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48,453 grants matching “machine learning”
Temperamental emotionality in preschoolers and depression risk
$748,431Daniel N Klein · State University New York Stony Brook · R01 · FY2021 · MH
** 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 INHABIT A WORLD WHERE DATA ARE UBIQUITOUS. BUSINESSES, GOVERNMENT AGENCIES, AND OTHER PUBLIC AND PRIVATE ENTITIES AND ORGANIZATIONS HARNESS A VARIETY OF DATA SOURCES AND DATA-CENTRIC TOOLS. THESE DATA, AND THE ASSOCIATED TOOLS USED TO ANALYZE THEM, ARE IN TURN USED TO IMPROVE DECISION MAKING AND TO GUIDE THE FORMATION, IMPLEMENTATION, AND PERFORMANCE BENCHMARKING OF STRATEGIC POLICY INITIATIVES. THESE OBSERVATIONS GO FAR IN EXPLAINING THE RAPID GROWTH IN DATA-RELATED JOBS ACROSS ALL SECTORS OF THE GLOBAL ECONOMY. AN IMMEDIATE IMPLICATION IS THERE IS A NEED TO OFFER MORE HANDS-ON, EXPERIENTIAL TRAINING IN DATA SCIENCE TO STUDENTS. SPECIFICALLY, THERE IS A NEED TO OFFER DATA SCIENCE TRAINING TO ANSWER QUESTIONS ACROSS THE FOOD-AGRICULTURAL NEXUS: FROM ENSURING CONTINUED AGRICULTURAL PRODUCTIVITY TO ENSURING THE SAFETY AND AFFORDABILITY OF NUTRITIOUS FOODS TO ENSURING VIBRANT, HEALTHY, AND PROSPEROUS RURAL COMMUNITIES. BY BUILDING ON A RESEARCH, PROJECT-BASED APPROACH TO TEACHING DATASCIENCE METHODS TO A BROAD AND INCLUSIVE SET OF STUDENTS, WE PROPOSE TO LEAD A SUMMER EXPERIENTIAL PROGRAM, DATA ANALYTICS IN COMMUNITY AND RURAL ECONOMICS (DATA-ACRE). OUR PROPOSED PROGRAM FULLY INTEGRATES TRAINING IN DATA SCIENCE METHODS WITH POLICY ISSUES RELEVANT TO AGRICULTURE AND RURAL COMMUNITIES.THE DATA-ACRE INTERNSHIP PROGRAM IS AN IMMERSIVE, TEN-WEEK SUMMER PROGRAM THAT TAKES PLACE ON VIRGINIA TECH'S BLACKSBURG CAMPUS. THE PROGRAM IS LED BY A MULTIDISCIPLINARY TEAM OF FACULTY MEMBERS (I.E., FACULTY MENTORS). THE GOAL OF THE INTERNSHIP IS TO PROVIDE STUDENTS WITH A HANDS-ON, MINDS-ON EXPERIENTIAL LEARNING OPPORTUNITY THAT DEMONSTRATES HOW DISPARATE TYPES AND FORMS OF DATA ARE USED TO INFORM PUBLIC POLICY AND DECISION-MAKING RELEVANT TO AGRICULTURE AND RURAL COMMUNITIES. THE STUDENTS ARE EXPECTED TO FULLY ENGAGE IN THIS TEAM-BASED LEARNING EXERCISE DURING THE ENTIRE TEN-WEEK PROGRAM. THE PROGRAM STARTS BY SPLITTING THE STUDENTS INTO SEVERAL TEAMS. EACH TEAM WORKS ON ONE OR MORE ASSIGNED DATA-INTENSIVE RESEARCH PROJECTS THROUGHOUT THE TEN-WEEK PERIOD. DURING THE FIRST TWO WEEKS, ALL STUDENTS RECEIVE TRAINING IN BASIC DATA SCIENCE METHODS. AFTER THAT, THE TRAINING BECOMES MORE CUSTOMIZED, WITH ADVANCED TOPICS PERTAINING TO USING, FOR EXAMPLE, GIS DATA, WEB SCRAPING, SUPERVISED AND UNSUPERVISED MACHINE LEARNING APPLIED TO STRUCTURED AND UNSTRUCTURED DATA SETS, AND OTHER ADVANCED STATISTICAL METHODS BEING COVERED AS WARRANTED. THE TRAINING WILL BE DELIVERED THROUGH A COMBINATION OF ON-SITE INSTRUCTION BY VIRGINIA TECH (VT) FACULTY MEMBERS. IN ADDITION, THE ON-SITE INSTRUCTION IS SUPPLEMENTED WITH VIRTUAL, SYNCHRONOUS TRAINING COORDINATED WITH THE UNIVERSITY OF VIRGINIA. IN ADDITION, VARIOUS TRAINING MATERIALS (E.G., VIDEOS, HANDOUTS, ETC.) DEVELOPED AS PART OF THE USDA-NIFA-AFRI-006609 FACT: THREE-STATE DATA SCIENCE FOR THE PUBLIC GOOD COORDINATED INNOVATION PROJECT ARE MADE AVAILABLE TO STUDENTS AT THE INTEGRATED DSPG WEB RESOURCE. WHILE THE TRAINING WILLOCCUR DURING THE MORNINGS, THE STUDENT TEAMS WILL BEGIN WORK IN THE AFTERNOONS WITH THEIR GRADUATE STUDENT PEER MENTOR AND FACULTY MENTORS TO DESIGN AND IMPLEMENT THEIR RESEARCH PROJECTS. AT THE END OF TEN WEEKS, THE STUDENTS WILL HAVE WORKED AS PART OF A TEAM TO DESIGN, IMPLEMENT, AND EXECUTE AT LEAST ONE AND USUALLY TWO POLICY-RELEVANT RESEARCH PROJECT(S). EACH TEAM WILL PRESENTS ITS FINDINGS IN A POSTER SESSION AT THE DATA SCIENCE FOR THE PUBLIC GOOD SYMPOSIUM, HELD IN EARLY AUGUST IN ARLINGTON, VIRGINIA.THE DATA-ACRE INTERNSHIP PROGRAM WILL HELP SHAPE THE AGRICULTURAL WORKFORCE IN THREE FUNDAMENTAL WAYS. FIRST, IT WILL HELP US ESTABLISH A PIPELINE OF UNDERSERVED AND UNDERREPRESENTED STUDENTS FROM THE SOCIAL, AGRICULTURAL, AGRIBUSINESS, AND DATA-RELATED SCIENCES FROM OUR NETWORK OF NINE SMALL AND (OR) HBCU AND HSI UNIVERSITIES AND COLLEGES ACROSS THE UNITED STATES. FOR VARIOUS REASONS, THESE STUDENTS MIGHT NOT OTHERWISE HAVE OPPORTUNITIES TO BE EXPOSED TO DATA ANALYTICS METHODS ANDTRAINING. IN THIS WAY, WE WILL INCREASE THE DIVERSITY OF STUDENTS WHO WILL PARTICIPATE IN OUR NOVEL PROGRAM AIMED AT DEVELOPING THE FUTURE AGRICULTURAL AND RURAL COMMUNITY WORKFORCE. SECOND, THE OUR TEAM-BASED, PROJECT-FOCUSED PROGRAM WILL PROVIDE ALL PARTICIPATING UNDERGRADUATE STUDENTS WITH AN OPPORTUNITY TO EXPERIENCE HOW DATA SCIENCE TOOLS ARE APPLIED TO MEANINGFUL RESEARCH PROBLEMS, AND ESPECIALLY PROBLEMS CONFRONTING AGRICULTURE AND RURAL COMMUNITIES. THE HANDS-ON, MINDS-ON APPLIED RESEARCH EXPERIENCES WE OFFER HELP STUDENTS UNDERSTAND HOW TO FORMULATE A RESEARCH QUESTION AND THEN HOW TO OBTAIN, USE, ANALYZE, AND PRESENT DATA TO ADDRESS THE QUESTION. IN ADDITION, THEY DEVELOP THE SKILLS NECESSARY TO SUMMARIZE AND PRESENT THEIR WORK IN MEANINGFUL WAYS TO POLICYMAKERS, DECISION-MAKERS, AND THE PUBLIC. THIRD, THE STUDENT-STAKEHOLDER PROJECT COLLABORATION INVOLVING EXTENSION SPECIALISTS AND OTHER STAKEHOLDERS PROVIDES AN IMPORTANT FORM OF PROFESSIONAL MENTORING FOR THE STUDENT INTERNS. THAT IS, STUDENTS WILL GAIN INSIGHTS INTO POTENTIAL CAREER OPPORTUNITIES IN THE AGRICULTURAL AND PUBLIC POLICY SECTORS.IN SUMMARY, THE SKILLS TAUGHT TO THE STUDENTS INVOLVED WITH THIS PROJECT WILL ADDRESS SUCH THEMES AS THE CREATION AND USE OF OPEN DATA, DATA-DRIVEN DECISION-MAKING FOR THE AGRICULTURAL SECTOR, AND NOTABLY, AGRICULTURAL SCIENCE POLICY LEADERSHIP.
$748,412Virginia Polytechnic Institute & State University · · FY2022 · National Institute of Food and Agriculture
Bridging clinical trial and real-world data via machine learning to advance rheumatoid arthritis treatment strategies
$748,363Katherine Phoenix Liao · Brigham And Women'S Hospital · R01 · FY2022 · AR
** AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** SOIL IS ONE OF OUR MOST VALUABLE RESOURCES, PROVIDING PHYSICAL SUPPORT TO PLANTS, REGULATING DIFFERENT BIOGEOCHEMICAL CYCLES, AND MITIGATING GLOBAL WARMING THROUGH ORGANIC CARBON STOCKS. EMPIRICAL DATA SUGGESTS THAT THE RATE AND MAGNITUDE OF NET C ACCUMULATION IS OFTEN LOWER THAN THE TOTAL AGRICULTURAL INPUT AND WE HAVE YET TO UNDERSTAND HOW ORGANIC C IS STABILIZED IN SOILS. WE PROPOSE, THROUGH A SERIES OF TRANSFORMATIVE EXPERIMENTS, TO QUANTIFY THREE KEY SOIL COMPONENTS: MICROBIOME STRUCTURE (BIOLOGY), ORGANIC MATTER STRUCTURE (CHEMISTRY) AND SOIL AGGREGATE STRUCTURE (PHYSICS), CONSIDERED THE FUNCTIONAL UNIT OF SOIL. THIS RESEARCH WILL BE GUIDED BY THE FOLLOWING SPECIFIC AIMS:T1. SEPARATING AGGREGATES INTO FOUR DIFFERENT CLASSES AND DETERMINE MICROBIAL CARBON USE EFFICIENCY (CUE) IN EACH OF THOSE AGGREGATES USING 18O ISOTOPES.T2. OBTAINING METAGENOMIC SEQUENCING OF MICROBIAL COMMUNITIES AT DIFFERENT AGGREGATE LEVELS AND ESTIMATING LIFE-HISTORY TRAITS ASSOCIATED WITH CUE.T3. CHARACTERIZE C ACCUMULATION AND SOURCES (Δ13C RATIOS) OF SOM FRACTIONS FOR AGGREGATES OF DIFFERENT SIZE CLASSES: DISSOLVED ORGANIC C, MICROBIAL BIOMASS C, MINERAL ASSOCIATED ORGANIC MATTER (OM), OCCLUDED PARTICULATE OM AND FREE PARTICULATE OM.T4. IDENTIFY SPECIFIC DIFFERENCES IN C PROCESS UTILIZATION USING A SUPERVISED MACHINE LEARNING APPROACH.T5. EXPLAIN C STABILIZATION AT THE FIELD SCALE BY INCORPORATING GENOMIC-ENABLED C PROCESSES INTO THE NEXT-GENERATION SOIL C MODEL - THE MILLENNIAL MODEL - TO SIMULATE MICROBIAL GROUP DYNAMICS AND THEIR FUNCTIONAL ROLES.THIS RESEARCH PROPOSAL ADDRESSES THE NIFA-AFRI FOUNDATIONAL PROGRAM: SOIL HEALTH. SPECIFICALLY, THE RESEARCH WILL FUNCTIONALLY CHARACTERIZE SOIL MICROBIOMES, THEIR FUNCTIONAL TRAITS RESPONSIBLE FOR C STABILIZATION AND MODEL THE OUTCOME IN AGRICULTURAL SOILS UNDER DIFFERENT MANAGEMENT PRACTICES.
$748,363University Of California, Davis · · FY2023 · National Institute of Food and Agriculture
DASS: A Framework for Accountable Smart Contract Wills
$748,328Clayton T Morrison · University Of Arizona · · FY2022 · CSE
Research Training in Biomedical Informatics and Data Science at Oregon Health & Science University
$748,296William R Hersh · Oregon Health & Science University · T15 · FY2023 · LM
The Neural Bases of Placebo Effects and their Relation to Regulatory Processes
$748,295Tor Dessart Wager · University Of Colorado · R01 · FY2013 · MH
Understanding and Enhancing Proprioception via Model-Based Human-Robot Interactions
$748,231Jennifer A Semrau · University Of Delaware · · FY2019 · ENG
Deep-Learning Enhanced ASL MRI For Early AD Assessment
$748,215Ze Wang · University Of Maryland Baltimore · R01 · FY2025 · AG
Mitigating Hematologic Adverse Events in Patients with Myeloid Malignancies: A Novel Causal Artificial Intelligence Approach
$748,104Kun-Hsing Yu · Harvard Medical School · R01 · FY2025 · HL
Harnessing Diverse BioInformatic Approaches to Repurpose Drugs for Alzheimers Disease
$748,092Mark W Albers · Massachusetts General Hospital · R01 · FY2021 · AG
Multi-Center Validation and Biologic Assessment of a Novel Pre-Transplant Biomarker Panel to Predict Liver Transplant Recipient Mortality
$748,049Keri Elizabeth Lunsford · Rutgers Biomedical And Health Sciences · R01 · FY2024 · DK
Cellular and Molecular Substrates of Synaptic Plasticity
$747,995Roger A Nicoll · University Of California, San Francisco · R37 · FY2012 · MH
Arrhythmia mapping using electromechanical wave imaging
$747,962Elisa E Konofagou · Columbia University Health Sciences · R01 · FY2024 · HL
Multimethod Examination of Individual and Environmental Factors Associated with Alcohol Use and Behavioral Health Care Disparities Among Racial/Ethnic Minority and Women Veterans
$747,944Jordan P Davis · Rand Corporation · R01 · FY2024 · AA
Reimagining the IMAGINE-TBM trial: Using metagenomics and host transcriptomics to improve our ability to diagnose tuberculous meningitis and assess response to treatment in a randomized clinical trial
$747,881Felicia C. Chow · University Of California, San Francisco · R01 · FY2025 · NS
F-CAP: Functionalization of Variants in Clinically Actionable Pharmacogenes
$747,826Allan Edward Rettie · University Of Washington · R24 · FY2016 · GM
Creating a region- specific biomolecular atlas of the brain of Alzheimerâs disease
$747,773Lingjun Li · University Of Wisconsin-Madison · R01 · FY2024 · AG
Improved Imaging of Fibrosis in Atrial Fibrillation
$747,762Edward Vr Di Bella · University Of Utah · R01 · FY2022 · HL
Improved Imaging of Fibrosis in Atrial Fibrillation
$747,762Edward Vr Di Bella · University Of Utah · R01 · FY2023 · HL
A novel data science and network analysis approach to quantifying facilitators and barriers of low tidal volume ventilation in an international consortium of medical centers
$747,700Curtis H. Weiss · Endeavor Health Clinical Operations · R01 · FY2019 · HL
Real-time spectroscopic photoacoustic/ultrasound (PAUS) scanner withsimultaneous fluence and motion compensation to guide and validateinterventions: system development and preclinical testing.
$747,636Matthew O'Donnell · University Of Washington · R01 · FY2021 · EB
Genetic characterization of atypical parkinsonism
$747,571Sonja Scholz · National Institute Of Neurological Disorders And Stroke · ZIA · FY2017 · NS
Disrupted neural synchrony during naturalistic perception in schizophrenia: Toward a new biomarker of social dysfunction
$747,555Eric Andrew Reavis · University Of California Los Angeles · R01 · FY2024 · MH
Disrupted neural synchrony during naturalistic perception in schizophrenia: Toward a new biomarker of social dysfunction
$747,555Eric Andrew Reavis · University Of California Los Angeles · R01 · FY2025 · MH