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15,895 grants matching “artificial intelligence”
INSiGHTS - Innovative Next Steps in Gaining Health Improvements Through Translational Science
$5,377,354Duane A. Mitchell · University Of Florida · UM1 · FY2025 · TR
UniProt: A Protein Sequence and Function Resource for Biomedical Science
$5,357,980Alex Bateman · European Molecular Biology Laboratory · U24 · FY2024 · HG
Gut Microbiome and Individual Differences in Lumbosacral Radicular Pain
$5,318,433Shiqian Shen · Massachusetts General Hospital · R01 · FY2025 · AT
Bridge2AI: Voice as a Biomarker of Health - Building an ethically sourced, bioaccoustic database to understand disease like never before
$5,302,032Yael Emilie Bensoussan · University Of South Florida · OT2 · FY2023 · OD
Bridge2AI: Cell Maps for AI (CM4AI) Data Generation Project
$5,289,382Trey Ideker · University Of California, San Diego · OT2 · FY2025 · OD
UniProt: A Protein Sequence and Function Resource for Biomedical Science
$5,287,200Alex Bateman · European Molecular Biology Laboratory · U24 · FY2025 · HG
Alliance Central: A platform for sustainable development of next generation genome knowledgebases
$5,241,011Paul Warren Sternberg · California Institute Of Technology · U24 · FY2024 · HG
Bridge2AI: Cell Maps for AI (CM4AI) Data Generation Project
$5,224,537Trey Ideker · University Of California, San Diego · OT2 · FY2025 · OD
Alliance Central: A platform for sustainable development of next generation genome knowledgebases
$5,156,426Paul Warren Sternberg · California Institute Of Technology · U24 · FY2025 · HG
Search for the Structural Basis of Biomacromolecular Function and Activity
$5,154,622Yun Xing M Wang · Division Of Basic Sciences - Nci · ZIA · FY2025 · CA
PIRE: International Program for the Advancement of Neurotechnology (IPAN)
$5,150,000Euisik Yoon · Regents Of The University Of Michigan - Ann Arbor · · FY2015 · O/D
NorthStar Node of the Clinical Trials Network
$5,141,157Gavin Bart · Hennepin Healthcare Research Institute · UG1 · FY2023 · DA
NSF Convergence Accelerator – Track D: Artificial Intelligence and Community Driven Wildland Fire Innovation via a WIFIRE Commons Infrastructure for Data and Model Sharing
$5,138,394Ilkay Altintas · University Of California-San Diego · · FY2021 · TIP
Pharmacokinetics and Drug Metabolism
$5,131,109Xin Xu · National Center For Advancing Translational Sciences · ZIA · FY2024 · TR
NSF Convergence Accelerator Track E: Ocean Vision AI: Scaling up visual observations of life in the ocean using artificial intelligence
$5,035,260Kakani K Young · Monterey Bay Aquarium Research Institute · · FY2022 · TIP
A NATIONAL INFRASTRUCTURE FOR ARTIFICIAL INTELLIGENCE ON THE GRID
$5,000,000Ping Things, Inc. · · FY2019 · Department of Energy
NSF Convergence Accelerator: Track H: Mobility Independence through Accelerated Wheelchair Intelligence
$5,000,000Brenna Argall · Northwestern University · · FY2023 · TIP
NSF Convergence Accelerator Track H: Visit Unknown Places Confidently: Mapping for Access BuiLt Environments (MABLE)
$5,000,000Vinod Namboodiri · Lehigh University · · FY2023 · TIP
NSF Convergence Accelerator Track H: Addressing the Fragmented Information Access Problem - A Community-Driven, AI-Powered Platform for Multimodal Content Creation
$5,000,000Jenna L Gorlewicz · Saint Louis University · · FY2023 · TIP
CSSI: Frameworks: Applying Artificial Intelligence Advances to the Next Generation of Workflow Management on Modern Cyberinfrastructure
$5,000,000Ewa Deelman · University Of Southern California · · FY2025 · CSE
Convergence Accelerator Track J Phase 2: Rapid Detection Technologies and Decision-Support Systems for Safe Food Systems
$5,000,000Mahmoud F Almasri · University Of Missouri-Columbia · · FY2023 · TIP
NSF Convergence Accelerator Track J Phase 2: CropSmart - a digital twin for making wiser cropping decisions nationwide
$5,000,000Liping Di · George Mason University · · FY2023 · TIP
**AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** THIS PROJECT WILL INCREASE FOOD AND NUTRITION SECURITY BY EXPANDING THE CAPACITY OF SMALL BUSINESSES SERVING FOOD DESERTS TO PRODUCE MORE FRESH FOOD. THIRTY-FOUR MILLION AMERICANS ARE FOOD-INSECURE AND 13.5-23.5 MILLION LIVE IN LOW-INCOME, SEGREGATED FOOD DESERTS, WHERE FRESH FOOD IS SCARCE BUT INDUSTRIALLY PRODUCED ULTRAPROCESSED FOODS ARE CHEAP, CONVENIENT, AND UBIQUITOUS. CURRENT EFFORTS TO ADDRESS FOOD DESERTS, AND THEIR NEGATIVE HEALTH AND ENVIRONMENTAL SEQUELAE, OFTEN OVERLOOK SMALL BUSINESSES AS A SOLUTION. THE NOURISH ARTIFICIAL INTELLIGENCE-ENABLED (AI) PLATFORM EMPOWERS SMALL BUSINESSES THROUGH NOVEL, CONVERGENT SOLUTIONS THAT ALLOW SMALL BUSINESS OWNERS TO TAILOR PRODUCTS TO LOCAL PREFERENCES FOR TASTE, CONVENIENCE AND AFFORDABILITY. IT BUILDS ON THE SKILL SETS OF EXISTING, BUT OFTEN UNDER-UTILIZED TALENT, RICH AND DIVERSE FOOD HERITAGES, UNMET DEMAND FOR HEALTHY FOOD, AND THE RELATIVELY LOW START-UP COSTS TO FOUND NEW SMALL BUSINESS AND EXPAND ESTABLISHED ONES. ACCESSED THROUGH PERSONAL COMPUTER OR CELL PHONE APP IN MULTIPLE LANGUAGES, THE USE-INSPIRED NOURISH PLATFORM IS AN INTEGRATIVE SOLUTION THAT EMPOWERS USERS (NEW AND ESTABLISHED SMALL FARMS AND PREPARED FOOD BUSINESSES) TO: 1) OBTAIN PUBLIC AND PRIVATE CAPITAL FOR STARTING OR EXPANDING FRESH FOOD BUSINESSES, 2) EXPLORE MARKET DATA ON THE COMPETITIVE LANDSCAPE, OPTIMAL BUSINESS LOCATIONS, AND CONSUMER PREFERENCES, 3) LEARN THROUGH CURATED BUSINESS TUTORIALS AND A BUSINESS PLAN ASSISTANT, 4) FIND PARTNERS IN LOCAL FRESH FOOD SUPPLY CHAINS THROUGH A SMART FOODSHEDS FEATURE, AND 5) UNDERSTAND AND APPLY FOR LOCALLY REQUIRED BUSINESS LICENSES AND PERMITS. END-USER TESTING BEGINS IN SAN DIEGO COUNTY (URBAN/SUBURBAN) AND RURAL IMPERIAL COUNTY BEFORE TRANSITIONING THE PRODUCT INTO WIDESPREAD PRACTICAL USE, STARTING IN CALIFORNIA.
$5,000,000Regents Of The University Of California, San Francisco, The · · FY2024 · National Institute of Food and Agriculture
** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** BACKGROUND:THE POULTRY INDUSTRY IS THE LARGEST MEAT INDUSTRY IN THE WORLD, AND THE UNITED STATES IS THE WORLD'S NO. 1 PRODUCER OF POULTRY MEAT. THE CONSUMPTION OF CHICKEN PRODUCTS HAS STEADILY INCREASED IN RECENT DECADES, AND THIS DEMAND WILL LIKELY CONTINUE INTO THE FORESEEABLE FUTURE. WHILE THE CURRENT POULTRY INDUSTRY IS CENTRALIZED AND DESIGNED TO PRODUCE FOOD EFFICIENTLY, SEVERAL OPERATIONS SUCH AS MEAT DEBONING RELY HEAVILY ON MANUAL LABOR. THE COVID-19 PANDEMIC DEMONSTRATED THAT THIS RELIANCE ON MANUAL LABOR MAKES THE SYSTEM VULNERABLE TO DISRUPTIONS. MANUFACTURING TASKS IN THESE FACILITIES REQUIRED MANY WORKERS TO STAND SIDE-BY-SIDE, WITHOUT THE ABILITY TO TELEWORK OR OPERATE EQUIPMENT REMOTELY. DURING THE PANDEMIC, THE INFECTION SPREAD QUICKLY AMONG MEAT PROCESSING WORKERS, DISRUPTING THE SUPPLY CHAIN. HIGH HUMAN-FOOD CONTACT CAN ALSO LEAD TO CROSS-CONTAMINATION RESULTING IN FOOD SAFETY RECALLS. THE POULTRY AND MEAT INDUSTRY IS CURRENTLY FACING UNPRECEDENTED CHALLENGES OFLABOR SHORTAGES AND FOOD AND WORKER SAFETY.THE MEAT PROCESSING INDUSTRY STANDS TO BENEFIT BY MORE FULLY EMBRACING TRANSFORMATIVE TECHNICAL PRINCIPLES SUCH AS SENSING, ADVANCED ROBOTICS, AND ARTIFICIAL INTELLIGENCE. THAT SAID, THE CURRENT CAPABILITIES OF ROBOTICS AND AUTOMATION CANNOT YET COMPETE WITH THE DEXTERITY AND FLEXIBILITY OF HUMAN WORKERS. ANIMALS ARE HIGHLY VARIABLE, REQUIRING INTELLIGENT AND ADAPTIVE AUTOMATION TO HANDLE THE SOFT AND VARIABLE MEAT TISSUES. WITH THE U.S. MEAT MANUFACTURING INDUSTRY GRADUALLY RECOVERING FROM THE COVID-19 PANDEMIC, NOW IS THE OPPORTUNE TIME FOR THE MEAT PROCESSING INDUSTRY TO REINVENT ITSELF AND PLAY A MAJOR ROLE IN ADDRESSING GLOBAL PROTEIN NEEDS, INCREASING PROCESSING EFFICIENCY, MINIMIZING MEAT QUALITY LOSS, ALLEVIATING THE PRESSURE OF LABOR FORCE SHORTAGE, PROTECTING WORKER SAFETY, IMPROVING WORKER WELFARE, AND THE WORK ENVIRONMENT.OVERALL GOALS AND OBJECTIVES:THE VISION OF THE CENTER FOR SCALABLE AND INTELLIGENT AUTOMATION IN POULTRY PROCESSING (CSI-APP) IS TO INCORPORATE ADVANCED TECHNOLOGIES IN ROBOTICS, ARTIFICIAL INTELLIGENCE, DIGITAL SENSING, BIOSENSING, AND FOOD SAFETY TO PROVIDE U.S. POULTRY PROCESSING INDUSTRY SCALABLE AND INTELLIGENT SOLUTIONS TO MEET THE RISING NATIONAL AND GLOBAL DEMAND IN POULTRY PRODUCTS. THE LONG-TERM GOAL FOCUSES ON TRANSFORMING CURRENT MASS MANUFACTURING PROTOCOLS IN LARGE, CENTRALIZED PROCESSING PLANTS TO MASS CUSTOMIZATION PROTOCOLS SUITABLE FOR PROCESSING PLANTS IN DIFFERENT SCALES TO OVERCOME THE INHERENT VARIABILITY ASSOCIATED WITH RAW BIOLOGICAL MATERIALS AND HUMANS. LARGE-SCALE INDIVIDUALIZATION CAN BE ACHIEVED ECONOMICALLY THROUGH THE INTEGRATION OF DIGITAL AND PHYSICAL SYSTEMS (INDUSTRY 4.0 PRINCIPLES). IN PURSUIT OF THE VISION AND THE LONG-TERM GOAL, CSI-APP WILL STRATEGICALLY TARGET VALUE CREATION AND TECHNOLOGICAL INNOVATION BY PERFORMING FOCUSED ENGINEERING RESEARCH AND EXTENSION ACTIVITIES BY FOLLOWING FOUR UNIFYING OBJECTIVES IN THIS PROPOSAL:OBJECTIVE 1: SCALABLE POULTRY M,ANUFACTURING. THE TEAM WILL CREATE ASCALABLE PLANT-READY INTELLIGENT ROBOTIC DEBONING SYSTEMCAPABLE OF PERFORMING AT PARITY WITH (OR EVEN EXCEEDING) HUMAN DEBONERS FOR THE MOST SKILLED TASK IN THE PLANT: SHOULDER CUTTING OF FRONT-HALVES. ARTIFICIAL INTELLIGENCE ALGORITHMS WILL BE DEVELOPED TO HANDLE THE HIGH BIOLOGICAL VARIABILITY OF MEAT.OBJECTIVE 2: VIRTUAL REALITY-BASED WORKFORCE TRANSFORMATION. THE LABOR SHORTAGE IS A MAJOR CHALLENGE FOR THE MEAT INDUSTRY. IT TAKES CONSIDERABLE TIME TO TRAIN AN INDIVIDUAL TO PERFORM DEXTEROUS JOBS LIKE MEAT DEBONING. DUE TO HIGH LINE SPEEDS IN A COLD, HUMID ENVIRONMENT, THERE ARE INJURIES RESULTING IN LABOR SHORTAGES. DURING THE PANDEMIC, THE INFECTION SPREAD QUICKLY AMONG MEAT PROCESSING WORKERS, DISRUPTING THE SUPPLY CHAIN. VIRTUAL REALITY CAN TRANSFORM, DIVERSIFY, AND DISTRIBUTE THE WORKFORCE IN SPACE AND TIME. USING THE PROPOSED VR TECHNOLOGY, SOMEONE WILL BE ABLE TO STAY IN A COMFORTABLE ENVIRONMENT AND VIRTUALLY OPERATE A ROBOT TO DEBONE MEAT IN A PROCESSING PLANT REMOTELY. THIS HAS THE POTENTIAL TO REDUCE LABOR SHORTAGE AND CREATE JOB OPPORTUNITIES EVERYWHERE, INCLUDING RURAL AREAS.OBJECTIVE 3: SENSOR AND ROBOTIC-BASED PRODUCT EVALUATION AND BIO-MAPPING FOR ENHANCING FOOD QUALITY AND SAFETY. A MOBILE ROBOTIC PLATFORM CONTAINING BIOSENSORS FOR RAPID ESTIMATION OF BACTERIA WILL BE DEVELOPED. THE BIOSENSORS WILL PROVIDE INITIAL BIOMAPPING OF BACTERIA IN THE PROCESSING PLANT AND IDENTIFY THE BEST AREAS TO COLLECT SWAB SAMPLES OF THE PRODUCT AND ENVIRONMENTAL SURFACES FOR FOOD SAFETY EVALUATIONS. THE FINAL BIOMAP WILL BE USED TO GUIDE SANITATION AND MANAGEMENT DECISIONS. AN IMAGING SYSTEM WILL ALSO BE DEVELOPED FOR DETECTING FOREIGN OBJECTS LIKE SMALL PLASTICS IN MEAT AND FOOD QUALITY EVALUATION.OBJECTIVE 4: RESEARCH AND EXTENSION INTEGRATION: CREATE AN INNOVATION ECOSYSTEM THROUGH TECHNOLOGY DEVELOPMENT/TRANSFER AND WORKFORCE EDUCATION. RESEARCH AND EXTENSION ACTIVITIES WILL BE INTEGRATED, ACCELERATING THE TECHNOLOGY TRANSFORMATION TO BETTER MEET STAKEHOLDERS' NEEDS. PLANNED ACTIVITIES INCLUDE SURVEYS TO IDENTIFY BARRIERS, WORKSHOPS FOR DISSEMINATING INFORMATION ABOUT ADVANCED TECHNOLOGIES, DEMONSTRATION EXHIBITS AT INDUSTRY CONFERENCES, AND ONE-ON-ONE TECHNICAL SUPPORT FOR INDUSTRIES CONSIDERING IMPLEMENTATION OF THESE TECHNOLOGIES.EXPECTED OUTCOMES:CSI-APP IS STRUCTURED TO (1) ENHANCE THE ROBUSTNESS AND SCALABILITY OF PRECISION MANUFACTURING IN MEAT PROCESSING AND CHICKEN DEBONING; (2) DISTRIBUTE THE WORKFORCE IN SPACE AND TIME USING VIRTUAL REALITY SYSTEMS; (3) IMPROVE FOOD QUALITY AND SAFETY IN PROCESSING PLANTS USING INTELLIGENT AUTOMATION, REAL-TIME VISION SENSING, BIOSENSING AND BIOMAPPING; AND (4) COLLECT STAKEHOLDER FEEDBACK OF DIGITALIZATION TRANSFORMATION IN THE MEAT INDUSTRY AND DISSEMINATE THE TECHNOLOGY TO THE STAKEHOLDERS. THIS CONTRIBUTION WILL BE SIGNIFICANT BECAUSE IT IS EXPECTED TO TRANSFORM THE POULTRY INDUSTRY TO A MORE DIGITIZED AND AUTOMATED INDUSTRY, WITH ENHANCED LABOR SAFETYA,ND FOOD QUALITY/SAFETY. THE SCALABLE AND TRANSFERRABLE TECHNOLOGY IS EXPECTED TO BE ADAPTABLE TO SMALLER CHICKEN PROCESSORS, WHICH IS BENEFICIAL FOR THE ECONOMIC DEVELOPMENT OF RURAL AREAS. A DISTRIBUTED NETWORK OF SMALLER PRODUCERS/PROCESSORS THAT CAN ALSO SUPPLY CHICKENS TO LOCAL CLIENTS EFFICIENTLY TO PROTECT THE FOOD SUPPLY FROM AGGRESSIVE ATTACKS AND THE SPREAD OF PATHOGENS. ON FUNDAMENTAL, APPLIED, AND EXTENSION LEVELS, THE LONG-TERM OUTCOMES OF CSI-APP CAN BE ADAPTED TO ALLIED FOOD INDUSTRIES BENEFITING THE U.S. AND GLOBAL ECONOMY, BUT THE POTENTIAL IMPACT OF CSI-APP GOES FAR BEYOND THIS. MAKING THE MASS CUSTOMIZATION OF PROTEIN MANUFACTURING A REALITY WILL CONTRIBUTE TO LONG-TERM ENVIRONMENTAL SUSTAINABILITY IN FOOD PRODUCTION AND TO WELL-BEING AROUND THE WORLD BY PROVIDING A SAFE AND AFFORDABLE SOURCE OF PROTEIN.PROJECT TEAM:CSI-APP CONNECTS FOUR CORE INSTITUTES: UNIVERSITY OF ARKANSAS SYSTEM DIVISION OF AGRICULTURE, GEORGIA TECH RESEARCH INSTITUTE, UNIVERSITY OF NEBRASKA-LINCOLN, AND FORT VALLEY STATE UNIVERSITY, ALONG WITH A KEY COLLABORATOR FROM USDA ARS NATIONAL POULTRY RESEARCH CENTER. AN INTERDISCIPLINARY TEAM FROM THE FOUR INSTITUTIONS AIMS TO UNCOVER THE ENGINEERING AND TECHNOLOGIES TO ENABLE SCALABLE, INTELLIGENT, EFFICIENT, SAFE, AND TRANSFORMABLE MEAT MANUFACTURING SYSTEMS TO ENHANCE WORKER SAFETY, FOOD SAFETY AND PROCESS EFFICIENCY. CSI-APP'S INDUSTRIAL BOARD CONSISTS OF 12 REPRESENTATIVE STAKEHOLDERS RELATED TO THE PROJECT FROM (1) POULTRY COMPANIES IN LARGE, MEDIUM, AND SMALL SIZES; (2) FOOD MANUFACTURING AND AUTOMATION COMPANIES; AND (3) INDUSTRY ASSOCIATIONSWITH BACKGROUNDS SPANNING POULTRY PRODUCTION, POULTRY PROCESSING, FOOD TECHNOLOGIES, AND INTELLIGENT FOOD SYSTEM DEVELOPMENT.
$5,000,000Division Of Agriculture Of The University Of Arkansas · · FY2023 · National Institute of Food and Agriculture
BioData Catalyst Data Management Core Program
$5,000,000Bruce Siege · Research Triangle Institute · OT2 · FY2025 · HL