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15,895 grants matching “artificial intelligence”
Support System for Subcutaneous Insulin Delivery System
$10,642University Of California Los Angeles · M01 · FY2004 · RR
Collaborative Research: EAGER: SaTC-EDU: Secure and Privacy-Preserving Adaptive Artificial Intelligence Curriculum Development for Cybersecurity
$10,626Lin L Lipsmeyer · Southern Methodist University · · FY2023 · EDU
Collaborative Research: Conference: STEM Learning for the Construction Industries of the Future
$10,616Sanjeev Adhikari · Kennesaw State University Research And Service Foundation · · FY2025 · EDU
Image-based models of tumor-immune dynamics in glioblastoma
$10,574Kristin R Swanson · Mayo Clinic Arizona · U01 · FY2023 · CA
2015 Association for Computational Linquistics (ACL) Student Research Workshop
$10,500Emily M Bender · University Of Washington · · FY2015 · CSE
Collaborative Research: NSF2026: EAGER: A Playground and Proposal for Growing an AGI.
$10,455Joshua K Hartshorne · Mgh Institute Of Health Professions · · FY2024 · CSE
WORKSHOP ON TRUSTED ARTIFICIAL INTELLIGENCE
$10,425Universidad Adolfo Ibanez · · FY2024 · Department of the Navy
WORKSHOP: Student Consortium at the 2013 ACM Conference on Intelligent User Interfaces
$10,368Henry Lieberman · Massachusetts Institute Of Technology · · FY2013 · CSE
Data to Design: An Integrated Approach to Developing New Synthetic Methods
$10,242Rajat Maji · University Of California Los Angeles · K99 · FY2025 · GM
Creating the First International Probabilistic Planning Competition
$10,232Michael L Littman · Rutgers University New Brunswick · · FY2003 · CSE
NMR TECHNOLOGY FOR STRUCTURAL GENOMICS OF BREAST CANCER
$10,144Harvard University (Medical School) · F32 · FY2003 · CA
THE OVERARCHING GOAL OF THIS RESEARCH IS TO DEVELOP A DEEP-LEARNING FRAMEWORK FOR THE AUTOMATED SELECTION OF OPTIMAL SOIL SAMPLING SITES BASED ON LANDSCAPE POSITION. SOIL SAMPLING IS ONE OF THE MOST FUNDAMENTAL PROCESSES IN AGRICULTURE: IT IS THE CRUCIAL FIRST STEP IN SOIL TESTING TO DETERMINE SOIL HEALTH. A SOIL ANALYSIS, WHICH PROVIDES INFORMATION IMPORTANT TO MAXIMIZE NUTRIENT USE EFFICIENCY AND AGRICULTURAL PRODUCTIVITY, CAN ONLY BE AS GOOD AS THE SAMPLES SENT TO THE LAB. GOOD SAMPLES REQUIRE SAMPLING AT MULTIPLE OPTIMAL SITES IN THE FIELD. IN THE CURRENT PRACTICE, FARMERS COLLECT AND POOL SAMPLES THEMSELVES AND SEND THEM TO A LAB FOR ANALYSIS. THERE ARE SCIENTIFIC METHODS WHERE SAMPLES CAN BE POOLED BASED ON LANDSCAPE POSITION AND KNOWLEDGE ABOUT HOW NUTRIENTS MOVE IN SOIL DUE TO DIFFERENCES IN PROPERTIES. HOWEVER, MOST PRODUCERS DO NOT FOLLOW THOSE PROCEDURES AS THEY CAN BE COMPLEX AND VARY FROM FIELD TO FIELD. POOLED SOIL SAMPLES DO NOT REPRESENT THE ACTUAL VARIATION IN SOIL PROPERTIES. PRODUCERS CAN PULL MULTIPLE SOIL SAMPLES BUT HAVE NO ASSURANCE OF THE EXTENT OF THEIR FIELDS WHICH EACH SAMPLE ACTUALLY REPRESENTS. AS A RESULT, THERE ARE NO RELIABLE METHODS FOR FARMERS TO ACCURATELY UTILIZE KNOWLEDGE OF SOIL VARIATION WITH THEIR PRECISION AGRICULTURE TECHNOLOGIES. THERE IS AN URGENT NEED FOR AN AUTOMATED TOOL THAT WILL HELP PRODUCERS IDENTIFY WHICH SPOTS ARE OPTIMAL FOR SAMPLING AND CAN BE POOLED TO GET ACCURATE SOIL ANALYSIS RESULTS.TO FILL THIS CRITICAL NEED, WE AIM TO DEVELOP A DEEP-LEARNING TOOL THAT OUTPUTS LANDSCAPE ZONES WITH POSITION ELEVATION AND IDENTIFIES OPTIMAL SAMPLING SPOTS FOR EACH ZONE. THE TRAINING LANDSCAPE DATA AND SCIENTIFIC METHODOLOGY WILL BE PROVIDED BY THE SOIL PEDOLOGIST CO-PI. THE ARTIFICIAL INTELLIGENCE (AI) -ENABLED TOOL WILL BE DEVELOPED WITH GPS GUIDANCE TO GO FROM SPOT TO SPOT. IT WILL ALSO ALLOW FOR THE MIXING OF APPROPRIATE SAMPLES AND PROVIDE INFORMATION ON THE ESTIMATED COST OF ANALYSIS. IF THE PRODUCER CHOOSES A PRICE CAP, THE TOOL COULD INFORM THEM OF THE NUMBER OF SAMPLES THAT COULD BE ANALYZED WITHIN THAT PRICE RANGE AND HOW ACCURATE THE RESULTS WOULD BE.OUR CENTRAL HYPOTHESIS IS THAT THE USE OF ADVANCED DEEP-LEARNING TECHNIQUES TO ANALYZE AND REFINE LANDSCAPE DATA WILL ENABLE PRECISE AND RELIABLE RECOMMENDATIONS OF OPTIMAL SOIL SAMPLING SPOTS. IN ADDITION, THE FRAMEWORK WILL PRODUCE CONSISTENT RESULTS UNDER THE UNCERTAIN VARIABLE CONDITIONS FROM FIELD TO FIELD. THE RATIONALE IS THAT DEEP LEARNING EXTRACTS MEANINGS FROM LANDSCAPE DATA AND HUMAN-LABELED DATA TO TRAIN MULTI-LAYER NEURAL NETWORKS TO INCREASE THE RELIABILITY AND ACCURACY OF SAMPLING LOCATION SELECTION. OUR TEAM IS PARTICULARLY WELL PREPARED TO UNDERTAKE THE PROPOSED RESEARCH BECAUSE OF OUR EXTENSIVE AND SUCCESSFUL TRACK RECORD OF AI-ENABLED AND DATA-DRIVEN RESEARCH IN PRECISION AGRICULTURE AND SOIL-LANDSCAPE ANALYSIS.WE PLAN TO TEST THE CENTRAL HYPOTHESIS BY PURSUING THE FOLLOWING THREE SPECIFIC OBJECTIVES:ESTABLISH A CYBERINFRASTRUCTURE OF LANDSCAPE DATA AND SOIL SAMPLING ANNOTATIONS TO TRAIN DEEP CONVOLUTIONAL NEURAL NETWORKS.DEVELOP A DEEP-LEARNING PIPELINE TO LEARN, ANALYZE, AND REFINE LANDSCAPE DATA FOR AUTOMATED SELECTION OF SOIL SAMPLING LOCATIONS. THE FRAMEWORK TAKES LANDSCAPE DATA AS INPUT AND OUTPUTS OPTIMAL SOIL SAMPLING SPOTS.DESIGN AND IMPLEMENT A SET OF METRICS TO ASSESS THE SUCCESS RATE OF THE OPTIMAL SAMPLING SITE PREDICTION TOOL.THE PROPOSED RESEARCH IS ORIGINAL AND TRANSFORMATIVE BECAUSE IT WILL CREATE AN ADVANCED TOOL FOR A CRUCIAL AND CHALLENGING PRECISION AGRICULTURE PROBLEM, NAMELY AUTOMATED AND RELIABLE SELECTION OF SOIL SAMPLING SITES. THIS TOOL IS CURRENTLY MISSING, AND IT WILL ENABLE A SIGNIFICANT IMPROVEMENT IN SOIL SAMPLING AND ANALYSIS, WHICH WILL LEAD TO A BETTER UNDERSTANDING OF SOIL HEALTH. IT WILL LAY A FOUNDATION FOR NOVEL APPLICATIONS OF DATA SCIENCE AND AI TECHNOLOGIES TO SOLVE AGRICULTURAL PROBLEMS.
$10,080South Dakota State University · · FY2022 · National Institute of Food and Agriculture
Mobile bedside ultrasound for the diagnosis of pediatric pneumonia in resource limited settings
$10,065Christopher J Gill · Boston University Medical Campus · R21 · FY2020 · TW
RI: Student Travel Support for the 2015 International Conference on Case-Based Reasoning; September 28-30, 2015; Frankfurt, Germany
$10,000David C Wilson · University Of North Carolina At Charlotte · · FY2015 · CSE
Symposium on Combinatorial Search - 2017
$10,000Nathan Sturtevant · University Of Denver · · FY2017 · CSE
Medical Image Perception Society (MIPS) XX
$10,000Elizabeth A Krupinski · Emory University · R13 · FY2024 · EB
I/UCRC Center for Safety, Security and Rescue Robotics (C-SSRR)
$10,000Robin R Murphy · University Of South Florida · · FY2003 · ENG
RI: Doctoral Student Consortium at the Twenty Fourth International Conference on Case-Based Reasoning
$10,000Ashok K Goel · Georgia Tech Research Corporation · · FY2016 · CSE
Travel: Student Travel Support for MVAPICH User Group (MUG) 2025 Conference
$10,000Dhabaleswar K Panda · Ohio State University, The · · FY2025 · CSE
The 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016; October 10-14, 2016 in Marriott Marquis, San Francisco
$10,000Lauren Tompkins · Stanford University · · FY2016 · MPS
NSF Student Travel Grant for the International Workshop on Bio-Design Automation (IWBDA)
$10,000Natasa Miskov-Zivanov · University Of Pittsburgh · · FY2025 · CSE
"CSP 101038" "PRICAI 2010: THE 11TH PACIFIC RIM INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, DATED 2 MAR 10" (THE GRANTEE'S TECHNICAL PROPOSA
$10,000Kyungpook National University · · FY2010 · Department of the Air Force
Individual: Fueling the STEM Pipeline by Mentoring Across the Age Span
$10,000Maja Matarić · University Of Southern California · · FY2011 · EDU
IEEE Medical Imaging Conference
$10,000Georges El Fakhri · Massachusetts General Hospital · R13 · FY2021 · EB
WORKSHOP: ARTIFICIAL INTELLIGENCE FOR WEATHER AND CLIMATE MODELLING
$10,000University Of Oxford · · FY2019 · Department of the Navy