2246358
COLLABORATIVE RESEARCH: IRES TRACK I: US/FRANCE MULTIDISCIPLINARY COLLABORATION IN NANOELECTRONICS, QUANTUM MATERIALS AND NEXT-GENERATION COMPUTING -THIS IRES PROJECT INVOLVES A RESEARCH AND EDUCATIONAL COLLABORATION BETWEEN UNIVERSITY OF CALIFORNIA, SAN DIEGO (UCSD) AND NEW YORK UNIVERSITY (NYU) IN THE US WITH INTERNATIONAL PARTNER INSTITUTIONS UNIVERSIT? DE LORRAINE AND UNIVERSIT? PARIS-SACLAY IN FRANCE. THE PROJECT WILL ADDRESS SOCIETAL NEEDS AND KEY TECHNOLOGICAL BARRIERS TO NEXT GENERATION COMPUTATION AND DATA STORAGE BY TRAINING US STUDENTS TO ADDRESS THESE CHALLENGES. A GOAL IS TO BROADLY EDUCATE DIVERSE, GLOBALLY ENGAGED, AND TALENTED YOUNG SCIENTISTS AND ENGINEERS IN MODERN MATERIALS AND DEVICES FOR ADVANCED COMPUTING. THIS WILL BE ACCOMPLISHED BY HAVING THEM STUDY AND CONDUCT RESEARCH IN FOREFRONT AREAS OF NANO-SYSTEMS AND QUANTUM MATERIALS THAT CAN ENABLE A NEW GENERATION OF COMPUTERS DURING RESEARCH INTERNSHIPS IN FRANCE. THE TOPICS ARE AT THE HEART OF RESEARCH ON NEW LOW-POWER COMPUTING NEEDS FOR OUR CURRENT DATA-CENTERED SOCIETY. IN THE PROJECT, THE STUDENT RESEARCHERS WILL BE EXPOSED TO A WIDE RANGE OF SCIENTIFIC AND ENGINEERING CHALLENGES AND BE TRAINED TO WORK EFFECTIVELY ACROSS DISCIPLINES. THIS IRES PROJECT WILL ENGAGE 9 STUDENTS PER YEAR IN RESEARCH INTERNSHIPS, WHICH ARE TYPICALLY 8 WEEKS-LONG. THE PROPOSED STUDENT POPULATION WILL BE 3 UNDERGRADUATE AND 2 GRADUATE RESEARCHERS PER YEAR FROM UCSD AND 2 UNDERGRADUATE AND 2 GRADUATE RESEARCHERS PER YEAR FROM NYU. THE INTELLECTUAL MERIT OF THIS MATERIALS-CENTERED MULTIDISCIPLINARY RESEARCH IS BASED ON EXPLOITING THE UNIQUE PROPERTIES OF QUANTUM MATERIALS TO ADDRESS FUNDAMENTAL PROBLEMS ASSOCIATED WITH CREATING NEW TYPES OF NON-VOLATILE MEMORIES AND ADVANCING NEXT GENERATION COMPUTING. SPECIFIC RESEARCH AND EDUCATION ACTIVITIES WILL FOCUS ON THE FABRICATION AND ADVANCED CHARACTERIZATION OF NEW QUANTUM MATERIALS, INTEGRATION OF THESE MATERIALS INTO PROTOTYPE DEVICES, DEVICE TESTING, AND ADVANCED MODELING. THE RESULTS WILL BE THE INPUT TO THEORY AND MODELING OF SCALING UP MEMORY-BASED BRAIN-INSPIRED COMPUTER ARCHITECTURES. THE RESEARCH GOALS WILL BE ON UNDERSTANDING AND CONTROL OF NOVEL MATERIALS, WHICH WILL HAVE BROAD RANGING IMPACT FROM UNDERSTANDING THE PERFORMANCE OF CURRENT DEVICES, TO ASSESSING THE POTENTIAL OF NEXT GENERATION ENERGY EFFICIENT, ULTRAFAST, AND ULTRA-SMALL MEMORY DEVICES. THUS THE WORK WILL PROVIDE INPUT TO THE MODELING AND DESIGN OF MEM-COMPUTING NETWORKS AND ARCHITECTURES. THE INTEGRATION OF RESEARCH AND EDUCATION WILL BE ACHIEVED VIA SEVERAL MECHANISMS INCLUDING RESEARCH ACTIVITIES AT WORLD-CLASS INTERNATIONAL LABORATORIES, PARTICIPATION OF STUDENTS IN SUMMER SCHOOLS, PRESENTATION OF THEIR RESEARCH AT INTERNATIONAL AND UNIVERSITY CONFERENCES, AND CONTINUED RESEARCH OPPORTUNITIES AT THEIR HOME INSTITUTIONS. THESE EFFORTS ARE AIMED AT STRENGTHENING THE PIPELINE OF STUDENTS, INCLUDING MINORITY AND WOMEN STUDENTS, INTO STEM WITH A FOCUS ON NANOTECHNOLOGIES. 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.
New York University
Project Grant
$150.0k 4/15/23 4/3/23 2330504
The National Science Foundation's Office of International Science and Engineering awarded a $249,987 Project Grant to the President and Board of Trustees of Santa Clara University (SCU) to support U.S. participation in the planning phase of a global research and training center. The planned center, co-led by SCU and Concordia University in Canada, aims to create a platform for collaborative investigation, innovation, and education towards a user-centric energy economy for grid-interactive communities. Key focus areas include enabling mechanisms and technologies to increase community acceptance, stakeholder benefits, and provider/consumer interaction of clean energy. The design phase will investigate critical applications, new theories and frameworks, clean energy market architectures, and grid edge technologies to advance scientific knowledge and engineering solutions for more equitable, affordable, flexible, and reliable access to clean energy supplies globally. The project will also provide special programs to promote diversity, equity, inclusion, and accessibility among multi-sector stakeholders.
President And Board Of Trustees Of Santa Clara College
Project Grant
$250.0k 1/1/24 9/18/23 2324781
COLLABORATIVE RESEARCH: CMOS+X: 3D INTEGRATION OF CMOS SPIKING NEURONS WITH ALBN/GAN-BASED FERROELECTRIC HEMT TOWARDS ARTIFICIAL SOMATOSENSORY SYSTEM -THREE-DIMENSIONAL HETEROGENEOUS INTEGRATION APPROACHES THAT COMBINE SILICON TECHNOLOGY WITH EMERGING DEVICES VIA ADVANCED PACKAGING PROCESSES CAN LEVERAGE UNIQUE SEMICONDUCTOR COMBINATIONS FOR ADVANCED ELECTRONICS/OPTOELECTRONICS. IN PARTICULAR, THE INTEGRATION OF SI-BASED ARTIFICIAL NEURONS AND ARTIFICIAL SYNAPSES WILL ENABLE ENERGY-EFFICIENT NEAR-SENSOR COMPUTING BY MINIMIZING DATA TRANSFER BETWEEN SENSOR, COMPUTING, AND ACTUATION UNITS. OUR NEUROMORPHIC ARRAY WILL ALLOW FOR THE IN-SITU PROCESSING OF DATA ACQUIRED BY VARIOUS SENSORS AND WILL PROVIDE NECESSARY CONTROL SIGNALS FOR ACTUATION THAT CAN BE UNIVERSALLY USED TO READ AND PROCESS EXTERNAL STIMULI AND RESPOND ACCORDINGLY, SUCH AS IN-SITU VISION PROCESSING AND MECHANICAL RESPONSE. SPECIFICALLY, 3D INTEGRATED NEUROMORPHIC UNIT WILL ENABLE HIGH-FREQUENCY AND HIGH-POWER OPERATION, REALIZING A SIMPLIFIED SENSING-TO-ACTION SYSTEM FOR ROBOTS, AUTONOMOUS VEHICLES, AND MEDICAL DEVICES. THUS, OUR PROPOSED HETEROGENEOUSLY INTEGRATED SYSTEM PROVIDES AN INNOVATIVE PARADIGM FOR A COMPACT NEUROMORPHIC EDGE-COMPUTING SYSTEM THAT IS DECENTRALIZED FROM CENTRAL PROCESSING UNITS (CPUS) AND GRAPHIC PROCESSING UNITS (GPUS). TO ACHIEVE THE ABOVE GOAL, THE PROPOSAL AIMS TO DESIGN AND DEMONSTRATE AN ON-CHIP ARTIFICIAL SOMATOSENSORY SYSTEM THAT CAN EMULATE THE BIOLOGICAL SOMATOSENSORY SYSTEM VIA 3D INTEGRATION OF COMPLEMENTARY METAL-OXIDE-SEMICONDUCTOR (CMOS)-BASED SPIKE NEURONS AND GAN FERROELECTRIC HIGH ELECTRON MOBILITY TRANSISTORS (FEHEMTS) BASED ARTIFICIAL SYNAPSES. THE DESIGNED NEUROMORPHIC CHIP WILL BE ABLE TO MODULATE SMALL SENSORY SIGNALS WITH A ONE-DIMENSIONAL TIME-SERIES VECTOR. THE RAW TIME-SERIES SENSORY SIGNALS CAN BE EFFICIENTLY PROCESSED WITH A CMOS-BASED SPIKING NEURAL NETWORK (SNN) FOR ENERGY-EFFICIENT AND SPATIOTEMPORAL ENCODING TO OVERCOME THE VON NEUMANN BOTTLENECK. THE DESIGNED NEUROMORPHIC CHIPS PROVIDE ONE-SHOT COMPUTATION, ANALOGOUS TO THE BIOLOGICAL COMPUTING IN THE CENTRAL NERVOUS SYSTEM (CNS). FURTHERMORE, CU-CU INTERCONNECTION WILL ENABLE THE HIGH DENSITY 3D INTEGRATION OF THE CMOS-BASED SNN WITH FERROELECTRIC TRANSISTORS BASED ON WIDE-BANDGAP SEMICONDUCTORS FOR IN-SITU PROCESSING OF THE INPUT STIMULUS TO TRIGGER MECHANICAL ACTUATION. THE TIME-SERIES DATA CAPTURED BY THE IMAGE SENSOR WILL BE ENCODED THROUGH THE FRONT-END CMOS-BASED NEUROMORPHIC CHIP IN A SPIKING DOMAIN. THE ENCODED OUTPUT SIGNALS WILL BE DIRECTLY TRANSMITTED TO THE BACK-END NEUROMORPHIC CHIP BASED ON THE FEHEMT CROSSBAR-BASED SYNPATIC ARRAY TO PROGRAM ITS WEIGHT VALUE. THE DECODED OUTPUT CURRENT THROUGH THE ALBN/GAN HEMT CROSSBAR ARRAY CAN EXCEED AN ORDER OF MANGITUDE OF AN AMPERE, ALLOWING IT TO DRIVE MECHANICAL ACTUATION FOR SYSTEM MACRO-MOTION, SUCH AS MECHANICAL OBJECT TRACKING. WE BELIEVE THE PROPOSED MIXED-SIGNAL NEUROMORPHIC ARRAY WILL ALLOW FOR THE IN-SITU PROCESSING OF TIME-SERIES SENSORY DATA, LEADING TO THE REALIZATION OF AN ULTRA-LOW-POWER ARTIFICIAL SOMATOSENSORY SYSTEM THAT PROVIDES POWER-EFFICIENT AND SPONTANEOUS COMPUTING FROM SENSING AND DATA PROCESSING TO REACTION FOR WIDESPREAD APPLICATIONS INCLUDING AIOT AND ROBOTICS. 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.
University Of Maryland, College Park
Project Grant
$288.0k 10/1/23 7/10/24 2247036
This three-year, $400,000 project grant from the National Science Foundation Office of International Science and Engineering (NSF OISE) CFDA #47.079 program will support international collaborations to develop expertise in solving water-related challenges. The University of California, Davis will partner with IHE Delft in the Netherlands to provide immersive experiences for three cohorts of U.S. graduate students in critical analysis of differing international approaches to water science, policy, and management.
Students will gain training and experience in flood risk management, drought and groundwater management, and freshwater ecosystems in a changing climate. Outcomes will include students trained to collaborate across borders on global problems, integrate disciplines and paradigms, and promote diversity and inclusion. The project aims to strengthen the U.S. STEM workforce and contribute to expertise in addressing water issues domestically and worldwide. Funding begins March 1, 2023 and concludes February 28, 2026.
University Of California, Davis
Project Grant
$400.0k 3/1/23 3/6/23 2302786
NSF-CSIRO: TOWARDS INTERPRETABLE AND RESPONSIBLE GRAPH MODELING FOR DYNAMIC SYSTEMS -REAL-WORLD NATURAL AND ENGINEERED SYSTEMS (E.G., FOOD WEB, POWER GRIDS, RIVER NETWORKS, AND OCEAN CURRENT NETWORKS) ARE INHERENTLY COMPLICATED AND ARE DRIVEN BY MANY FACTORS WITH DEPENDENCY RELATIONSHIPS. GRAPHS HAVE BEEN COMMONLY USED TO REPRESENT THE STRUCTURE AND CONTENT OF THESE SYSTEMS FOR EVENT PREDICTION AND RISK ESTIMATION. TO DATE, MANY GRAPH LEARNING METHODS, SUCH AS GRAPH NEURAL NETWORKS, HAVE BEEN PROPOSED, BUT PRIMARILY FOR STATIC GRAPHS. IN DYNAMIC SYSTEMS, THE STRUCTURE AND CONTENT ARE SIMULTANEOUSLY EVOLVING IN RESPONSE TO EMERGING TRENDS AND EVENTS, MAKING IT DIFFICULT TO UNDERSTAND AND INTERPRET HOW EACH PART OF THE GRAPH FUNCTIONS IN FORMING RELIABLE MODELS FOR PREDICTIONS. THIS PROJECT STRIVES TO BUILD A GRAPH LEARNING AND INTERPRETATION FRAMEWORK FOR DYNAMIC SYSTEMS BY COMBINING SENSOR PATTERN DISCOVERY, NODE INTERACTION AND NETWORK FUNCTIONALITY ANALYSIS, AND PHYSICS- AND KNOWLEDGE-INFORMED LEARNING. THE PROJECT WILL PROPOSE NEW ALGORITHMS FOR MODELING AND UNDERSTANDING LARGE-SCALE DYNAMIC SYSTEMS USING GRAPHS, AS WELL AS DEVELOP A PROTOTYPE FOR DOMAIN EXPERTS TO ANALYZE THEIR DATA, EXPLAIN WHAT IS CURRENTLY HAPPENING IN THE SYSTEM, UNDERSTAND THE RESULTING CONSEQUENCES, AND PROVIDE POSSIBLE MITIGATION STRATEGIES. THE JOINT EFFORT BETWEEN THE US AND AUSTRALIAN TEAMS WILL HELP UNDERSTAND/UNCOVER THE DYNAMICS OF WATER MONITORING SYSTEMS FOR DIFFERENT TERRAIN TYPES, INLAND AND COASTAL WATER EXCHANGE, TOXIC ALGAL BLOOMS, AND RESILIENCE OF RURAL AND REGIONAL COMMUNITIES. THE PROJECT INCLUDES THREE MAIN THRUSTS: (1) SENSOR SIGNAL TO FEATURE EXTRACTION AND UNDERSTANDING; (2) DYNAMIC NETWORK NODE MODELING AND INTERPRETATION; AND (3) DYNAMIC NETWORK FUNCTIONALITY AND TRUSTWORTHINESS. THE RESEARCH WILL STUDY SIGNAL SNIPPET PATTERN (SSP) EXTRACTION AND INTERACTION ANALYSIS TO UNDERSTAND HOW FEATURES INTERACT WITH EACH OTHER DURING THE EMERGENCE OF SIGNIFICANT EVENTS. AT THE NODE LEVEL, NEW TEMPORAL ENCODING AND SPATIAL-TEMPORAL GRAPH NEURAL NETWORKS WILL BE USED TO LEARN MODELS FOR NODE EVENT PREDICTION AND ANOMALY DETECTION FOR EARLY WARNING. THE STUDY OF NODE INTERACTION WILL ANSWER WHY, WHEN, AND HOW TWO NODES MAY BE INTERACTING WITH EACH OTHER. BEYOND NODE LEVEL INTERPRETATION, THE PROJECT WILL TARGET GRAPH FUNCTIONAL UNITS, ESTIMATE EACH SNAPSHOT GRAPH?S CONTRIBUTION, AND LOCATE SUBGRAPHS WITH THE HIGHEST SIGNIFICANCE CONCERNING OUTPUT SYSTEMS. A PERTURBATION-BASED POST-HOC EXPLAINER WILL PROVIDE COUNTERFACTUAL EXPLANATIONS TO ENHANCE THE EXPLAINABILITY AND TRUSTWORTHINESS OF DYNAMIC GRAPH NEURAL NETWORK SYSTEMS. THE RESEARCH WILL ALSO INVESTIGATE COMBINING PHYSICS LAWS AND DOMAIN KNOWLEDGE INTO DYNAMIC GRAPH NEURAL NETWORKS TO DEVELOP A DATA-EFFICIENT, ROBUST, AND RESPONSIBLE GRAPH MODELING FRAMEWORK. THIS IS A JOINT PROJECT BETWEEN U.S. AND AUSTRALIAN RESEARCHERS FUNDED BY THE COLLABORATION OPPORTUNITIES IN RESPONSIBLE AND EQUITABLE AI UNDER THE U.S. NSF AND THE AUSTRALIAN COMMONWEALTH SCIENTIFIC AND INDUSTRIAL RESEARCH ORGANISATION (CSIRO). 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.
Florida Atlantic University
Project Grant
$200.0k 5/15/23 5/12/23