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15,895 grants matching “artificial intelligence”
Collaborative Research: Self-Identification for Robot Manipulation under Uncertainty Aided by Passive Adaptability
$399,032Aaron Dollar · Yale University · · FY2022 · ENG
Collaborative Research: Self-Identification for Robot Manipulation under Uncertainty Aided by Passive Adaptability
$399,000Kaiyu Hang · William Marsh Rice University · · FY2022 · ENG
AF: Small: Towards Theoretical Foundations of Multi-agent Learning - Algorithms, Dynamics and their Limitations
$398,990Ioannis Panageas · University Of California-Irvine · · FY2025 · CSE
PECASE: Computational Social Choice Theory: Strategic Agents and Iterative Mechanisms
$398,974Amy Greenwald · Brown University · · FY2002 · CSE
SBIR Phase I Topic 402 - Artificial Intelligence-Aided Imaging for Cancer Prevention, Diagnosis, and Monitoring
$398,952Henky Wibowo · Phenomapper, Llc · N43 · FY2020 · CA
MRI: Acquisition of a High Performance GPU/CPU Cluster for Research and Innovation in Computational Sciences and Engineering
$398,945Marc M Baarmand · Florida Institute Of Technology · · FY2020 · CSE
DS-I Africa - LAW
$398,940Donrich Willem Thaldar · University Of Kwazulu-Natal · U01 · FY2021 · MH
Metabolomics and Clinical Assays Center
$398,899Susan J Sumner · Univ Of North Carolina Chapel Hill · U24 · FY2022 · CA
Collaborative Research: RI: Medium: A Rigorous, General Framework for Tractable Learning of Large-Scale DAGs from Data
$398,866Nikhyl B Aragam · University Of Chicago · · FY2020 · CSE
Cornerstones for an Undergraduate Quantum Computing Program: Creating an Active Learning Curriculum
$398,804David H Hoe · Loyola University Maryland, Inc. · · FY2025 · EDU
Optimizing RNA import for microinjection-free genetic manipulation in C. elegans
$398,774Adriana San Miguel · North Carolina State University Raleigh · R21 · FY2025 · GM
Targeted Infusion Project: Shaping the Workforce for Industry 4.0 through AI and Data Science in Architecture, Engineering, Construction, and Digital Media Arts Education
$398,745Rania Labib · Prairie View A & M University · · FY2025 · EDU
CURRENT UNDERSTANDING: THE SUN CONTINUOUSLY AFFECTS THE INTERPLANETARY (IP) ENVIRONMENT BY A HOST OF INTERCONNECTED PHYSICAL PROCESSES. CORONAL MASS EJECTIONS (CMES) SOLAR FLARES AND SOLAR ENERGETIC PARTICLES (SEPS) ARE KEY DRIVERS OF GEOMAGNETIC STORMS THAT COULD CAUSE DISRUPTIONS OF TECHNOLOGICAL SYSTEMS SUCH AS ORBITING SATELLITES GLOBAL POSITIONING SYSTEMS AND GROUND-BASED POWER GRIDS AMONG OTHERS. WHILE SOME CMES AND FLARES ARE ASSOCIATED WITH INTENSE SEPS SOME SHOW NO OR LITTLE SEP ASSOCIATION. FURTHERMORE THERE IS NO STRONG CONNECTION BETWEEN THE PROPERTIES OF SEPS OBSERVED AT 1 AU AND THEIR PROGENITORS AT OR NEAR THE SUN. THIS IS DUE TO THE VERY COMPLEX ENVIRONMENT THAT DOMINATES SEP ORIGIN ACCELERATION AND TRANSPORT IN THE IP SPACE. TO DATE ROBUST LONG-TERM (HOURS) FORECASTING OF SEP PROPERTIES (E.G. ONSET PEAK INTENSITIES HEAVY ION COMPOSITION) DOES NOT EXIST. GOAL AND SCIENCE QUESTIONS: OUR OVERARCHING GOAL IS TO DETERMINE THE FEASIBILITY OF FORECASTING SEP OCCURRENCE ONSET TIME PEAK INTENSITIES AND HEAVY ION PROPERTIES USING DATA INTENSIVE CORRELATIVE STUDIES AND ARTIFICIAL INTELLIGENCE APPROACHES. WE WILL ACHIEVE THIS GOAL BY ANSWERING THE FOLLOWING SCIENCE QUESTIONS: Q1. WHAT ARE THE RELATIONSHIPS BETWEEN THE SUN S PHOTOSPHERIC SPATIAL FEATURES ERUPTING REGIONS AND FLARE PROPERTIES AND THE PROPERTIES OF THE ASSOCIATED ICMES IP SHOCKS IP PLASMA AND SEPS MEASURED AT 1 AU? Q2. CAN THIS COMPREHENSIVE SET OF PARAMETERS BE COMBINED TO PREDICT SEP PROPERTIES AT 1 AU? DATA AND METHODOLOGY: WE USE X-RAY FLARE PROPERTIES PHOTOSPHERIC SOLAR IMAGES ENERGETIC H-FE ION PLASMA AND MAGNETIC FIELD DATA FROM SDO SOHO GOES ACE WIND AND STEREO-A&B DURING SOLAR CYCLES 23 AND 24. USING ~6000 CATALOGUED FLARES DURING 1998-2018 WE WILL IDENTIFY THOSE ASSOCIATED WITH SEP EVENTS AT 1 AU. FOR EACH EVENT AND WHEN AVAILABLE WE WILL DERIVE A MATRIX OF PARAMETERS CHARACTERIZING ITS ASSOCIATED FLARE PROPERTIES PHOTOSPHERIC SPATIAL FEATURES UPSTREAM CONDITIONS IP SHOCK CME AND SEP PROPERTIES. STATISTICAL AND CORRELATION STUDIES WILL BE PERFORMED TO IDENTIFY THE DOMINANT DRIVERS THAT AFFECT SEP ONSET TIMES PEAK INTENSITIES AND HEAVY ION PROPERTIES. USING ALL INFERRED PARAMETERS WE WILL THEN UTILIZE MACHINE-LEARNING ALGORITHMS TO ENHANCE THE FORECASTING OF SEP OCCURRENCE AND PHYSICAL PROPERTIES AT 1 AU. EXPECTED FORECAST PRODUCTS METRICS AND VALIDATION METHODS: THE STUDY OUTCOME WILL INCLUDE THE FOLLOWING PRODUCTS: - A COMPREHENSIVE CATALOGUE OF SOLAR FLARES AND THEIR ASSOCIATED PHOTOSPHERIC FEATURES CMES IP PLASMA AND SEP PROPERTIES AT 1 AU. - A QUANTITATIVE ASSESSMENT OF FORECASTING SEP PROPERTIES AT 1 AU OVER A TIME RANGE BETWEEN ~20 MINUTES TO TENS OF HOURS. - METRICS THAT MEASURE THE AI CLASSIFIERS PERFORMANCES AND THEIR ACCURACIES. WE WILL ALSO DEVELOP RELEVANT SKILL SCORES TO ASSES THE GOODNESS OF EACH MODEL PREDICTABILITY POWER. - ALGORITHM TO VALIDATE THE MODELS USING OUT-OF-TIME SAMPLING MEASURES. TRAINING AND TESTING DATA SETS WILL BE RANDOMLY INITIALIZED AND WILL BE CROSS-SELECTED THROUGH A LARGE ITERATIVE PROCESS. RELEVANCE TO NASA AND H-SWO2R: OUR PROJECT RESPONDS DIRECTLY TO ALL GOALS OF THE HELIOPHYSICS SPACE WEATHER OPERATIONS-TO-RESEARCH (H-SWO2R) PROGRAM TO IMPROVE FORECASTS OF THE ENERGETIC PROTON AND/OR HEAVY ION CONDITIONS IN THE HELIOSPHERE DUE TO SOLAR ERUPTIONS AND TO IMPROVE DATA UTILIZATION TECHNIQUES THAT COULD ADVANCE FORECASTING CAPABILITIES AND WHICH COULD ALSO LEAD TO IMPROVED SCIENTIFIC UNDERSTANDING. RESULTS ARE RELEVANT TO TWO SCIENCE GOALS OF THE 2012 SOLAR AND SPACE PHYSICS DECADAL SURVEY AND TO A KEY STRATEGIC GOAL OF NASA S HELIOPHYSICS DIVISION I.E. UNDERSTAND THE SUN AND ITS INTERACTIONS WITH THE EARTH AND THE SOLAR SYSTEM INCLUDING SPACE WEATHER. THE OUTCOME ALSO ALIGNS WITH THE INTERESTS OF NASA SPACE RADIATION ANALYSIS GROUP (SRAG) NOAA SPACE SCIENCE PREDICTION CENTER (SWPC) AND THE NATIONAL SPACE WEATHER ACTION PLAN (NSWAP).
$398,680Southwest Research Institute · · FY2020 · National Aeronautics and Space Administration
Improving Native American Health Through Community-based Screening and Diagnostic Testing for Tuberculosis
$398,580Paul K Drain · University Of Washington · R21 · FY2024 · NR
Spin-Controlled Light-Emitting Diodes and Lasers
$398,500Igor Zutic · Suny At Buffalo · · FY2025 · ENG
Image Tools for Computational Cellular Barcoding and Automated Annotation
$398,349Steven M Finkbeiner · J. David Gladstone Institutes · R01 · FY2024 · LM
Image Tools for Computational Cellular Barcoding and Automated Annotation
$398,349Steven M Finkbeiner · J. David Gladstone Institutes · R01 · FY2025 · LM
PRESCIENT: A phase IIc, open-label, randomized controlled trial of ultra-short course bedaquiline, clofazimine, pyrazinamide and delamanid versus standard therapy for drug-susceptible tuberculosis
$398,334Serena Patricia Koenig · Brigham And Women'S Hospital · U01 · FY2025 · AI
CAREER: The Development, Design, and Ethical Issues of Algorithmic Hiring Tools
$398,296Ifeoma Y Ajunwa · University Of North Carolina At Chapel Hill · · FY2021 · SBE
SBIR Phase I - Topic 402 - Artificial Intelligence-Aided Imaging for Cancer Prevention, Diagnosis, and Monitoring
$398,149William Booker · Babel Analytics Llc · N43 · FY2020 · CA
NRI: FND: Collaborative Research: DeepSoRo: High-dimensional Proprioceptive and Tactile Sensing and Modeling for Soft Grippers
$398,096Chen Feng · New York University · · FY2021 · ENG
Improving representation of non-Hispanic Black and Hispanic study participants in a trial of virtual reality for chronic lower back pain
$398,083Brennan Spiegel · Cedars-Sinai Medical Center · UH3 · FY2021 · AR
AI Platform to Discover Therapeutics for Substance Use Disorders
$397,829Dale Adam Lauver · Callentis Consulting Group Llc · R41 · FY2025 · DA
SYMBOLIC SUPERCOMPUTER FOR ARTIFICIAL INTELLIGENCE RESEARCH ON SOFTWARE COLLABORATORS
$397,819Northwestern University · · FY2025 · Department of the Air Force
REU Site: BME Community of Undergraduate Research Scholars for Cancer (BME CUReS Cancer)
$397,808Mia K Markey · University Of Texas At Austin · · FY2018 · ENG