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48,453 grants matching “machine learning”
HDR Institute: Institute for Data Driven Dynamical Design
$16,656,673Eric S Toberer · Colorado School Of Mines · · FY2021 · CSE
Early Onset AD Consortium - the LEAD Study (LEADS)
$16,618,207Liana G Apostolova · Indiana University Indianapolis · U01 · FY2021 · AG
Infectious Diseases Collaborative Technological Research Resources - Bethesda
$16,477,283James Cherry · National Institute Of Allergy And Infectious Diseases · ZIC · FY2024 · AI
Center for Alzheimer's and Related Dementias (CARD): Harmonized Data-Derived Resources for the Alzheimer's Disease and Related Dementias Community
$16,309,444Andrew Singleton · National Institute On Aging · ZIA · FY2024 · AG
HDR Institute: Accelerated AI Algorithms for Data-Driven Discovery
$16,250,000Shih-Chieh Hsu · University Of Washington · · FY2021 · MPS
RII Track-1: Adaptive and Resilient Infrastructures driven by Social Equity (ARISE)
$16,096,547Belinda Sturm · University Of Kansas Center For Research Inc · · FY2022 · O/D
Natural Hazards Engineering Research Infrastructure: Cyberinfrastructure (DesignSafe) 2020-2025
$16,091,422Ellen M Rathje · University Of Texas At Austin · · FY2020 · ENG
HDR Institute: Imageomics: A New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning
$15,968,123Tanya Berger-Wolf · Ohio State University, The · · FY2021 · CSE
Early Onset AD Consortium - the LEAD Study (LEADS)
$15,954,813Liana G Apostolova · Indiana University Indianapolis · U01 · FY2020 · AG
The Temporal Dynamics of Learning
$15,938,236Garrison W Cottrell · University Of California-San Diego · · FY2006 · SBE
NSF Center for Computer-Assisted Synthesis
$15,600,000Olaf G Wiest · University Of Notre Dame · · FY2022 · MPS
Center for Alzheimer's and Related Dementias (CARD): Harmonized Data-Derived Resources for the Alzheimer's Disease and Related Dementias Community
$15,505,643Andrew Singleton · National Institute On Aging · ZIA · FY2023 · AG
Institute for Mathematical and Statistical Innovation
$15,500,000Kevin D Corlette · University Of Chicago · · FY2020 · MPS
THE RESILIENT EXTRATERRESTRIAL HABITATS RESEARCH INSTITUTE (RETHI) WILL HARNESS PROMISING NEXT-GENERATION TECHNOLOGICAL ADVANCES TO OVERCOME THE GRAND CHALLENGE OF DEEP SPACE HABITATION. BY LEVERAGING WORLD-LEADING EXPERTISE IN DEVELOPING CIVIL INFRASTRUCTURE RESPONSIVE TO CATASTROPHIC NATURAL HAZARDS AND MERGING IT WITH LEADERS IN THE FIELDS OF MODULAR AND AUTONOMOUS ROBOTICS PLATFORMS SMART BUILDINGS HYBRID SIMULATION COMPLEX SYSTEMS AND DIAGNOSTICS AND PROGNOSTICS WE WILL DEVELOP AND DEMONSTRATE THE TRANSFORMATIVE TECHNOLOGIES NEEDED TO DESIGN AND OPERATE RESILIENT DEEP SPACE HABITATS THAT CAN ADAPT ABSORB AND RAPIDLY RECOVER FROM EXPECTED AND UNEXPECTED DISRUPTIONS TO DEEP SPACE HABITAT SYSTEMS WITHOUT FUNDAMENTAL CHANGES IN FUNCTION OR SACRIFICES IN SAFETY. TO ACHIEVE THIS VISION THE RETHI TEAM WILL PURSUE THE FOLLOWING TIGHTLY-INTEGRATED RESEARCH OBJECTIVES: 1) ESTABLISH A COMPREHENSIVE RESILIENCE FRAMEWORK TO SUPPORT RESILIENT DESIGN OPERATION AND MANAGEMENT WHILE ANTICIPATING A HABITAT THAT EVOLVES AND GROWS OVER TIME; 2) CONDUCT THE RESEARCH AND DEVELOPMENT NECESSARY TO ESTABLISH SMART HABITATS THAT AUTONOMOUSLY SENSE ANTICIPATE AND RESPOND UNDER A VARIETY OF MANNED AND UNMANNED CONFIGURATIONS; 3) DEVELOP DECISION-MAKING TECHNIQUES THAT CAN WEIGH ALTERNATIVES FOR COMPLEX INTERCONNECTED INTERDEPENDENT HABITAT SYSTEMS WHILE ALSO UNDERSTANDING AND WHEN NECESSARY COMBATING THE NATURAL HUMAN INSTINCT TO INTERFERE OR OVERRIDE AUTOMATED SYSTEMS; AND 4) CONTRIBUTE TO THE NASA MISSION TO EDUCATE THE NEXT GENERATION OF ENGINEERS AND SCIENTISTS WHILE BUILDING PARTNERSHIPS WITH US INDUSTRIES AND ORGANIZATIONS AND OTHER NATIONS AND GENERATE DATA PRODUCTS THAT WILL INFORM AND GUIDE FUTURE RESEARCH AND DEVELOPMENT. TO ACCOMPLISH THESE GOALS WE WILL EMPLOY THE LATEST APPROACHES IN RESILIENT DESIGN AUTOMATED AND COORDINATED ROBOTICS MACHINE LEARNING INTELLIGENT SYSTEM MONITORING AND ADAPTIVE CONTROL. THESE PARALLEL BUT INTERCONNECTED EFFORTS WILL CONVERGE IN THE ESTABLISHMENT OF A CYBER-PHYSICAL TESTBED THAT INTEGRATES PHYSICAL MODELS WITH VIRTUAL MODELS TO SYSTEMATICALLY DEVELOP DEPLOY AND VALIDATE PRINCIPLES OF RESILIENCE AND AUTONOMOUS DETECTION AND CORRECTIVE CAPABILITIES. RETHI S HEADQUARTERS WILL BE AT PURDUE UNIVERSITY S DISCOVERY PARK. PARTICIPANT UNIVERSITIES WILL INCLUDE THE UNIVERSITY OF CONNECTICUT HARVARD UNIVERSITY AND THE UNIVERSITY OF TEXAS SAN ANTONIO. THROUGH THIS INTEGRATED EFFORT RETHI WILL FACILITATE DEEP SPACE HABITATS WITH EMBEDDED AUTONOMOUS CAPABILITIES THAT HAVE THE ABILITY TO OPERATE IN BOTH MANNED AND UNMANNED CONFIGURATIONS RAPIDLY AND SAFELY TRANSITIONING BETWEEN THOSE STATES WHEN NEEDED. RATHER THAN EVALUATING SUBSYSTEMS OR COMPONENTS INDEPENDENTLY RETHI WILL ESTABLISH A NEW APPROACH SYSTEM RESILIENCE THAT WILL BE THE TURNING POINT IN ACHIEVING PERMANENT DEEP SPACE HABITATS FOR LONG TERM HUMAN SETTLEMENT THAT ARE MORE COST-EFFECTIVE AND MORE RESPONSIVE TO UNFORESEEN EVENTS. THE INSTITUTE WILL SERVE AS A HUB FOR WORLD-CLASS RESEARCH PRIVATE AND PUBLIC PARTNERSHIPS AND PROJECT-BASED LEARNING BY DISTRIBUTED TEAMS OF STUDENTS ALL FOCUSED ON THE RESILIENCE OF COMPLEX SYSTEMS THAT ARE BUILT FROM AND DEPEND UPON THE SYNERGY OF COMPUTATIONAL AND PHYSICAL COMPONENTS.
$15,000,000Purdue University · · FY2020 · National Aeronautics and Space Administration
TO SAFELY EXECUTE THE HUMAN-EXPLORATION MISSIONS CURRENTLY BEING PROPOSED BY NASA THE DESIGN OF DEEP-SPACE HABITATS REQUIRES A FUNDAMENTALLY DISRUPTIVE APPROACH ONE THAT RELIES NOT ONLY ON TRADITIONAL SUBSYSTEM RELIABILITY ENGINEERING AND PROBABILISTIC RISK ANALYSIS BUT ON EMERGENT TECHNOLOGIES IN AUTONOMOUS SYSTEMS FAILURE-TOLERANT DESIGN HUMAN/AUTOMATION TEAMING DENSE SENSOR POPULATIONS DATA SCIENCE MACHINE LEARNING ROBOTIC MAINTENANCE AND ON-BOARD MANUFACTURING. ACCORDINGLY THE HOME STRI FOR DEEP SPACE HABITAT DESIGN WILL SYNTHESIZE THE IDEAS AND BACKGROUNDS OF A UNIQUELY EXPERIENCED DIVERSE AND OPERATIONALLY PRAGMATIC RESEARCH TEAM WITH INITIALLY-LOW TRL INNOVATIVE TECHNOLOGIES TO PROVIDE A 5-YEAR FLOW OF RESEARCH DELIVERABLES THAT COMPRISE A NEW PARADIGM FOR RESILIENT AUTONOMOUS AND SELF-MAINTAINED DEEP-SPACE HABITATS FOR HUMAN EXPLORERS. THE SCOPE OF THE HOME STRI S RESEARCH WILL BE DRIVEN BY THE TWO PRIMARY OPERATIONAL REQUIREMENTS OF DEEP-SPACE HABITATS: 1) KEEP HUMANS ALIVE WHILE THEY ARE RESIDENT 2) KEEP THE VEHICLE ALIVE WHILE THEY ARE NOT. THE PRIMARY DELIVERABLE OF THE HOME STRI RESEARCH IS A CLASS OF NOVEL DESIGN METHODOLOGIES BEST PRACTICES AND ANALOG-VALIDATED DESIGN TOOLS. OUR APPROACH WILL DRAW FROM FUNCTION-BASED ANALYSIS OF THE SPACECRAFT AND TASK ALLOCATION OPTIONS FROM WHICH A COMBINATION OF CURRENT VALIDATED TECHNOLOGIES EXTENDED SIGNIFICANTLY BY MODERN DEVELOPMENTS IN AUTONOMY SYSTEM RESILIENCE SELF-MAINTENANCE ROBOTICS AND AI WILL BE IDENTIFIED EVALUATED AND DEMONSTRATED. THIS FUNCTIONAL-NEEDS BASED APPROACH TO SMARTHAB DESIGN RESULTS IN THE FOLLOWING BROAD CATEGORIES OF RESEARCH: A. AUTONOMOUS FUNCTIONALITY B. VEHICLE SYSTEMS ENGINEERING FUNCTIONAL REQUIREMENTS OPERATIONS CONCEPT C. HUMAN HABITABILITY D. ROBUST/RELIABLE VEHICLE OPERABILITY. OUR GUIDING PHILOSOPHY IS INTELLIGENT APPLICATION OF SMART-SYSTEMS TECHNOLOGY. ACCORDINGLY IN EACH OF THE ABOVE RESEARCH TOPICS THE HOME STRI WILL INCORPORATE STATE-OF-THE-ART TECHNOLOGIES (FROM THE FIELDS OF SPACEFLIGHT AVIATION MANUFACTURING BUILDING SCIENCE ROBOTICS MEDICINE) AND THEN WILL PUSH BEYOND CURRENT PRACTICE TO FORMULATE MISSION-RELEVANT NEW RESEARCH WITH A CONVERGENT FOCUS ON AN INTELLIGENTLY-AUTONOMOUS FUNCTIONALLY-DRIVEN REALISTICALLY-ACHIEVABLE HABITAT DESIGN.
$15,000,000University Of California, Davis · · FY2020 · National Aeronautics and Space Administration
NSF Engines: Central Florida Semiconductor Innovation Engine
$14,938,671Ronald F Piccolo · Icamr, Inc. · · FY2024 · TIP
An Atlas of Human Brain Cell Variation
$14,907,240Steven Andrew McCarroll · Broad Institute, Inc. · UM1 · FY2022 · MH
WE PROPOSE TO CONTINUE OUR SURVEY TO DISCOVER NEAR EARTH OBJECTS (NEOS) WITH THE PAN-STARRS SYSTEM EXPANDED TO INCLUDE THE PAN-STARRS2 OBSERVATORY (PS2) TOGETHER WITH THE PAN-STARRS1 OBSERVATORY (PS1). SINCE THE START OF DEDICATED USE OF PAN- STARRS FOR NEO DISCOVERY IN SPRING OF 2014 PS1 HAS DISCOVERED OVER 40% OF ALL NEOS AND OVER 50% OF THE LARGER NEOS AND POTENTIALLY HAZARDOUS ASTEROIDS. PS1 IS ALSO THE LEADING DISCOVERY TELESCOPE FOR NEOS LARGER THAN 1 KM IN DIAMETER. WITH PS2 WE WILL AT LEAST DOUBLE OUR RAW SURVEY POWER. THE PAN-STARRS2 OBSERVATORY IS COMPLETE AND WE EXPECT TO COMPLETE ITS CAMERA (GPC2) SOON AND ADD SCIENCE OPERATIONS WITH PS2 TO THE ONGOING PS1 SURVEY. PS2 WILL BE IN FULL SCIENCE OPERATIONS BY THE START OF THE PERIOD OF PERFORMANCE OF THIS PROPOSAL. THE PS2 OPTICS ARE SUPERIOR TO THOSE OF PS1 AND WE HAVE ELIMINATED THE CAUSE OF CORRELATED READ NOISE THAT AFFLICTS FAINT OBJECTS IN THE CAMERA ON PS1. THUS WE EXPECT PS2 TO BE SLIGHTLY SUPERIOR TO PS1 IN DISCOVERING NEOS. THE PAN-STARRS SYSTEM WITH BOTH PS1 AND PS2 WILL CHANGE THE LANDSCAPE OF NEO DISCOVERY. WE CAN DOUBLE THE AREA SURVEYED OR PERFORM SELF FOLLOW-UP OBSERVATIONS WHICH WILL SIGNIFICANTLY DECREASE THE NUMBER OF OBJECTS LOST DUE TO AN ABSENCE OF FOLLOW-UP. MORE SELF-FOLLOW-UP WILL ALSO AVOID BIASES INTRODUCED BY THE DIGEST SCORE AND PROVIDE A MORE SYSTEMATIC SURVEY. WE WILL INVESTIGATE WIDE AREA SURVEY STRATEGIES RANGING BETWEEN THESE TWO EXTREMES TO OPTIMIZE FOR THE MOST COMPLETE NEO SURVEY AND TO REDUCE LOSSES OF RARE OR CAMOUFLAGED NEOS THAT WE ARE CURRENTLY UNDER-SAMPLING. IN ADDITION TO BRINGING THE SURVEY POWER OF PS2 ON LINE WE HAVE IDENTIFIED PROMISING AVENUES WHERE WE CAN IMPROVE OUR DISCOVERY RATE BY ADVANCES IN SOFTWARE INCLUDING IMPROVED DE-TRENDING ASTROMETRY OBJECT DETECTION IMAGE SUBTRACTION AND MACHINE LEARNING TECHNIQUES. FINALLY WE HAVE AN EXPERIENCED TEAM WITH A PROVEN RECORD OF SUCCESS.
$14,868,120University Of Hawaii · · FY2020 · National Aeronautics and Space Administration
Research Infrastructure: FABRIC Operations - Accelerating Innovation and Research
$14,598,010Paul Ruth · University Of North Carolina At Chapel Hill · · FY2023 · CSE
Center: NSF Engineering Research Center for Human AugmentatioN via Dexterity (HAND)
$14,000,000James E Colgate · Northwestern University · · FY2024 · ENG
Early Onset AD Consortium - the LEAD Study (LEADS)
$13,904,119Liana G Apostolova · Indiana University Indianapolis · U01 · FY2023 · AG
An Atlas of Human Brain Cell Variation
$13,764,972Steven Andrew McCarroll · Broad Institute, Inc. · UM1 · FY2024 · MH
Functional MRI Core Facility
$13,738,965Peter Bandettini · National Institute Of Mental Health · ZIC · FY2025 · MH
HDR Institute: HARP- Harnessing Data and Model Revolution in the Polar Regions
$13,731,122Vandana Janeja · University Of Maryland Baltimore County · · FY2022 · CSE
Critical Path Public Private Partnerships
$13,700,000Klaus Romero · Critical Path Institute · U18 · FY2025 · FD