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15,895 grants matching “artificial intelligence”
RET Site: Cybersecurity Research Experience for Educators through Data Science (CREEDS)
$630,000Deepak K Tosh · University Of Texas At El Paso · · FY2022 · CSE
Direct Numerical Simulations and Statistical Analysis to Guide Turbulent Combustion Closure Modeling
$630,000William A Sirignano · University Of California-Irvine · · FY2025 · ENG
Collaborative Research: FuSe: Efficient Situation-Aware AI Processing in Advanced 2-Terminal SOT-MRAM
$630,000Deliang Fan · Johns Hopkins University · · FY2023 · CSE
CC* Compute-Campus: Modernizing Campus Cyberinfrastructure for AI-Enhanced Research and Education (ModernCARE)
$630,000Tae Hyuk Ahn · Saint Louis University · · FY2024 · CSE
CC* Storage-Campus: The MSU Data Hub: A campus-wide hub for data storage, collaboration, and sharing to enable data-intensive research and education
$629,790Brian W O'Shea · Michigan State University · · FY2024 · CSE
Multi-Center Academic-Industrial Partnership for Personalized Al-Enabled High Count PET
$629,316Chi Liu · Yale University · R01 · FY2025 · CA
BID Core
$628,961Alison Meredith Buttenheim · University Of Pennsylvania · P30 · FY2025 · AG
Using Re-inforcement Learning to Automatically Adapt a Remote Therapy Intervention (RTI) for Reducing Adolescent Violence Involvement
$628,820Patrick M. Carter · University Of Michigan At Ann Arbor · R01 · FY2021 · HD
Pathogenesis of Primary Biliary Cholangitis
$628,683Konstantinos N Lazaridis · Mayo Clinic Rochester · R01 · FY2021 · DK
Elucidating ECM Signaling in Cardiac Organoids with Machine Learning and Single-cell Multiomics
$628,643Joseph C Wu · Stanford University · R01 · FY2022 · HL
Delaware Clinical and Translational Research ACCEL Program (BERD Core)
$628,604Cathy H Wu · University Of Delaware · U54 · FY2023 · GM
Motion-Resolved, Comprehensive Quantitative Tissue Characterization Using MR Multitasking
$628,575Debiao Li · Cedars-Sinai Medical Center · R01 · FY2022 · EB
Motion-Resolved, Comprehensive Quantitative Tissue Characterization Using MR Multitasking
$628,575Debiao Li · Cedars-Sinai Medical Center · R01 · FY2020 · EB
Validation and Implementation of an Artificial Intelligence Machine-to-Machine (M2M) Model for Glaucoma Screening
$628,531Felipe Medeiros · University Of Miami School Of Medicine · R01 · FY2024 · EY
Genome-wide mutational integration for ultra-sensitive plasma tumor burden monitoring in immunotherapy
$628,307Dan Landau · Weill Medical Coll Of Cornell Univ · R01 · FY2023 · CA
Quantification of Liver Fibrosis with MRI and Deep Learning
$628,266Lili He · Cincinnati Childrens Hosp Med Ctr · R01 · FY2021 · EB
Predicting Tissue and Functional Outcome in Acute Stroke
$628,218Gregory George Zaharchuk · Stanford University · R01 · FY2023 · NS
ContinuOuS Monitoring Tool for Delayed Cerebral IsChemia (COSMIC)
$628,133Soojin Park · Columbia University Health Sciences · R01 · FY2025 · NS
AI driven acute renal replacement therapy - (AID-ART)
$628,057Raghavan Murugan · University Of Pittsburgh At Pittsburgh · R01 · FY2022 · DK
Interactions of retroviral and host proteins guided by advanced modeling
$628,000Monica J Roth · Rutgers Biomedical And Health Sciences · R35 · FY2024 · GM
Interactions of retroviral and host proteins guided by advanced modeling
$628,000Monica J Roth · Rutgers Biomedical And Health Sciences · R35 · FY2025 · GM
Collaborative Research: SaTC: CORE: Medium: Detection of Images and Videos Created by Artificial Intelligence
$627,811Liyue Fan · University Of North Carolina At Charlotte · · FY2020 · CSE
NSF-BSF: Mechanisms of Perceptual Enhancement by Action Preparation
$627,789Joo-Hyun Song · Brown University · · FY2024 · SBE
Computational Pathology of Proteinuric Diseases
$627,585Laura Mariachiara Barisoni · Duke University · R01 · FY2022 · DK
**AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** WE WILL ASSEMBLE AND MAKE PUBLIC A NOVEL DATABASE OF ALL STATE-LEVEL LEGISLATION AFFECTING THE COSTS AND REVENUES ASSOCIATED WITH AGRICULTURE IN THE UNITED STATES FOR THE PERIOD 1975 TO 2021, NO MATTER WHETHER THE OBJECTIVES OF THOSE POLICIES WERE DIRECTLY RELATED TO AGRICULTURE OR NOT. USING A COMBINATION OF WEB-SCRAPING, MACHINE-LEARNING METHODS, AND ARTIFICIAL INTELLIGENCE, WE (I) ANALYZE ALL STATE-LEVEL LEGISLATION THE STUDY 1975-2021 TO IDENTIFY ANY POLICIES THAT ARE LIKELY TO AFFECT AGRICULTURAL COSTS AND REVENUES, EITHER DIRECTLY OR INDIRECTLY, (II) DEVELOP A MECHANISM TO CLASSIFY WHETHER AND HOW EACH POLICY INCREASES OR DECREASES THOSE SAME AGRICULTURAL COSTS AND REVENUES FOR SPECIFIC COMMODITIES AND CROPS WITHIN EACH STATE, AND (III) CREATE A WEB-BASED TOOL TO ALLOW OTHER RESEARCHERS TO SEARCH AND BROWSE COLLECTED POLICIES BY COMMODITY OR CROP. WE WILL USE THESE DATA TO ANSWER THREE SPECIFIC RESEARCH QUESTIONS. FIRST, WHAT ARE THE BROAD PATTERNS OVER TIME WHEN IT COMES TO AGRICULTURAL POLICY IN THE U.S.? SECOND, WHAT ARE THE GEOGRAPHICAL PATTERNS? THIRD, WE WILL ANALYZE THE CORRELATES OF AGRICULTURAL POLICY WITHIN EACH STATE FOR THE STUDY PERIOD. FINALLY, WE WILL WRITE A CODEBOOK TO ALLOW RESEARCHERS INTERESTED IN USING THESE DATA FOR THEIR OWN RESEARCH PURPOSES, AND WE WILL MAKE THE CODEBOOK, DATA, AND WEB-BASED TOOL PUBLICLY AVAILABLE THROUGH THE WEBSITES OF OUR RESPECTIVE INSTITUTIONS.
$627,562Regents Of The University Of Minnesota · · FY2022 · National Institute of Food and Agriculture