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15,895 grants matching “artificial intelligence”
Building BRIDGES: Coordinating the Dissemination and Training for Biomedical Artificial Intelligence
$126,502Alex Bui · University Of California Los Angeles · U54 · FY2025 · HG
RUI-Meson Spectroscopy with GlueX and CLAS12 at Jefferson Lab
$126,442Carlos W Salgado · Norfolk State University · · FY2021 · MPS
Vector Flow Velocity Imaging of Human Placenta using Angle-resolved Ultrasound and Deep Learning
$126,375You Li · Stanford University · K99 · FY2022 · HD
Machine learning-based brain aging morphological signatures of chronic musculoskeletal pain
$126,333Pedro Antonio Valdes Hernandez · University Of Florida · K01 · FY2025 · AG
Machine learning-based brain aging morphological signatures of chronic musculoskeletal pain
$126,333Pedro Antonio Valdes Hernandez · University Of Florida · K01 · FY2024 · AG
THIS PROJECT PROPOSES TO DEVELOP AN ARTIFICIAL INTELLIGENCE (AI) TECHNIQUE CAPABLE OF PROCESSING IMAGES, DETECTING AND TRACKING ALL DROPLETS APPEARING ACROSS THE IMAGE FRAMES, AND MEASURING THE DROPLET SIZE AND MOTION. OUR CENTRAL HYPOTHESIS IS THAT THE INTEGRATION OF DEEP-LEARNING TECHNIQUES INTO THE IMAGE PROCESSING ALGORITHM WILL ENABLE PRECISE AND RELIABLE DETECTION, TRACKING, AND MEASURING OF DROPLET MOTION AND SIZE. IN ADDITION, THE FRAMEWORK WILL PRODUCE CONSISTENT RESULTS UNDER A VARIETY OF UNCERTAIN IMAGERY CONDITIONS. THE RATIONALE IS THAT DEEP LEARNING EXTRACTS MEANING FROM IMAGERY DATA AND HUMAN-LABELED DATA TO TRAIN A LEARNING SCHEME THAT INCREASES THE RELIABILITY AND ACCURACY OF DROPLET TRACKING.WE PLAN TO TEST THIS CENTRAL HYPOTHESIS BY PURSUING THE FOLLOWING THREE SPECIFIC AIMS: 1) DEVELOP A DEEP-LEARNING FRAMEWORK FOR DROPLET DETECTION WITH A FAST PROCESSING RATE, 2) INTEGRATE A FILTERING ALGORITHM INTO THE DEEP-LEARNING FRAMEWORK FOR DROPLET TRACKING, AND 3) DESIGN AND IMPLEMENT THE METRICS TO ASSESS THE SUCCESS RATE OF DROPLET DETECTION AND TRACKING.THE PROJECT OUTCOMES WILL PROVIDE AN AI SOLUTION TO A CHALLENGING PRECISION AGRICULTURE PROBLEM, NAMELY MEASURING THE DYNAMIC PROPERTY OF DROPLETS FROM A CROP SPRAYING SYSTEM. THE TOOL WILL LEAD TO THE NEXT GENERATION OF AGRICULTURAL NOZZLES WITH SIGNIFICANTLY IMPROVED PERFORMANCE, WHICH WILL IMPROVE PRODUCER EFFICIENCIES AND MINIMIZE CHEMICAL RUNOFF THAT POLLUTES THE ENVIRONMENT.
$126,116Florida Institute Of Technology Inc · · FY2023 · National Institute of Food and Agriculture
Using Routine Care Electronic Medical Record Data and Artificial Intelligence to Develop a Passive Digital Marker to Predict Postoperative Delirium
$126,092Sanjay Mohanty · Indiana University Indianapolis · K23 · FY2022 · AG
Novel artificial intelligence-based approaches to understand the pathological and genetic drivers of primary tauopathies
$126,010Kurt William Farrell · Icahn School Of Medicine At Mount Sinai · K01 · FY2023 · AG
Novel artificial intelligence-based approaches to understand the pathological and genetic drivers of primary tauopathies
$126,010Kurt William Farrell · Icahn School Of Medicine At Mount Sinai · K01 · FY2025 · AG
Collaborative Research: Preparing the Workforce for Industry 4.0's Intelligent Industrial Robotics
$126,000Nancy M Wilson · Lawson State Community College · · FY2020 · EDU
ERI: Distributed Learning in Regulation of UAV Communication Networks with Dynamic UAV Lineup
$125,926Ran Zhang · University Of North Carolina At Charlotte · · FY2023 · ENG
Novel artificial intelligence-based approaches to understand the pathological and genetic drivers of primary tauopathies
$125,914Kurt William Farrell · Icahn School Of Medicine At Mount Sinai · K01 · FY2024 · AG
Collaborative Research: Friedrichs Learning: Mathematical Foundation and Applications
$125,902Haizhao Yang · University Of Maryland, College Park · · FY2022 · MPS
Collaborative Research: Friedrichs Learning: Mathematical Foundation and Applications
$125,701Chunmei Wang · University Of Florida · · FY2022 · MPS
** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** THE RESEARCH ADDRESSES THE CHALLENGE OF OPTIMIZING BIRD WELFARE AND PRODUCTIVITY IN POULTRY PRODUCTION THROUGH ADVANCED TECHNOLOGICAL SOLUTIONS. TRADITIONAL METHODS RELY HEAVILY ON MANUAL LABOR AND BASIC MONITORING SYSTEMS, WHICH ARE NOT SUFFICIENT TO MAINTAIN CONSISTENT HEALTH AND ENVIRONMENTAL CONDITIONS FOR THE BIRDS. THE IMPORTANCE OF THIS RESEARCH EXTENDS BEYOND THE POULTRY INDUSTRY, AS IT ALSO IMPACTS ECONOMIC EFFICIENCY, COMMUNITY HEALTH, AND ENVIRONMENTAL SUSTAINABILITY. BY IMPROVING BIRD WELFARE, PRODUCTIVITY IS ENHANCED, LEADING TO BETTER ECONOMIC OUTCOMES FOR FARMERS. THIS, IN TURN, CONTRIBUTES TO FOOD SECURITY AND AFFORDABILITY. MOREOVER, HEALTHIER AND BETTER-MANAGED POULTRY OPERATIONS CAN REDUCE THE ENVIRONMENTAL FOOTPRINT, PROMOTING MORE SUSTAINABLE AGRICULTURAL PRACTICES. THEREFORE, THIS RESEARCH IS VITAL FOR FOSTERING A RESILIENT AGRICULTURAL SYSTEM THAT CAN ADAPT TO GROWING GLOBAL FOOD DEMANDS WHILE MAINTAINING HIGH STANDARDS OF ANIMAL WELFARE. WE WILL DEVELOP AN INTEGRATED CYBER-PHYSICAL SYSTEM (CPS) COMBINING ROBOTICS, ARTIFICIAL INTELLIGENCE (AI), AND ADVANCED SENSING TECHNOLOGIES. SENSORS WILL CONTINUOUSLY MONITOR ENVIRONMENTAL CONDITIONS AND BIRD HEALTH INDICATORS WITHIN POULTRY HOUSES, GATHERING DATA ON TEMPERATURE, HUMIDITY, AIR QUALITY, AND OTHER RELEVANT PARAMETERS. ROBOTICS WILL ASSIST IN TASKS SUCH AS LITTER AERATION AND EGG COLLECTION, REDUCING PHYSICAL BURDENS ON FARM WORKERS. AI MODELS WILL ANALYZE COLLECTED DATA TO DETECT PATTERNS AND ANOMALIES, PROVIDING INSIGHTS FOR OPTIMIZING BIRD WELFARE AND ENVIRONMENTAL CONDITIONS. THROUGH COLLABORATIVE PLANNING BETWEEN THE PHYSICAL SYSTEMS (ROBOTS AND SENSORS) AND THE CYBER LAYERS (AI AND DATA ANALYTICS), WE AIM TO CREATE A HOLISTIC MONITORING AND MANAGEMENT SYSTEM. THIS SYSTEM WILL BE VALIDATED IN REAL-WORLD COMMERCIAL POULTRY FARMS, ENSURING ITS PRACTICALITY AND SCALABILITY. THE ULTIMATE GOAL OF THIS PROJECT IS TO DEVELOP A DEPENDABLE AND ECONOMICALLY SUSTAINABLE CPS FOR IMPROVING BIRD WELFARE AND PRODUCTIVITY IN POULTRY PRODUCTION. ACHIEVING THIS GOAL WILL HAVE SIGNIFICANT SOCIETAL BENEFITS, INCLUDING ENHANCED FOOD SECURITY AND AGRICULTURAL SUSTAINABILITY. THE PROJECT AIMS TO REDUCE THE LABOR INTENSITY AND HEALTH RISKS ASSOCIATED WITH TRADITIONAL POULTRY FARMING METHODS, THEREBY IMPROVING THE QUALITY OF LIFE FOR FARM WORKERS. ADDITIONALLY, BY PROMOTING BETTER ANIMAL WELFARE, THE PROJECT SUPPORTS ETHICAL FARMING PRACTICES, WHICH ARE INCREASINGLY VALUED BY CONSUMERS. THE RESEARCH ALSO HAS BROADER IMPLICATIONS FOR THE DEVELOPMENT OF SMART FARMING TECHNOLOGIES THAT CAN BE ADAPTED TO OTHER LIVESTOCK INDUSTRIES, FOSTERING A MORE RESILIENT AND SUSTAINABLE AGRICULTURAL SECTOR.
$125,665Iowa State University Of Science And Technology · · FY2025 · National Institute of Food and Agriculture
Novel artificial intelligence-based approaches to understand the pathological and genetic drivers of primary tauopathies
$125,514Kurt William Farrell · Icahn School Of Medicine At Mount Sinai · K01 · FY2022 · AG
Multimodal monitoring and high-dimensional data for episode prediction in bipolar disorder
$125,486Abigail Ortiz · Centre For Addiction And Mental Health · R21 · FY2022 · MH
Genomics
$125,143Kevin Knudtson · University Of Iowa · P30 · FY2025 · CA
Collaborative Research: Frameworks: Building the Twenty-first Century Citizen Science Framework to Enable Scientific Discovery Across Disciplines
$125,020Mark R Salvatore · Northern Arizona University · · FY2025 · CSE
MEDIC ONE STROKE SCALE
$125,010University Of Washington · K23 · FY2000 · NS
MEDIC ONE STROKE SCALE
$125,010University Of Washington · K23 · FY2001 · NS
MEDIC ONE STROKE SCALE
$125,010University Of Washington · K23 · FY2003 · NS
MEDIC ONE STROKE SCALE
$125,010University Of Washington · K23 · FY2002 · NS
Minimization of Health Risks Due to Metalworking Fluid Microbes and Biocides: An Optimal Control System using Microfiltration and Flow Cytometry
$125,000Steven J Skerlos · Regents Of The University Of Michigan - Ann Arbor · · FY2000 · ENG
Development of machine learning approaches to population pharmacokinetic model selection and evaluation of application to model-based bioequivalence analysis.
$125,000Mark E Sale · Certara Usa, Inc. · U01 · FY2022 · FD