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48,453 grants matching “machine learning”
High-dimensional statistical learning and inference
$920,001Jianqing Fan · Princeton University · · FY2007 · MPS
Collaborative Research: DMREF: Accelerated Discovery of Perovskite Nanomaterials Using Distributed Self-Driving Labs
$920,000Milad Abolhasani · North Carolina State University · · FY2025 · MPS
Liquid Biopsy in Glioblastoma Treated with Chemoradiation and an Oxygen Therapeutic
$919,366Evan Charles Unger · Nuvox Pharma, Llc · R44 · FY2025 · CA
BIGDATA: F: Learning Big Bayesian Networks
$919,305Qing Zhou · University Of California-Los Angeles · · FY2015 · CSE
BandPass: A Remote Monitoring System for Sarcopenia and Functional Decline
$919,218Ryan Joseph Halter · Synchrohealth Llc · R42 · FY2023 · AG
Causal Representation Learning for the Spatial Analysis of Transcriptomic and Imaging Data in Tissue Contexts
$919,200Caroline Uhler · Broad Institute, Inc. · DP2 · FY2025 · AT
Towards Clinically Effective AI for Screening Mammography
$919,121William Edward Lotter · Deephealth, Inc. · R44 · FY2020 · CA
The Role of Emotion in Propelling the SMET Process
$918,883Rosalind W Picard · Massachusetts Institute Of Technology · · FY2000 · EDU
Automatic, Opportunistic Surveillance of Hip Bone Fragility in X-ray Images
$918,848Ashkan Vaziri · Biosensics, Llc · R44 · FY2024 · AG
Systems Immunology of COVID-19
$918,148John Tsang · National Institute Of Allergy And Infectious Diseases · ZIA · FY2020 · AI
Creating adaptive, wearable technologies to assess and intervene for individuals with ADRDs
$918,000Diane Joyce Cook · Washington State University · R35 · FY2021 · AG
A data science approach to identify and manage Multisystem Inflammatory Syndrome in Children (MIS-C) associated with SARS-CoV-2 infection and Kawasaki disease in pediatric patients
$917,957Cedric Manlhiot · Johns Hopkins University · R61 · FY2021 · HD
MATH-DT: Scalable Bayesian Online Learning for Digital Twins in Power Network Resilience against Sequential Extreme Events
$917,946Luis A Ceferino · University Of California-Berkeley · · FY2025 · ENG
ClinGen Genome Resource (ClinGen) Resource Project
$917,818Carlos D. Bustamante · Stanford University · U41 · FY2017 · HG
Statistical genetics of aging-related genomic and phenotypic change
$917,721Jun Ding · National Institute On Aging · ZIA · FY2023 · AG
Reconstructing HIV Epidemics from HIV Phylogenetics
$917,615Thomas K. Leitner · Triad National Security, Llc · R01 · FY2021 · AI
Reconstructing HIV Epidemics from HIV Phylogenetics
$917,615Thomas K. Leitner · Triad National Security, Llc · R01 · FY2022 · AI
Novel whole-genome analysis methods for Alzheimer's risk prediction
$917,300Ellen McRae Greytak · Parabon Nanolabs, Inc. · R44 · FY2023 · AG
Using Structured Light Sensing with Machine Learning to Detect Unwitnessed In-Home Falls
$916,985Paul Gibson · Applied Universal Dynamics Corporation · R44 · FY2024 · AG
TO IMAGE POTENTIALLY HABITABLE EXOPLANETS AND ACQUIRE SPECTRA OF THEIR ATMOSPHERES OR SURFACES IMAGING SYSTEMS MUST BE CAPABLE OF OPERATING AT HIGH CONTRAST WHERE CONTRAST IS DEFINED AS THE RATIO OF STELLAR BRIGHTNESS TO PLANETARY BRIGHTNESS. THE AMOUNT OF STARLIGHT DIFFRACTED INTO THE SCIENCE PIXELS CALLED STRAY LIGHT MUST BE MINIMIZED BY COMBINING CORONAGRAPHY AND WAVEFRONT CONTROL TECHNIQUES. IT CAN BE REMOVED BY ACTIVELY CONTROLLING THE DIFFRACTION PATTERN WITH A DEFORMABLE MIRROR REQUIRING ESTIMATION OF ITS AMPLITUDE AND PHASE VIA A WAVEFRONT SENSING PROCEDURE. THE FRACTION OF THE STAY LIGHT THAT CAN BE REMOVED IN THIS WAY DEPENDS ON THE EFFICIENCY OF THIS WAVEFRONT SENSING STEP. EVEN THIS PROCEDURE FOR ACTIVELY REMOVING STRAY LIGHT MAY NOT BE ADEQUATE SO BACKGROUND SUBTRACTION TECHNIQUES ARE EMPLOYED IN A POST-PROCESSING STEP THAT IDENTIFIES AND REMOVES SOME OF THE REMAINING STRAY LIGHT. THE RESULTING DETECTION LIMIT CONTRAST (THE AUGMENTED CONTRAST) MUST BE WELL BELOW THE PLANETS FLUX LEVEL. AT THE ~1E10 (STAR-TO-PLANET) FLUX-RATIO CHARACTERISTIC OF POTENTIALLY HABITABLE EXOPLANETS AROUND SUN-LIKE STARS ACHIEVING THE REQUIRED RAW AND AUGMENTED CONTRAST LEVELS IS EXTREMELY CHALLENGING. WE WILL ENHANCE WAVEFRONT ESTIMATION AND INTEGRATE IT WITH IMAGE POST-PROCESSING IMPROVING BOTH RAW AND AUGMENTED CONTRASTS. THE NEW FRAMEWORK WILL DELIVER WELL-CALIBRATED SCIENCE IMAGES UTILIZING THE PROPERTY THAT MOST OF THE STRAY LIGHT THAT CURRENTLY LIMITS DETECTIONS CAN BE RECONSTRUCTED FROM WAVEFRONT SENSING MEASUREMENTS. OUR APPROACH RELIES ON THREE RELATED TECHNIQUES: [1] COHERENT DIFFERENTIAL IMAGING (CDI) WILL IDENTIFY IN THE CORONAGRAPHIC IMAGE THE COHERENT (STARLIGHT) AND INCOHERENT (PLANET LIGHT) COMPONENTS. THE MEASUREMENT RELYING ON COHERENT MIXING WITH REFERENCE STARLIGHT WAS PREVIOUSLY DEVELOPED FOR WAVEFRONT CONTROL. WE WILL OPTIMIZE IT FOR CONTRAST AUGMENTATION AND DEVELOP THE ASSOCIATED PROCESSING ALGORITHMS. [2] PREDICTIVE CONTROL (PC) WILL OPTIMALLY COMBINE PAST WAVEFRONT MEASUREMENTS TO IMPROVE BOTH WAVEFRONT CORRECTION AND STRAY LIGHT ESTIMATION. [3] SENSOR FUSION (SF) WILL COMBINE MEASUREMENTS FROM MULTIPLE SENSORS (SUCH AS FOCAL PLANE IMAGES CORONAGRAPHIC LOW-ORDER WAVEFRONT SENSOR AND PUPIL PLANE SENSORS) TO ESTIMATE THE WAVEFRONT STATE AND THE CORRESPONDING RESIDUAL STARLIGHT IMAGE COMPONENT. TOGETHER PC AND SF WILL INCREASE THE EFFICIENCY SENSITIVITY AND RELIABILITY OF WAVEFRONT SENSING FOR HIGH CONTRAST IMAGING SPACE MISSIONS (TECHNOLOGY GAPS CG-5 CG-7) AND MITIGATE WAVEFRONT CONTROL CHALLENGES ASSOCIATED WITH LARGE SEGMENTED APERTURES (CG-6). THE CDI APPROACH TOGETHER WITH NOISE ESTIMATION FROM PC AND SF WILL PROVIDE THE REAL-TIME IMAGE CALIBRATION MAKING USE OF STRAY LIGHT INFORMATION CONTAINED IN THE WAVEFRONT SENSING TELEMETRY (CG-4). IN PARALLEL TO NUMERICAL DEVELOPMENT AND FOCUSED TESTBED EXPLORATIONS AT NASA AMES UNIVERSITY OF ARIZONA AND JPL WE WILL INTEGRATE THE APPROACHES IN A COMMON FRAMEWORK ON THE SCEXAO HIGH CONTRAST TESTBED/INSTRUMENT FOR BOTH LABORATORY (DAYTIME) ANDON-SKY VALIDATION AT MODERATE CONTRAST LEVELS. THE TESTBED ALREADY PROVIDES THE SYSTEM-LEVEL ENVIRONMENT REQUIRED FOR MATURING AND VALIDATING MULTI-SENSOR ALGORITHMS AND DEMONSTRATING THEIR PRACTICAL IMPLEMENTATION. WAVEFRONT-SENSOR BASED POST-PROCESSING OF SCIENCE IMAGES WILL BE EXERCISED ON ON-SKY EXOPLANET OBSERVATION DATASETS FOR END-TO-END VALIDATION AT MODERATE CONTRAST. EXTRAPOLATION TO HIGHER CONTRAST ENVIRONMENTS WILL RELY ON NUMERICAL VALIDATION OF ACHIEVED RESULTS SUPPORTED BY TESTBED CALIBRATIONS. OUR EFFORT WILL BENEFIT FROM AND VALIDATE RECENT ADVANCES IN DETECTOR TECHNOLOGIES IN VISIBLE AND NEAR-IR (TECHNOLOGY GAP GC-9) AND MACHINE LEARNING TECHNIQUES. OUR TEAM INCLUDES EXPERTS IN THESE AREAS AS WELL AS HIGH CONTRAST IMAGING AND WAVEFRONT SENSING EXPERTS.
$916,541Research Corporation Of The University Of Hawaii · · FY2020 · National Aeronautics and Space Administration
EFIT-AI: MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE ASSISTED EQUILIBRIUM RECONSTRUCTION FOR TOKAMAK EXPERIMENTS AND BURNING PLASMAS
$916,440Tech-X Corporation · · FY2020 · Department of Energy
EMERGE PHASE III CLINICAL CENTER AT PARTNERS HEALTHCARE
$916,160Scott T Weiss · Brigham And Women'S Hospital · U01 · FY2017 · HG
SHF: Medium: Program Synthesis for Weak Supervision
$916,000Aws Albarghouthi · University Of Wisconsin-Madison · · FY2021 · CSE
NSF Convergence Accelerator Track D: Artificial Intelligence and Community Driven Wildland Fire Innovation via a WIFIRE Commons Infrastructure for Data and Model Sharing
$915,999Ilkay Altintas · University Of California-San Diego · · FY2020 · TIP
RI: AF: Medium: Learning and Matrix Reconstruction with the Max-Norm and Related Factorization Norms
$915,986Nathan Srebro · Toyota Technological Institute At Chicago · · FY2013 · CSE