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48,453 grants matching “machine learning”
Collaborative Research: RI: Medium: A Rigorous, General Framework for Tractable Learning of Large-Scale DAGs from Data
$799,933Pradeep K Ravikumar · Carnegie Mellon University · · FY2020 · CSE
SBIR Phase II: Development of An Accurate Low-Cost Wearable Ultraviolet Dosimeter For The General Population
$799,923Emmanuel Dumont · Youv Labs · · FY2020 · TIP
SLES: Whitebox Testing, Debugging, and Repairing for Multi-module Autonomous Vehicles in Near-Collision Traffic Scenarios
$799,921Tianyi Zhang · Purdue University · · FY2024 · CSE
A Preclinical Program for Targeting Mycobacterium tuberculosis KasA
$799,834Joel Stephen Freundlich · Rutgers Biomedical And Health Sciences · R01 · FY2023 · AI
** 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 USDA SPENDS BILLIONS OF DOLLARS PER YEAR ON CONSERVATION TO ENHANCE ENVIRONMENTAL QUALITY, ECOSYSTEM SERVICES AND AGRICULTURAL SUSTAINABILITY. THE BIOPHYSICAL IMPACTS OF THESE PROGRAMS (E.G., ON SOIL RETENTION AND WATER QUALITY) ARE RELATIVELY WELL UNDERSTOOD AND CAN BE ESTIMATED USING STANDARD MODELING APPROACHES. YET THE ECONOMIC BENEFITS OF THESE PROGRAMS REMAIN LARGELY UNKNOWN, AND CREDIBLE INFORMATION ON NON-MARKET BENEFITS IS PARTICULARLY LACKING. DESPITE AN EXTENSIVE LITERATURE ON NON-MARKET VALUATION, THE METHODS FROM THIS LITERATURE ARE OFTEN IMPRACTICAL TO USE FOR THE ESTIMATION OF VALUES PROVIDED BY USDA AND OTHER CONSERVATION PROGRAMS. LARGE-SCALE, APPLIED VALUATION OF THIS TYPE ALMOST UNIVERSALLY REQUIRES BENEFIT TRANSFER, OR BT. BT USES EXISTING ECONOMIC VALUE ESTIMATES FROM PRIOR STUDIES AT ONE OR MORE LOCATIONS TO PREDICT ECONOMIC VALUE ESTIMATES SUCH AS WILLINGNESS TO PAY (WTP) AT OTHER, TYPICALLY UNSTUDIED LOCATIONS. BENEFIT TRANSFER CAN PRODUCE ECONOMIC VALUE ESTIMATES FOR AREAS AND ECOSYSTEM SERVICE IMPROVEMENTS FOR WHICH ORIGINAL ECONOMIC VALUATION STUDIES HAVE NOT BEEN CONDUCTED--THEREBY QUANTIFYING THE ECONOMIC VALUE OF LARGE-SCALE AGRICULTURAL CONSERVATION TO THE PUBLIC. YET BT METHODS TO SUPPORT RELIABLE LARGE-SCALE VALUATION ARE INADEQUATELY DEVELOPED, PARTICULARLY FOR APPLICATIONS SUCH AS RESOURCE CONSERVATION AND WATER QUALITY IMPROVEMENTS WITH WIDESPREAD, DIFFUSE AND PATCHY IMPACTS. DUE TO THE LACK OF SUFFICIENTLY ACCURATE BT METHODS, USDA AND ITS PARTNERS STRUGGLE TO PRODUCE CREDIBLE ESTIMATES OF NON-MARKET CONSERVATION BENEFITS.ADDRESSING THIS UNRESOLVED RESEARCH AND POLICY NEED REQUIRES A SET OF FLEXIBLE, STANDARDIZED BT APPROACHES THAT ARE ABLE TO PREDICT BENEFITS FOR THE LARGE SPATIAL SCALES OVER WHICH CONSERVATION OCCURS, WHILE SIMULTANEOUSLY ACCOUNTING FOR THE IMPORTANT EFFECTS OF LOCALIZED, PLACE-SPECIFIC SPATIAL AND OTHER DIMENSIONS ON VALUES FOR ENVIRONMENTAL IMPROVEMENTS. RESPONDING TO THIS IMPORTANT GAP IN KNOWLEDGE AND METHODS FOR ECONOMIC ANALYSIS, THE PRESENT PROJECT WILL DEVELOP AND EVALUATE BT PROCEDURES WITH A PREVIOUSLY UNATTAINABLE CAPACITY TO ACCOUNT FOR LOCALIZED SPATIAL HETEROGENEITY OF CONSERVATION-RELATED ENVIRONMENTAL IMPROVEMENTS OVER LARGE SPATIAL SCALES (SUCH AS WATER QUALITY IMPROVEMENTS), WHILE IDENTIFYING AREAS WHEREIN IMPROVEMENTS ARE MOST VALUED BY TARGET POPULATIONS, INCLUDING DISADVANTAGED COMMUNITIES. ALTHOUGH APPLICABLE TO ANY CONSERVATION OUTCOME, METHODS WILL BE ILLUSTRATED FOR BTS THAT PREDICT WILLINGNESS TO PAY (WTP) FOR SPATIALLY DIFFUSE WATER QUALITY IMPROVEMENTS.THE PROJECT ADDRESSES USDA AFRI ENVIRONMENTAL AND NATURAL RESOURCE ECONOMICS (A1651) PROGRAM PRIORITIES, WHICH CALL FOR BENEFIT TRANSFER TO INFORM BENEFIT-COST CALCULATIONS FOR CONSERVATION AND NATURAL RESOURCE POLICY DESIGN AND IMPLEMENTATION. THESE NOVEL METHODS WILL INTEGRATE (1) LOCALLY WEIGHTED META-REGRESSION MODELS (LW MRMS) FOR WTP METADATA THAT PRODUCE UNIQUE BENEFIT FUNCTIONS FOR EACH SITE, (2) INTERAC,TIVE MAP-BASED SURVEY ARCHITECTURE THAT IDENTIFIES HIGHLY VALUED (SALIENT) AREAS NATIONWIDE FOR SPECIFIC ENVIRONMENTAL IMPROVEMENTS, (3) A MACHINE-LEARNING SPATIAL SALIENCE CLASSIFICATION MODEL (SCM) THAT USES THESE SURVEY DATA TO PROVIDE GENERALIZABLE PREDICTIONS, FOR ANY CENSUS BLOCK GROUP (CBG) NATIONWIDE, ON THE DEGREE TO WHICH ANY POTENTIAL WATERSHED AREA IS SALIENT (OR PARTICULARLY IMPORTANT) TO RESIDENTS FOR WATER QUALITY IMPROVEMENTS, AND (4) VALIDATED METADATA ON HOUSEHOLD WTP FOR WATER QUALITY IMPROVEMENTS IN US WATERBODIES DRAWN FROM PRIOR STUDIES IN THE VALUATION LITERATURE, AUGMENTED WITH SCM RESULTS TO SUPPORT LW MRMS WITH ENHANCED WTP-PREDICTION ACCURACY. THE PROJECT WILL PROVIDE TRANSFORMATIVE YET STANDARDIZED BT METHODS ABLE TO PREDICT VALUES DUE TO DIFFUSE CONSERVATION OVER LARGE SCALES, TOGETHER WITH A SET OF NATIONWIDE SPATIAL SALIENCE DATA LAYERS THAT CAN BE USED INDEPENDENTLY TO IDENTIFY AREAS WHEREIN WATER QUALITY IMPROVEMENTS ARE MOST VALUED BY RESIDENTS OF ANY CBG. THESE METHODS WILL ENHANCE THE ACCURACY OF LARGE-SCALE BT, BY INCORPORATING SYSTEMATIC INFORMATION ON THE EXTENT TO WHICH PATCHY ENVIRONMENTAL IMPROVEMENTS OCCUR IN LOCAL (OR NON-LOCAL) AREAS THAT ARE IMPORTANT (OR SALIENT) TO HOUSEHOLDS. IN DOING SO, THESE APPROACHES WILL INCREASE THE CAPACITY OF USDA AND OTHERS TO QUANTIFY THE ECONOMIC VALUES GENERATED BY AGRICULTURAL CONSERVATION PROGRAMS.
$799,772Trustees Of Clark University · · FY2024 · National Institute of Food and Agriculture
Testing the Bottom-Up vs Top-Down Imbalance Hypothesis of ASD
$799,760Tal Kenet · Massachusetts General Hospital · R01 · FY2019 · MH
QUANTUM-INSPIRED BAYESIAN SAMPLING FOR UNCERTAINTY QUANTIFICATION AND MACHINE LEARNING
$799,740University Of California, Santa Barbara · · FY2020 · Department of Energy
Circulating Biomarkers and Imaging for Early Detection of Pancreatic Cancer
$799,728Subrata Sen · University Of Tx Md Anderson Can Ctr · U01 · FY2024 · CA
Neural Mechanisms of Social Attribution from Faces
$799,720Josef Parvizi · Stanford University · R01 · FY2024 · MH
National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA): San Diego Research Project Site
$799,619Susan F Tapert · University Of California, San Diego · U01 · FY2023 · AA
Integrative analysis of multi-omic signatures and cellular function in human pancreas across developmental timeline at single-cell spatial resolution
$799,570Marcela Brissova · Vanderbilt University Medical Center · U01 · FY2025 · DK
Investigating and identifying the heterogeneity in COVID-19 misinformation exposure on social media among Black and Rural communities to inform precision public health messaging
$799,507Sharath Chandra Guntuku · University Of Pennsylvania · R01 · FY2022 · MD
Regulatory landscape of the human genome: comparative and evolutionary analysis.
$799,484Ivan Ovcharenko · National Library Of Medicine · ZIA · FY2011 · LM
Advancing Maryland's Statewide Suicide Data Warehouse to Improve Individual and Population-level Mortality Prediction and Prevention
$799,385Hadi Kharrazi · Johns Hopkins University · R01 · FY2021 · MH
CAREER: The Mechanistic Roles of Receptor Oligomerization in Molecular Signaling
$799,246Colin D Kinz-Thompson · Rutgers University Newark · · FY2025 · MPS
Natural language processing for precision medicine and clinical and consumer health question
$799,199Dina Demner-Fushman · National Library Of Medicine · ZIA · FY2020 · LM
Cardiovascular risk from comprehensive evaluation of the CT calcium score exam
$799,168David L Wilson · Case Western Reserve University · R01 · FY2023 · HL
Partnership for Research and Education in Soft Matter Research & Technology and Quantum Confinement Materials Design (SMaRT QD)
$799,058Cherese Winstead · Delaware State University · · FY2021 · MPS
Collaborative Research: SaTC: CORE: Medium: Defending against Emerging Stateless Web Tracking
$799,030Alexandros Kapravelos · North Carolina State University · · FY2022 · CSE
Leveraging Machine Learning Approaches to Understand Mechanisms of Exposure Therapy in Real-World Settings
$798,987Jennie M Kuckertz · Mclean Hospital · R01 · FY2024 · MH
Scaling Volumetric Imaging, Analysis and Science Communication Using Immersive Virtual Reality
$798,921Michael David Morehead · Istovisr · R44 · FY2023 · MH
Contributions of spared brain structures and connections to aphasia recovery
$798,921Peter Ethan Turkeltaub · Georgetown University · R01 · FY2017 · DC
CCRI: ENS: Collaborative Research: Developing the Dialog Ecosystem to Support and Enhance Research in Spoken Dialog Systems
$798,909David R Traum · University Of Southern California · · FY2019 · CSE
Interpretable machine learning to synergize brain age estimation and neuroimaging genetics
$798,863Andrei Irimia · University Of Southern California · R01 · FY2024 · AG
Toward Diagnostics and Therapies of Molecular Subcategories of CAD
$798,847Johan M Bjorkegren · Icahn School Of Medicine At Mount Sinai · R01 · FY2018 · HL