THE THIRD THRUST, DEEP NEURAL NETWORK SYMBOL DETECTORS WILL BE DEVELOPED, BOTH AS A STAND-ALONE JOINT SYMBOL DETECTOR AND SYNCHRONIZER, AS WELL AS A JOINT SYMBOL DETECTOR AND SYNCHRONIZER COUPLED WITH A LOW-DENSITY PARITY CHECK DECODER FOLLOWING THE TURBO DETECTION MECHANISM. THE FOURTH THRUST DEVELOPS NOVEL READ CHANNELS BUILT ENTIRELY OF NEURAL NETWORKS, BOTH AS A SEPARATE NETWORK EQUALIZER FOLLOWED BY A NETWORK SYMBOL DETECTOR, AND AS A HOLISTIC DEEP NEURAL NETWORK READ CHANNEL. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.

HIGHER EFFICIENCY ORGANIC SOLAR CELLS VIA CONTINUOUS PROCESSING UNDER OPTIMUM SHEARING CONDITIONS

SATC: CORE: SMALL: RELATIONAL VERIFICATION FOR INFORMATION ASSURANCE AND PRIVACY

MEMBRANE-ACTING PEPTIDES

DEVELOPMENT OF RECRYSTALLIZATION METHODOLOGIES FOR HNFX TO OBTAIN HIGH DENSITY POLYMORPH

TC: SMALL: DENIAL-OF-SERVICE ATTACKS AND COUNTER MEASURES IN DYNAMIC SEPCTRUM ACCESS NETWORKS

MULTIMEDIA IMMERSION INSPIRES STEM LEARNING

PROJECT TITLE ASSESSING PLUVIAL COASTAL FLOOD RISK AND POTENTIAL CLIMATE INEQUITIES IN NEW YORK CITYPROJECT PERIOD 9 1 22 8 31 23RECENT FLOOD DISASTERS ARISING FROM COASTAL STORMS E G , HARVEY AND IDA HAVE DEMONSTRATED THE CRITICAL IMPORTANCE OF INCORPORATING RAINFALL INTO ASSESSMENTS OF COASTAL FLOOD RISK HOWEVER, STUDIES OF PRESENT AND FUTURE COASTAL FLOOD RISK AND ADAPTATION NEARLY ALWAYS NEGLECT RAINFALL AND THUS HAVE BIASES THAT MAY LEAD TO SUBOPTIMAL GOVERNMENT PLANNING DECISIONS CLIMATE CHANGE IS LEADING TO BOTH INCREASING RAINFALL INTENSITY AND RISING COASTAL FLOODS, WORSENING THESE BIASES AND THE DANGERS THEY REPRESENT VULNERABILITY TO FLOODING, WHICH INCLUDES EXPOSURE, DEFINED AS LIVING IN AN AREA THAT MAY FLOOD, SUSCEPTIBILITY TO SUFFER DAMAGE IF FLOODING OCCURS, AND CAPACITY TO RECOVER, DIFFERS ACROSS COMMUNITIES WITH DIFFERENT SOCIO ECONOMIC CHARACTERISTICS PRIOR RESEARCH CHARACTERIZES HOW VULNERABILITY TO FLOODING DRIVEN BY COASTAL STORMS DIFFERS IN THE POPULATION IN THE URBAN NEIGHBORHOODS OF NEW YORK CITY NYC VULNERABILITY TO NUISANCE, TIDAL, AND PLUVIAL FLOODING IS MUCH LESS WELL DOCUMENTED AND UNDERSTOOD IMPACTS OF AND THEREFORE VULNERABILITY TO NUISANCE AND PLUVIAL FLOODING CAN DIFFER FROM COASTAL STORM FLOODING FOR EXAMPLE, ANECDOTAL EVIDENCE SUGGESTS THAT THE DANGER POSED TO RESIDENTS OF BASEMENT APARTMENTS CAN BE PARTICULARLY ACUTE IN THE CASE OF FLASH FLOODING DRIVEN BY EXTREME RAINFALL RESIDENTS OF BASEMENT APARTMENTS ARE OFTEN DISADVANTAGED IN MANY WAYS, BEING LOW INCOME, FROM MINORITY RACIAL GROUPS, OR RECENT IMMIGRANTS IN THIS STUDY, WE WILL COMBINE NOVEL MODELING AND ASSESSMENT OF COMPOUND COASTAL PLUVIAL FLOOD HAZARD WITH ANALYSES OF FLOOD VULNERABILITY IN POPULATIONS WITH DIFFERENT CHARACTERISTICS AROUND JAMAICA BAY, NYC INNOVATIVE HYDRODYNAMIC AND MACHINE LEARNING ML MODELS WILL BE DEVELOPED AND APPLIED FOR INTEGRATED FLOOD MODELING FOR JAMAICA BAY, BOTH VALIDATED USING EXISTING CITIZEN SCIENCE OBSERVATIONS AND ULTRASONIC SENSOR MEASUREMENTS OF STREET FLOODING WE WILL COLLECT AND ANALYZE SOCIAL DATA THROUGH INTERVIEWS AND HOUSEHOLD SURVEYS TO DOCUMENT IMPACTS OF AND RECOVERY FROM FLOODING IN NEIGHBORHOODS THAT HAVE RECENTLY BEEN IMPACTED BY PLUVIAL AND HIGH TIDE FLOODING AND THAT REPRESENT A BROAD RANGE OF NATURAL AND BUILT ENVIRONMENTAL AND SOCIO ECONOMIC CONDITIONS WE WILL COMBINE INVESTIGATION OF SOCIAL VULNERABILITY TO PLUVIAL AND HIGH TIDE FLOODING WITH EXISTING UNDERSTANDING OF SOCIAL VULNERABILITY TO COASTAL STORM FLOODING IN URBAN NEIGHBORHOODS, TO ASSESS INEQUITIES IN THE BURDEN OF FLOOD RISK AND INFORM POLICIES THAT CAN ADVANCE EQUITABLE ADAPTATION TO FLOOD RISK THE RESEARCH SUPPORTS THE USGS GOALS OF IMPROVING COASTAL AND FLOOD MODELING AND ITS APPLICATION TO REDUCING SOCIETAL RISK AND IMPROVING COASTAL RESILIENCE INTENDED BENEFICIARIES ARE FLOOD AND COASTAL MODELING SCIENTISTS, MUNICIPAL GOVERNMENTS, AND COASTAL RESIDENTS VULNERABLE TO FLOODING, PARTICULARLY RACIAL MINORITY, LOW INCOME AND IMMIGRANT COMMUNITIES RESULTS OF THE STUDY WILL BE MADE AVAILABLE TO THE ACADEMIC COMMUNITY AND PUBLIC THROUGH 1 PEER REVIEWED PUBLICATIONS, 2 CONFERENCE AND SEMINAR PRESENTATIONS, 3 DATASET PUBLICATIONS, 4 MODEL SETUP TOOLS AND A HOW TO REPORT FOR INCORPORATING RAIN INTO THE HYDRODYNAMIC MODEL, AND A 5 POLICY BRIEF THE PROJECT IS DIRECTED BY RESEARCHERS AT THE STEVENS INSTITUTE OF TECHNOLOGY, WHO WILL ALSO SPEARHEAD THE FLOOD MODELING ACTIVITIES, AND AWARD SUBRECIPIENTS AT COLUMBIA UNIVERSITY AND BROOKLYN COLLEGE WILL LEAD THE SOCIAL SCIENCE COMPONENTS OF THE STUDY

SHF: SMALL: ENHANCING JUST-ENOUGH AND MAINTAINABLE MOCKING IN UNIT TESTING IN SOFTWARE ENGINEERING -UNIT TESTING, A FUNDAMENTAL PHASE OF SOFTWARE TESTING, FACES CHALLENGES DUE TO INTERDEPENDENCIES AMONG THE FUNCTION UNITS IN A SYSTEM. IT IS IMPRACTICAL TO TEST A SYSTEM AS COMPLETELY SEPARATE UNITS WITHOUT CONSIDERING THEIR DEPENDENCIES. SOFTWARE ENGINEERS HAVE DEVISED A MECHANISM CALLED MOCKING, WHICH REPLACES THE TEST DEPENDENCIES OF THE FUNCTION UNDER TEST BY CREATING MOCK OBJECTS. VARIOUS DEDICATED MOCKING FRAMEWORKS PROVIDE WELL-CONSTRUCTED APPLICATION PROGRAMMING INTERFACES (APIS) TO SUPPORT THE MOCKING MECHANISM IN PRACTICE. HOWEVER, PRACTITIONERS OFTEN FIND ADOPTING THESE FRAMEWORKS CHALLENGING. THIS AWARD TARGETS THE FOLLOWING CHALLENGES: (1) THERE IS A KNOWLEDGE GAP REGARDING WHAT TO MOCK AND WHAT NOT TO MOCK IN UNIT TESTING; (2) DESPITE MOCKING BEING USED IN PRACTICE FOR DECADES, THERE IS LITTLE UNDERSTANDING OF GOOD PRACTICES TO FOLLOW AND BAD PRACTICES TO AVOID IN MOCKING; AND (3) MOCKING AND ITS MAINTENANCE REQUIRE A HIGH LEVEL OF EXPERTISE AND MANUAL EFFORT, WHICH RAISES THE BAR FOR USING MOCKING FRAMEWORKS. THIS AWARD AIMS TO CONTRIBUTE VALUABLE EMPIRICAL KNOWLEDGE AND DEVELOP A FRAMEWORK WITH AUTOMATED SUPPORT FOR ACHIEVING JUST ENOUGH AND MAINTAINABLE MOCKING IN UNIT TESTING. THE PROPOSED RESEARCH WILL FACILITATE CREATING MORE INDEPENDENT, EFFICIENT, EASIER TO DEBUG, AND MORE MAINTAINABLE UNIT TEST CASES. THE RESEARCH TEAM ALSO PLANS TO DEVELOP AN ADVANCED COURSE ABOUT MOCKING FOR UNDERGRADUATE SENIORS AND GRADUATE STUDENTS IN SOFTWARE ENGINEERING, COMPUTER SCIENCE, OR RELATED FIELDS. ADDITIONALLY, THE TEAM PLANS TO PREPARE PUBLICLY AVAILABLE ONLINE TUTORIALS AND TRAINING SESSIONS TO BENEFIT PRACTITIONERS INTERESTED IN BUILDING SKILLS IN MOCKING. THE RESEARCH TEAM WILL FOCUS ON THREE RESEARCH DIRECTIONS IN THIS PROJECT. FIRST, CONDUCTING AN IN-DEPTH EMPIRICAL STUDY OF MOCKING PRACTICES. THE OBJECTIVE IS TO PROVIDE EXTENSIVE EMPIRICAL KNOWLEDGE ABOUT WHAT TO MOCK AND WHAT NOT TO MOCK, INCLUDING GOOD DESIGN PATTERNS TO FOLLOW AND BAD ANTI-PATTERNS TO AVOID IN MOCKING. SUCH EMPIRICAL KNOWLEDGE BENEFITS PRACTITIONERS BY OFFERING GUIDANCE AND REFERENCES FOR EFFECTIVELY USING MOCKING FRAMEWORK APIS. SECOND, DEVELOPING A FRAMEWORK TO ENABLE JUST ENOUGH AND MAINTAINABLE MOCKING. THIS FRAMEWORK CONSISTS OF TWO KEY COMPONENTS: (1) AUTOMATED DETECTION OF DEPENDENCIES TO MOCK TO ACHIEVE JUST ENOUGH MOCKING; AND (2) AUTOMATED DETECTION AND REFACTORING OF MOCKING ANTI-PATTERNS TO ENSURE GOOD DESIGN AND MAINTAINABILITY OF MOCK OBJECTS IN TEST CASES. FINALLY, DEVELOPING CURRICULUM AND TRAINING MATERIALS ABOUT MOCKING. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

LASER BEAM (LIDAR) PROPAGATION IN THE ATMOSPHERE-OCEAN SYSTEM IN SUPPORT OF ACTIVE REMOTE SENSING FROM SPACE

HIERARCHICAL SELF ASSEMBLY OF MULTIFUNCTIONAL BIOINTERACTIVE SURFACES

REMOTE DETECTION OF CHEM/BIO HAZARDS VIA COHERENT ANTI-STOKES RAMAN SPECTROSCOPY

EPILEPTIC ELECTROPHYSIOLOGICAL BRAIN NETWORKS MODELING WITH PARTIALLY OBSERVABLE BRAIN REGIONS - PROJECT SUMMARY EPILEPSY IS ONE OF THE MOST COMMON NEUROLOGICAL DISORDERS, AFFECTING 50 MILLION PEOPLE WORLDWIDE OF ALL AGES. SEIZURES IN UP TO ONE THIRD OF EPILEPSY PATIENTS ARE DRUG REFRACTORY, WHERE SURGERY OFFERS A NECESSARY MEANS TO RESECT EPILEPTOGENIC REGIONS (EZS). HOWEVER, THE OUTCOMES OF EPILEPSY SURGERY MAY OFTEN BE SUBOPTIMAL AS ON AVERAGE APPROXIMATELY 50% OF PATIENTS ARE STILL NOT SEIZURE FREE AFTER SURGERY, MAINLY DUE TO THE EZS CANNOT BE ACCURATELY LOCALIZED. TRADITIONALLY, THE EZ IS CLINICALLY DETERMINED BY USING ICTAL INTRACRANIAL ELECTROENCEPHALOGRAPHY (IEEG) RECORDINGS, WHICH ARE INVASIVE, AND CAN ONLY COVER PARTIAL BRAIN REGIONS, AND WITH A WAITING PERIOD OF DAYS TO WEEKS FOR SEIZURE TO OCCUR. IN MORE RECENT YEARS, IT HAS BEEN RECOGNIZED BY RESEARCHERS THAT SEIZURES ARISE FROM A COORDINATED ACTIVITY ACROSS LARGE SCALE EPILEPTIC NETWORKS, THUS CHARACTERIZING THE CONNECTIONS AMONG THE INVOLVED EPILEPSY REGIONS IS PROFOUND TO UNDERSTAND THE TRANSMISSION PATHWAYS OF EPILEPTIC BRAIN NETWORK AND EPILEPTOGENIC FOCI. HOWEVER, THE CURRENT ESI FRAMEWORKS ARE INSUFFICIENT TO TACKLE THE CHANGES. FIRSTLY, IEEG ELECTRODES CAN ONLY RECORD FROM PARTIAL BRAIN REGIONS, AND IT IS INFEASIBLE TO RECORD THE WHOLE BRAIN INTRACRANIAL DATA DUE TO ITS INVASIVE NATURE, AND SECONDLY, THE EXISTING ESI FRAMEWORKS SUFFER FROM VERY LOW ACCURACY WHEN IT COMES TO THE ESTIMATION OF WHOLE BRAIN ELECTROPHYSIOLOGICAL NETWORKS. IN THIS PROJECT, WE AIM TO DEVELOP A UNIFIED PARADIGM USING A SIMULTANEOUS MULTIMODAL MEASUREMENT OF SCALP EEG AND IEEG SIGNALS TO ESTIMATE THE ELECTROPHYSIOLOGICAL NETWORKS OF THE WHOLE BRAIN, THUS ENABLING THE CHARACTERIZATION OF SEIZURE ONSET ZONES (SOZ) AND ITS KEY TRANSMISSION PATHWAYS FROM THE LEVEL OF WHOLE BRAIN SOURCE SPACE. WE AIM TO BRIDGE THE GAP BETWEEN THE LESS ACCURATE WHOLE BRAIN NETWORK RECONSTRUCTION USING SOURCE LOCALIZATION WITH SCALP EEG AND THE MORE ACCURATE BUT REGIONAL BRAIN NETWORKS CONSTRUCTED FROM IEEG BY USING A PRINCIPLED MACHINE LEARNING FRAMEWORK AND LETTING THE PARTIALLY OBSERVABLE BRAIN SIGNALS TO “SEMI- SUPERVISE” THE WHOLE BRAIN NETWORKS ESTIMATION PROCESS. WE TERM THIS NEW PARADIGM OF SOURCE IMAGING AS “ELECTROPHYSIOLOGICAL NETWORKS IMAGING” (ENI) IN CONTRAST TO THE TRADITIONAL ELECTROPHYSIOLOGICAL SOURCE IMAGING (ESI). THE PROPOSED FRAMEWORK WILL ENABLE DELINEATION OF BRAIN REGIONS INVOLVED IN SEIZURE GENERATION AND PROPAGATION AT THE WHOLE BRAIN SCALE AND IMPROVE UNDERSTANDING OF DIFFERENT EPILEPSY BIOMARKERS FROM A NETWORK PERSPECTIVE AND THEIR VALUES IN THE PRE-SURGERY DECISION MAKING AND SURGICAL OUTCOMES.

THE PATIENT JOURNEY FOR CHILDREN WITH MEDICAL COMPLEXITY DURING PANDEMIC ERA ANDITS IMPLICATIONS. - PROJECT SUMMARY/ABSTRACT CMC ARE A SMALL PROPORTION OF CHILDREN AND YOUTH WITH SPECIAL HEALTH CARE NEEDS THAT ACCOUNT FOR LESS THAN 1-5% OF ALL CHILDREN BUT CONSUME OVER ONE THIRD OF HEALTH CARE RESOURCES. THEY ARE AT INCREASED RISK OF MULTIPLE AND PROLONGED HOSPITALIZATIONS, INEFFICIENT USE OF HEALTHCARE RESOURCES, FREQUENT MEDICAL ERRORS, POOR HEALTH OUTCOMES, SIGNIFICANT UNMET NEEDS FOR HEALTH SERVICES, AND STRESS ON FAMILY CAREGIVERS. THIS COMPLEXITY AND RELATED PROBLEMS HAVE BEEN AND CONTINUE TO BE EVEN FURTHER EXACERBATED BY THE COVID PANDEMIC. THE RISE OF THE NOVEL CORONAVIRUS (COVID-19) CHANGED DYNAMICS AND CONTRIBUTED TO A PARADIGM SHIFT IN THE OVERALL HEALTH CARE PRACTICE WHICH WILL PROBABLY HAVE LONG LASTING IMPACT AND MAY BE THE “NEW NORMAL”. IN THIS EXPLORATORY STUDY, OUR OVERARCHING GOAL IS TO UNDERSTAND HOW COVID-19 PANDEMIC IMPACTED CMC CARE PATIENT JOURNEY. WE WILL CAPTURE THE EXPERIENCE OF MULTI STAKEHOLDERS ASSOCIATED WITH CMC CARE INCLUDING HOSPITALISTS, PEDIATRICS OUTPATIENT PROVIDERS, HOME NURSES, CMC CAREGIVERS AND PATIENTS. THE FINDINGS WILL HELP THE ONGOING EFFORTS TO REDESIGN AND IMPROVE CMC CARE ESPECIALLY IN THE LIGHT OF NEW CHALLENGES INTRODUCED BY THE COVID-19 PANDEMIC. THE AIMS OF THE PROJECT ARE TO: 1) PERFORM A MULTI-STAKEHOLDER 360-DEGREE ANALYSIS OF THE COVID EXPERIENCE FOR CMC PATIENTS ACROSS DIFFERENT SETTINGS IN THEIR PATIENT JOURNEY USING QUALITATIVE AND HUMAN FACTORS TECHNIQUES. 2) QUANTITATIVELY EVALUATE USEFULNESS AND EXPERIENCE OF TELEHEALTH USE IN CMC CARE, AND 3) EVALUATE THE IMPACT OF PANDEMIC ON HEALTH OUTCOME/UTILIZATION CMC USING RETROSPECTIVE CHART REVIEW. THE RESEARCH TEAM IS WELL POSITIONED TO ADDRESS THE PROPOSED AIMS FOR THE CMC POPULATION AND THUS GUIDE IDENTIFICATION OF POTENTIAL INTERVENTIONS TO IMPROVE CMC CARE. THIS INNOVATIVE, IN-DEPTH, AND RICH ANALYSIS OF THE CMC CARE PATIENT JOURNEY DURING THE PANDEMIC USING NOVEL HUMAN FACTORS METHODOLOGIES WILL PROVIDE HIGHLY VALUABLE INFORMATION, NOT ONLY FOR CMC, BUT ALSO FOR OTHER SIMILARLY COMPLEX CARE SETTINGS AND PATIENT POPULATIONS.

RI: SMALL: LEARNING TO ELIMINATE HEURISTICS IN STEREO VISION

COLLABORATIVE RESEARCH: GCR: CONVERGENT ANTHROPOCENE SYSTEMS (ANTHEMS) - A SYSTEM-OF-SYSTEMS PARADIGM -CONVERGENT ANTHROPOCENE SYSTEMS (ANTHEMS) WILL DEVELOP A SYSTEMS-OF-SYSTEMS (SOS) CONVERGENCE PARADIGM THAT INCLUDES AN SOS COMPUTATIONAL FRAMEWORK, AN SOS DECISION-SUPPORT SYSTEM, AND AN SOS PEDAGOGY, ENABLING DIVERSE STAKEHOLDERS TO INTEGRATIVELY ADDRESS THE SUITE OF SOCIETAL CHALLENGES OF THE ANTHROPOCENE (E.G., CLIMATE CHANGE AND IMPACTS, RENEWABLE ENERGY, ADAPTIVE INFRASTRUCTURE, DISASTERS, PANDEMICS, FOOD INSECURITY, BIODIVERSITY LOSS) AND CATALYZING A MAJOR TRANSFORMATION IN NATIONAL AND GLOBAL APPROACHES TO THE SCIENCE AND ENGINEERING RELEVANT TO THESE CHALLENGES. THIS PARADIGM WILL BE DEVELOPED, IMPLEMENTED, AND VALIDATED IN CLOSE COLLABORATION WITH THE CHESAPEAKE BAY PROGRAM (CBP), FOCUSING ON THE CHESAPEAKE BAY WATERSHED (CBW) REGION. THE CBW IS HOME TO OVER 17 MILLION PEOPLE AND THE CBP STAKEHOLDER COMMUNITY WILL BENEFIT FROM INTEGRATED MODELING TOOLS TO EXAMINE SYNERGIES (E.G., NUTRIENT REDUCTION AND FLOOD RISK MITIGATION) AND TRADEOFFS (E.G., NUTRIENT REDUCTION AND FISH PRODUCTIVITY) ACROSS MULTIPLE SYSTEMS. TOGETHER, THE CBW AND THE CBP PROVIDE A REAL-WORLD TESTBED FOR THE SOS CONVERGENCE PARADIGM, ENABLING THE PROJECT TO BRING TOGETHER INTELLECTUALLY-DIVERSE RESEARCHERS TO ADDRESS MULTIPLE INTERDEPENDENT SOCIETAL CHALLENGES (EUTROPHICATION, FOOD AND AGRICULTURE, AND ECONOMIC GROWTH) BY INTEGRATING ACROSS MULTIPLE SYSTEMS (WATERSHED, LAND USE, ECONOMIC, ESTUARY AND GOVERNANCE) AND MULTIPLE DISCIPLINES (ENVIRONMENTAL ENGINEERING, CITY AND REGIONAL PLANNING, PLANNING POLICY AND DESIGN, CIVIL ENGINEERING, GEOGRAPHY, INDUSTRIAL AND SYSTEMS ENGINEERING, POLITICAL ECONOMY AND PUBLIC POLICY). ANTHEMS WILL DEVELOP, IMPLEMENT, AND VALIDATE THE SOS CONVERGENCE PARADIGM FOR A SET OF INTERDEPENDENT SOCIETAL CHALLENGES IN THE CBW REGION. IN PHASE 1, ANTHEMS WILL INTEGRATE REGIONAL MODELS OF LAND USE, WATERSHED, AND ECONOMICS USING THE SOS COMPUTATIONAL FRAMEWORK, ENGAGE WITH STAKEHOLDERS TO EVALUATE REGIONAL SCENARIOS, AND BEGIN THE DEVELOPMENT AND EVALUATION OF THE SOS DECISION-SUPPORT SYSTEM AND SOS PEDAGOGY. PHASE 2 WILL EXTEND THE SOS COMPUTATIONAL FRAMEWORK BY INCLUDING ESTUARY AND GOVERNANCE MODELS, WHILE ZOOMING IN TO BALTIMORE AT THE URBAN SCALE. ONE OUTCOME OF THIS PROJECT WILL BE THE CAPABILITY TO SCALE UP THE SOS PARADIGM TO A LARGER FAMILY OF SOCIETAL CHALLENGES IN THE FUTURE, GENERALIZING THE APPROACH TO OTHER REGIONS AND THEIR ASSOCIATED URBAN AREAS. THE SOS COMPUTATIONAL FRAMEWORK ADVANCES THE EXISTING SYSTEMS ENGINEERING LITERATURE, ADDRESSING ANTHROPOCENE CHALLENGES. THE SOS DECISION-SUPPORT SYSTEM PROVIDES A STRUCTURED APPROACH FOR TRANSLATING SOS SCENARIOS AND COMPUTATIONAL RESULTS INTO REAL-WORLD INSIGHTS FOR A DIVERSE SET OF STAKEHOLDERS. THE SOS PEDAGOGY WILL BEGIN TO TRAIN A NEW GENERATION OF ANTHROPOCENE SYSTEM INTEGRATORS (INCLUDING STUDENTS, ACADEMICS, PRACTITIONERS AND STAKEHOLDERS) TO CONCEPTUALIZE ANTHROPOCENE CHALLENGES HOLISTICALLY, THINK COHERENTLY IN TERMS OF COMMON ONTOLOGICAL CONSTRUCTS, PRODUCE AND SIMULATE SOS COMPUTATIONAL MODELS, FACILITATE DECISION-SUPPORT CONVERSATIONS FILLED WITH COHERENT, DATA-DRIVEN, REAL-WORLD INSIGHTS, AND USE THESE INSIGHTS TO ONCE AGAIN CONCEPTUALIZE SOCIETAL PROBLEMS. THE EFFECTIVENESS OF THE SOS PEDAGOGY WILL BE STUDIED USING THE SCIENCE-OF-TEAM-SCIENCE-BASED ANTECEDENT-PROCESS-OUTPUT EVALUATION MODEL, THEREBY ADVANCING THE STUDY OF CONVERGENCE PROCESSES AND OUTCOMES. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

SNR DBS FOR THE TREATMENT OF GAIT AND POSTURAL DISTURBANCES IN PARKINSON'S DISEASE

PATIENTS PERCEPTIONS OF ELECTRONIC HEALTH RECORD USE DURING INITIAL ONCOLOGY OUTPATIENT CLINIC VISITS

CAREER: FUNDAMENTAL RESEARCH LEVERAGING NANOPARTICLE-INDUCED CRYSTALLIZATION IN SEMICRYSTALLINE POLYMER NANOCOMPOSITES

CAREER: SCALABLE QUANTUM PHOTONIC DEVICES BASED ON VERTICAL QUANTUM DOTS AND PHOTONIC CRYSTALS

IMPACT OF PERMEABILITY HETEROGENEITY ON SOLUTE DISPERSION IN UNSATURATED POROUS MEDIA -SOLUTE DISPERSION IN UNSATURATED POROUS MEDIA HAS CRITICAL IMPLICATIONS FOR VARIOUS NATURAL AND ENGINEERED SYSTEMS, SUCH AS NUTRIENT AND CONTAMINANT TRANSPORT IN THE VADOSE ZONE, THE UNSATURATED REGION BETWEEN THE GROUND SURFACE AND THE WATER TABLE. HOWEVER, RELATIVELY FEW STUDIES HAVE BEEN CONDUCTED ON SOLUTE DISPERSION IN UNSATURATED POROUS MEDIA COMPARED TO IN SATURATED POROUS MEDIA. THIS IS PARTIALLY DUE TO THE CHALLENGES IN STUDYING MULTIPHASE FLOWS (I.E., CO-FLOW OF IMMISCIBLE FLUIDS) IN POROUS MEDIA. THE PERMEABILITY OF A POROUS MEDIUM DESCRIBES THE MEDIUM?S CAPABILITY TO ALLOW A FLUID TO FLOW THROUGH IT. THE PERMEABILITY OF NATURAL GEOLOGICAL FORMATIONS IS USUALLY COMPLEX, WHICH DICTATES THE SOLUTE TRANSPORT MECHANISMS IN UNSATURATED FLOWS. EXPERIMENTAL DATA CONCERNING THE ROLE OF COMPLEX PERMEABILITY ON SOLUTE DISPERSION IN UNSATURATED FLOWS ARE EXTREMELY RARE DUE TO THE CHALLENGES ENCOUNTERED BY CONVENTIONAL EXPERIMENTAL METHODS IN CONSTRUCTING A WELL-CONTROLLED PERMEABILITY FIELD IN THE LABORATORY. THE OBJECTIVE OF THE RESEARCH IS TO USE PORE-SCALE NUMERICAL SIMULATION, MICROFLUIDICS, AND THREE-DIMENSIONAL (3D) PRINTING TECHNOLOGIES TO OVERCOME THE CHALLENGES ENCOUNTERED BY CONVENTIONAL EXPERIMENTAL METHODS IN ORDER TO ADVANCE THE UNDERSTANDING OF THE IMPACT OF COMPLEX PERMEABILITY ON SOLUTE DISPERSION IN UNSATURATED POROUS MEDIA. THE EDUCATIONAL OBJECTIVE IS TO INCREASE PUBLIC SCIENTIFIC LITERACY, ENGAGE WOMEN AND MINORITY STUDENTS IN STEM, ENRICH UNDERGRADUATE AND GRADUATE CURRICULA, AND DEVELOP PARTNERSHIPS WITH THE INDUSTRY AND SMALL BUSINESSES. A FUNDAMENTAL KNOWLEDGE GAP EXISTS IN HOW THE DYNAMIC INTERACTION BETWEEN FLUID CO-FLOW AND COMPLEX PERMEABILITY REGULATES SOLUTE DISPERSION IN UNSATURATED FLOWS. THE PROJECT AIMS TO CLOSE THE KNOWLEDGE GAP USING PORE-SCALE NUMERICAL SIMULATION AND STATE-OF-THE-ART 3D PRINTING. THE RESEARCH TASKS ARE: 1) DEVELOP A PORE-SCALE NUMERICAL MODEL TO DIRECTLY SIMULATE TWO-PHASE FLOW AND SOLUTE DISPERSION IN POROUS MEDIA TO UNRAVEL THE IMPACT OF WATER SATURATION, PECLET NUMBER, AND CAPILLARY NUMBER ON THE DISPERSIVITY AND DEVELOP AN EMPIRICAL MODEL FOR DISPERSIVITY PREDICTIONS, 2) DEVELOP AN ADVANCED OBSERVATION METHOD FOR IN SITU SOLUTE CONCENTRATION MEASUREMENTS AND CONDUCT TWO-FLUID CO-INJECTION AND SOLUTE DISPERSION EXPERIMENTS IN A MICROFLUIDIC DEVICE TO VALIDATE THE PORE-SCALE SIMULATION RESULTS, AND 3) USE 3D PRINTING TO CONSTRUCT A KNOWN AND WELL-CONTROLLED HETEROGENEOUS PERMEABILITY FIELD AT THE CONTINUUM (METER) SCALE TO STUDY ITS ROLE ON SOLUTE DISPERSION IN UNSATURATED FLOWS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

PASSIVE SOURCE QUANTUM SUPERRESOLUTION ASSISTED BY PHYSICS-INFORMED ROBUST DEEP LEARNING -RESOLUTION IS KEY TO SEEING FINE DETAILS IN IMAGING AND SENSING?WHETHER IT?S IN BIOMEDICAL IMAGING, OBSERVING DISTANT STARS, QUANTUM MEASUREMENTS, OR EVERYDAY OPTICAL SYSTEMS. BUT ALL OPTICAL SYSTEMS FACE A CRUCIAL BARRIER KNOWN AS THE DIFFRACTION LIMIT, WHICH SETS A FUNDAMENTAL LIMIT ON HOW CLOSELY TWO POINTS CAN BE DISTINGUISHED. PREVIOUS BREAKTHROUGHS HAVE ACHIEVED SUPER-RESOLUTION BY ACTIVELY CONTROLLING OR LABELING THE SAMPLE, WHICH WORKS WELL FOR CERTAIN BIOMEDICAL SYSTEMS. HOWEVER, THIS APPROACH ISN?T POSSIBLE FOR LIVE BIOLOGICAL SAMPLES THAT COULD BE DAMAGED BY PROBES, FOR DELICATE QUANTUM SYSTEMS THAT CAN BE DISTURBED BY MEASUREMENT, OR FOR ASTRONOMICAL OBJECTS THAT WE SIMPLY CANNOT MANIPULATE. THIS PROJECT AIMS TO OVERCOME THESE CHALLENGES BY DEVELOPING NEW SUPER-RESOLUTION METHODS THAT DO NOT REQUIRE CONTROLLING THE SOURCE. THE RESEARCH TEAM WILL COMBINE ADVANCED PHYSICAL MODELS OF IMAGING WITH ARTIFICIAL INTELLIGENCE (AI) TO RESOLVE DETAILS OF PASSIVE, UNCONTROLLABLE OBJECTS IN REAL TIME. THIS RESEARCH WILL PROMOTE THE PROGRESS OF IMAGING AND SENSING SCIENCE BY PUSHING THE BOUNDARIES OF WHAT IS POSSIBLE IN OPTICAL IMAGING, BENEFITING FIELDS LIKE MEDICINE, ASTROPHYSICS, AND QUANTUM SENSING. IN ADDITION, BY INTEGRATING ARTIFICIAL INTELLIGENCE WITH OPTICAL ENGINEERING, THE PROJECT WILL CREATE UNIQUE EDUCATIONAL OPPORTUNITIES IN QUANTUM AND OPTICAL PHYSICS AND AI FOR HIGH SCHOOL, UNDERGRADUATE, AND GRADUATE STUDENTS, HELPING TO INSPIRE AND TRAIN THE NEXT GENERATION OF SCIENTISTS AND ENGINEERS. THIS PROJECT AIMS TO ACHIEVE REAL-TIME QUANTUM SUPER-RESOLUTION IMAGING OF PRACTICAL PASSIVE POINT SOURCES BY DEVELOPING A PARAMETER-DECOUPLED SUPPER-RESOLUTION TECHNIQUE INTEGRATED WITH PHYSICS-INFORMED ROBUST DEEP LEARNING. WHILE PRIOR SUPER-RESOLUTION METHODS HAVE OVERCOME THE ABBE-RAYLEIGH DIFFRACTION LIMIT FOR CONTROLLABLE ACTIVE SOURCES, PRACTICAL APPROACHES FOR PASSIVE, INCOHERENT, AND UNBALANCED SOURCES REMAIN ELUSIVE DUE TO REAL-WORLD IMPERFECTIONS, MULTI-SOURCE COMPLEXITIES, AND STABILITY CHALLENGES. BUILDING ON THE TEAM?S PREVIOUS THEORETICAL ADVANCES AND PROMISING PRELIMINARY RESULTS (REACHING 14 TIMES BETTER THAN THE CONVENTIONAL RESOLUTION LIMIT), THE PROJECT PROPOSES A THREE-STEP STRATEGY: PHYSICS-INFORMED MACHINE-LEARNING SUPER-RESOLUTION, STABILITY-DRIVEN REAL-TIME DEEP LEARNING, AND EXPERIMENTAL VALIDATION. SCIENTIFICALLY, THE PRIMARY OBJECTIVES OF THIS PROPOSAL ARE A HIGH-PRECISION, NOISE-TOLERANT TECHNIQUE THAT OVERCOMES PARTIAL COHERENCE, INTENSITY IMBALANCE, RANDOM PHASE AND PHOTON STATISTICS LIMITATIONS, WITH BROADER IMPACTS ACROSS OPTICAL IMAGING IN ASTROPHYSICS, BIOMEDICAL MEASUREMENT, AND QUANTUM INFORMATION SCIENCE. ADDITIONALLY, THE OBJECTIVES INCLUDE COMPREHENSIVE EDUCATIONAL OUTREACH AND TRAINING EFFORTS TO PROMOTE STEM PARTICIPATION FROM HIGH SCHOOL THROUGH GRADUATE EDUCATION. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

DIRECTED IONIC TRANSPORT IN POLY(IONIC LIQUID)-GRAFTED NANOPARTICLES IN POLARIZABLE MEDIA

OPTIMIZING PERIPHERAL NERVE REGENERATION USING COMPUTATIONAL INTELLIGENCE BASED T

PERSONALIZED PREDICTIONS OF BIOMARKER PROGRESSION IN ALZHEIMER'S DISEASE

BIOFILM GROWTH ON FUNCTIONALIZED SURFACES

MULTIFUNCTIONAL ANTIMICROBIAL MICROGELS

EVAPORATIVE ASSEMBLY OF DRUG-ELUTING BIORESORBABLE NANOCOMPOSITE MICROPATTERNS

CAREER: EVALUATING COOPERATIVE INTELLIGENCE IN CONNECTED COMMUNITIES -THIS PROJECT EXPLORES A VISION WHERE GROUPS OF BUILDINGS AUTONOMOUSLY COOPERATE TO SHARE ENERGY RESOURCES SUCH AS SOLAR PANELS, BATTERIES, OR GENERATORS. THROUGH MULTI-AGENT SIMULATIONS AND REAL-WORLD EXPERIMENTS, IT AIMS TO REVEAL HOW COOPERATION CAN EMERGE AND PERSIST WITHIN SELF-ORGANIZING ENERGY SYSTEMS, AND HOW IT CAN LEAD TO COLLECTIVE BENEFITS SUCH AS ENERGY SAVINGS AND CLIMATE ADAPTATION. BY HARNESSING COLLECTIVE EFFORTS, THIS WORK AIMS TO CATALYZE A SHIFT TOWARDS COLLECTIVE INFRASTRUCTURE SYSTEMS. BEYOND ITS TARGETED SCIENTIFIC CONTRIBUTIONS, THE PROJECT INCLUDES AN INTERACTIVE EDUCATIONAL PROGRAM FEATURING GAMES AND SIMULATIONS FOSTERING PUBLIC UNDERSTANDING OF COOPERATION AS A VITAL ASPECT FOR ENERGY EQUITY AND SUSTAINABILITY. THE GOAL IS FOR FINDINGS TO EMPOWER ARCHITECTS, PLANNERS, AND POLICYMAKERS WITH KNOWLEDGE AND TOOLS TO DESIGN AND MANAGE CONNECTED COMMUNITIES WHERE BUILDINGS SHARE, RATHER THAN COMPETE FOR, ENERGY RESOURCES. THE PROJECT ASPIRES TO INSPIRE A NEW WAY OF THINKING ABOUT HOW COLLECTIVE COLLABORATION CAN CREATE BETTER ENERGY SYSTEMS. THIS PROJECT WILL INVESTIGATE HOW COOPERATION CAN EMERGE AND BE SUSTAINED AMONG GROUPS OF BUILDINGS THAT STRATEGICALLY POOL DISTRIBUTED ENERGY RESOURCES (DERS) TO ENHANCE SHARED RESILIENCE AND SUSTAINABILITY. IT WILL ESTABLISH AN INTERDISCIPLINARY FRAMEWORK TO INVESTIGATE COOPERATION WITHIN MULTI-AGENT ENERGY SYSTEMS. THE TECHNICAL APPROACH SYNERGISTICALLY COMBINES REINFORCEMENT LEARNING-BASED CONTROL POLICIES, MULTI-AGENT SIMULATIONS, AND EMPIRICAL VALIDATION. IT SEEKS TO FORMALLY MODEL THE COMPLEX RECIPROCAL INTERACTIONS UNDERLYING COOPERATIVE ENERGY BEHAVIORS WITHIN CONNECTED COMMUNITIES. THE OVERARCHING GOAL IS TO ELUCIDATE QUANTITATIVE DESIGN PRINCIPLES AND POLICY GUIDELINES THAT EMBED COOPERATIVE INTELLIGENCE WITHIN ENGINEERED, SELF-ORGANIZING ARCHITECTURES TO ENHANCE COLLECTIVE RESILIENCE AND EQUITABLE RESOURCE ALLOCATION. THE FIRST THRUST OF THE PROJECT INVOLVES DEVELOPING AN ADAPTABLE SIMULATION TESTBED TO EVALUATE COOPERATION TRAJECTORIES UNDER VARIOUS ENERGY MANAGEMENT SCHEMES, COMMUNITY CONFIGURATIONS, AND DECISION PROTOCOLS. THIS FLEXIBLE VIRTUAL TESTBED WILL ENABLE SYSTEMATIC EVALUATION OF FACTORS THAT INFLUENCE EMERGENT COOPERATION. THE SECOND THRUST ENTAILS AN EMPIRICAL ANALYSIS TO DIAGNOSE HOW REAL-WORLD SOCIO-TECHNICAL ELEMENTS?FROM HUMAN PREFERENCES TO TECHNOLOGY DIFFUSION ASYMMETRIES?SHAPE COOPERATIVE OUTCOMES. GROUNDING INSIGHTS IN DATA WILL UNCOVER ACTIONABLE PATHWAYS FOR IMPLEMENTATION. FINALLY, INTERACTIVE WEB PLATFORMS AND GAMES BASED ON CONSTRUCTIVIST LEARNING WILL CULTIVATE PUBLIC UNDERSTANDING OF DECENTRALIZED SYSTEMS AND COOPERATIVE INTELLIGENCE FOR EQUITABLE AND RESILIENT ENERGY ACCESS. BY INTEGRATING INSIGHTS ACROSS TECHNICAL AND SOCIAL DIMENSIONS, THIS PROJECT WILL INFORM THE DESIGN OF EFFICIENT, EFFECTIVE CONNECTED COMMUNITIES AND FOSTER SUSTAINABLE, EQUITABLE ENERGY SYSTEMS. BY ELUCIDATING STRATEGIES FOR LOCALIZED SHARING AND ENERGY MANAGEMENT, THE PROJECT WILL SHOWCASE MODELS OF DISTRIBUTED OWNERSHIP AND GOVERNANCE. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.

SUPPORTING SUSTAINABLE EVOLUTION OF ELECTRICAL ENERGY SYSTEMS VIA CLOSED-LOOP CONSUMER BEHAVIOR AND MARKET SYSTEM MODELING

HIGH-RESOLUTION DYNAMIC IMAGING OF OVARIAN CANCER METASTASIS POST CHEMOTHERAPY - PROJECT SUMMARY/ABSTRACT WOMEN UNDERGOING CHEMOTHERAPY TREATMENT FOR OVARIAN CANCER (OC) CAN DEVELOP NEW PERITONEAL METASTASES DURING RECOVERY TIME, INDICATING A POSSIBILITY THAT THERAPY PROMOTES THE EVOLUTION OF METASTATIC CELL POPULATIONS. THEREFORE, IT IS OF THE HIGHEST CLINICAL INTEREST TO STUDY THE EFFECTS OF CHEMOTHERAPY ON PERITONEAL DISSEMINATION. A HALLMARK OF OC PERITONEAL DISSEMINATION IS A DISRUPTION OF TUMOR TISSUE THAT LEADS TO THE FORMATION OF CARCINOMA OUTGROWTHS THAT SUBSEQUENTLY DETACH, TRANSIT INTO THE PERITONEAL CAVITY, AND INTERCALATE INTO MESOTHELIUM THAT COVERS VITAL ORGANS. IN THIS APPLICATION, WE HYPOTHESIZE THAT CHEMOTHERAPY DISRUPTS TUMOR TISSUE, PROMOTES OUTGROWTHS, CELL DETACHMENT, AND TUMOR MESOTHELIAL INTERCALATION. TO TEST OUR HYPOTHESIS, WE PROPOSE TWO AIMS THAT CENTER ON THE DEVELOPMENT OF IN VITRO AND IN VIVO IMAGING APPROACHES THAT WILL ENABLE VISUALIZATION AND QUANTIFICATION OF OC DISSEMINATION POST-CHEMOTHERAPY. IN AIM 1 OF THIS PROJECT, WE WILL ESTABLISH AN ORGANOID-BASED IMAGING ASSAY TO DETERMINE THE EFFECTS OF CHEMOTHERAPY ON OC ORGANOID STRUCTURE, OUTGROWTH FORMATION, CELL DETACHMENT, AND MESOTHELIAL INTERCALATION. AIM 2 OF THIS PROPOSAL FOCUSES ON DEVELOPING AN IN VIVO IMAGING ASSAY IN A MOUSE MODEL TO STUDY THE DYNAMIC ACTIVITIES OF OC IN RESPONSE TO CHEMOTHERAPY. TO COMPLETE THESE AIMS, WE HAVE ASSEMBLED AN INTERINSTITUTIONAL TEAM WITH MEMBERS THAT BRING UNIQUE EXPERTISE IN TISSUE ENGINEERING OF OC DISSEMINATION, 3D IN VIVO IMAGING OF THE MOUSE REPRODUCTIVE SYSTEM, AND GENETICALLY MODIFIED MODELS OF OVARIAN CANCER. THIS MULTI-PI COMBINED EFFORTS WILL PROVIDE MUCH-NEEDED INFORMATION ABOUT THE EFFECTS OF CHEMOTHERAPY ON THE DYNAMICS OF OC PERITONEAL DISSEMINATION.

WHILE MANY PREVIOUSLY PROPOSED ENCELADUS PLUME TRANSPORT MODELS RELY ON A SHARP LIQUID/GAS BOILING INTERFACE MOST FORMS OF TERRESTRIAL EXPLOSIVE SILICATE VOLCANISM A POTENTIAL ANALOG EXHIBIT CONTINUOUS EXSOLUTION/DEGASSING AND EXPANSION OF DISSOLVED VOLATILE BUBBLES DURING ASCENT WITHIN AN OPEN CONDUIT. THE TEAM PROPOSES TO ADVANCE THE MULTI-COMPONENT MULTI-PHASE COMPRESSIBLE PLUME TRANSPORT MODEL "CRYO-ERUPT." ADVANCING THIS MODEL AND DETERMINING IF MODEL PREDICTIONS ARE CONSISTENT WITH EXISTING ENCELADUS OBSERVATIONS REPRESENTS AN IMPORTANT CONTRIBUTION FOR TWO PRIMARY REASONS: 1) THE GROWING INTEREST IN DIRECTLY SAMPLING ERUPTED OR ERUPTING MATERIALS FOR FUTURE MISSIONS TO ENCELADUS 2) THE UNDER-EXPLORED NATURE OF THIS CLASS OF PLUME TRANSPORT MODEL WHICH OUR PRELIMINARY WORK SUGGESTS IS VALID AND STABLE ON LONG TIMESCALES. IF CONSISTENT WITH ENCELADUS OBSERVATIONS THE CRYO-ERUPT MODEL FUNDAMENTALLY CHANGES OUR UNDERSTANDING OF HOW THE ENCELADUS PLUME ERUPTS AND HAS IMPLICATIONS FOR RELATING PLUME OBSERVATIONS TO OCEAN COMPOSITION.

ENGINEERED INTRAVASCULAR CATHETERS FOR THE TREATMENT OF BACTEREMIA

CAREER: PRECISE MATHEMATICAL MODELING AND EXPERIMENTAL VALIDATION OF RADIATION HEAT TRANSFER IN COMPLEX POROUS MEDIA USING ANALYTICAL RENEWAL THEORY ABSTRACTION-REGRESSIONS -MODELING RADIATION HEAT TRANSFER IN COMPLEX MEDIA PRESENTS A SIGNIFICANT AND BURDENSOME CHALLENGE, PARTICULARLY AS THE EXISTING COMPUTATIONAL SOLUTIONS HAVE NOT ADEQUATELY EVOLVED TO MATCH THE INCREASING GROWTH, DIVERSITY, AND COMPLEXITY OF REAL-WORLD APPLICATIONS. THIS CHALLENGE IS ESPECIALLY PRONOUNCED IN FIELDS WHERE PRECISE CONTROL AND UNDERSTANDING OF THERMAL PROCESSES ARE PIVOTAL, SUCH AS IN ADVANCED MATERIALS ENGINEERING, ENERGY-EFFICIENT BUILDING DESIGN, AND HIGH-PERFORMANCE COMPUTING SYSTEMS. BY DEVELOPING ADVANCED MATHEMATICAL AND COMPUTATIONAL MODELS, THIS PROJECT AIMS TO SIGNIFICANTLY IMPROVE THE ACCURACY, SPEED, AND APPLICABILITY OF RADIATION HEAT TRANSFER ESTIMATIONS BEYOND THE CAPABILITIES OF EXISTING METHODS. AT THE HEART OF THESE MODELS IS THE NOVEL USE OF RENEWAL, RUIN, AND SURPLUS RISK THEORY IN THE MATHEMATICAL DERIVATIONS OF RADIATIVE TRANSFER IN POROUS MEDIA. THE BROADER IMPACT OF THIS ENDEAVOR EXTENDS TO ITS POTENTIAL IN REVOLUTIONIZING MULTI-SCALE ENERGY TRANSPORT QUANTIFICATION AND MANAGEMENT, INFLUENCING VARIOUS APPLICATIONS FROM RENEWABLE ENERGY TO BIOMEDICAL ENGINEERING AND CLIMATOLOGY. THE SOCIETAL CONTRIBUTIONS OF THE PROJECT EXTEND BEYOND ADVANCING SCIENTIFIC KNOWLEDGE, ENCOMPASSING THE DEVELOPMENT OF MORE EFFICIENT AND SUSTAINABLE ENERGY TECHNOLOGIES. THE EDUCATIONAL OBJECTIVES OF THE PROJECT INCLUDE FOSTERING SCIENCE TECHNOLOGY ENGINEERING AND MATHEMATICS ENGAGEMENT AMONG K-12 STUDENTS, SEAMLESSLY INTEGRATING WITH THE OVERARCHING RESEARCH GOALS. THE TECHNICAL OBJECTIVE OF THIS CAREER PROJECT IS TO ESTABLISH A NOVEL ANALYTICAL DUAL ABSTRACTION-REGRESSION FRAMEWORK FOR CHARACTERIZING AND SOLVING MACRO RADIATIVE QUANTITIES IN HETEROGENEOUS MEDIA. THIS APPROACH COMBINES ABSTRACTION MODELS REPRESENTING MACRO-CONFIGURATIONS WITH POINT-WISE RADIATIVE FEATURE TENSORS WITH ANALYTICAL REGRESSION MODELS BASED ON RENEWAL/RUIN AND POWERS-GERBER-SHIU RISK SURPLUS THEORIES. THESE MODELS ARE DESIGNED TO PRECISELY ESTIMATE RADIATIVE MACRO PROPERTIES FROM HOMOGENIZED MICRO TENSORS, FILLING A CRITICAL KNOWLEDGE GAP IN THE FIELD. THE PROJECT ENCOMPASSES THREE MAIN RESEARCH OBJECTIVES: (I) UNDERSTANDING THE CONNECTIONS BETWEEN RISK SURPLUS THEORY AND RADIATION HEAT TRANSFER CHARACTERIZATION, (II) DEVELOPING DUAL ABSTRACTION-REGRESSION MODELS FOR PRECISE RADIATIVE ESTIMATIONS, AND (III) EVALUATING THE FRAMEWORK'S EFFECTIVENESS THROUGH EXPERIMENTAL VALIDATION. THE INTELLECTUAL SIGNIFICANCE OF THIS PROJECT IS ROOTED IN ITS POTENTIAL TO TRANSFORM THE WAY RADIATION HEAT TRANSFER IS MODELED IN COMPLEX MEDIA, ESPECIALLY IN POROUS STRUCTURES WHERE CURRENT METHODOLOGIES FALL SHORT. THE BROADER IMPACT IS FAR-REACHING, WITH IMPLICATIONS FOR ENHANCING SOLAR ENERGY SYSTEMS, IMPROVING THERMAL MANAGEMENT IN ELECTRONIC DEVICES, AND CONTRIBUTING TO THE DEVELOPMENT OF NEW MATERIALS WITH OPTIMIZED THERMAL PROPERTIES. THIS RESEARCH IS EXPECTED TO YIELD SIGNIFICANT ADVANCEMENTS IN THE FUNDAMENTAL UNDERSTANDING OF RADIATION HEAT TRANSFER, DRIVING INNOVATION IN BOTH THEORETICAL AND APPLIED ASPECTS OF THE SCIENCE OF RADIATION. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.- SUBAWARDS ARE NOT PLANNED FOR THIS AWARD.