Government Contract Award Search - Machine Learning | Federal Compass

Government Contract Award Search - Machine Learning

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140R8121P0079 - MACHINE LEARNING SUBSEASONAL FOREACSTING
Purchase Order - 541990 All Other Professional, Scientific, and Technical Services
Contractor
UNIVERSITY OF SAN DIEGO
Contracting Agency/Office
Interior»Bureau of Reclamation»Office of Policy, Administration and Budget»Mission Support Organization
Effective date
07/12/2021
Obligated Amount
$250k
80NSSC21K0993 - SINCE THE ADVENT OF FIRST GENERATION MODERN ASTRONOMICAL OBSERVATORIES, THE ENSUING GOAL HAD BEEN TO OBTAIN DEEPER AND HIGHER RESOLUTION OBSERVATIONS OF THE SKY. THOUGH THIS CAN ULTIMATELY BE ATTAINED WITH BETTER INSTRUMENTATION AND LARGER OBSERVATORIES, THESE OBJECTIVES WOULD ULTIMATELY BE LIMITED BY EXISTING TECHNOLOGY, MOST NOTICEABLY AT LONGER WAVELENGTHS. THE AVAILABILITY OF DEEP HIGH RESOLUTION DATA, SPECIFICALLY WHEN AVAILABLE AT MULTIPLE WAVELENGTHS IN THE FORM OF BROAD-BAND AND/OR SPECTROSCOPIC OBSERVATIONS, HAS THE POWER TO DETERMINE THE PHYSICAL PROPERTIES AND EVOLUTIONARY HISTORIES OF GALAXIES. THE FIELD OF MACHINE LEARNING HAS WITNESSED TREMENDOUS ADVANCES OVER THE PAST DECADE WITH THE DEVELOPMENT OF THE STATE-OF-THE-ART HARDWARE COMBINED WITH NEURAL NETWORK DEEP LEARNING ALGORITHMS ACHIEVING SUPER-HUMAN CAPABILITIES. THIS IN PARTICULAR EXTENDS TO NOT ONLY IMAGE CLASSIFICATIONS AND FEATURE IDENTIFICATION BUT TO QUITE INTERESTINGLY MACHINE GENERATED DATA IDENTICAL TO THE REAL OBSERVATIONS, WHERE ITS BEING READILY UTILIZED IN VARIOUS SECTORS. GENERATIVE ADVERSARIAL NETWORKS (GANS) ARE AN UNSUPERVISED DEEP LEARNING BASED GENERATIVE APPROACH THAT ARE NOW WIDELY USED IN MANY DIVERSE DISCIPLINES TO CREATE NEW DATA SATISFYING TRUE DISTRIBUTIONS, REMOVE NOISE, FILL-IN MISSING DATA OR IMPROVE RESOLUTION AMONG OTHER APPLICATIONS. DISTRIBUTION OF GALAXIES IN THEIR MULTIDIMENSIONAL SPACE OF FLUXES OVER THE ELECTROMAGNETIC SPECTRUM PROVIDES A GOOD LEARNING POOL FOR ASTRONOMICAL GANS. IN THIS PROPOSAL WE AIM TO USE THE NASA ASTROPHYSICAL DATABASE ARCHIVE TO TRAIN THE DISTRIBUTION OF GALAXY IMAGES, SEDS AND SPECTRA OVER A WIDE WAVELENGTH RANGE AND USE THE TRAINED MODELS TO PRODUCE HIGH RESOLUTION IMAGES AND SPECTRA GIVEN LOWER RESOLUTION MULTI-WAVEBAND SEDS IN THE SAME WAVELENGTH RANGE. IT HAS BEEN SHOWN THAT THE BROAD-BAND COLORS HAVE HIDDEN INFORMATION ABOUT HIGHER RESOLUTION FEATURES IN THE SPECTRA SUCH AS EMISSION LINE PROPERTIES. GANS PROVIDE THE MEANS TO EASILY FIND THESE HIDDEN CORRELATIONS BY CLASSIFYING GALAXIES OVER THE WHOLE SPECTRAL ENERGY DISTRIBUTIONS (SEDS). WE WILL PROVIDE FINE-TUNED ALGORITHMS TO INCREASE THE NUMBER OF BROAD BANDS IN THE EUCLID AND ROMAN SPACE TELESCOPE DEEP FIELDS, INCREASE THE SPATIAL RESOLUTION OF THE VERA RUBIN OBSERVATORY IMAGES, AND INCREASE THE SPECTRAL RESOLUTION OF SPHEREX OBSERVATIONS TO MATCH THOSE OF THE KECK. BENEFITS FROM THESE ENHANCED DATA PRODUCTS ARE COUNTLESS, AMONG WHICH ARE LESS BLENDING, BETTER REDSHIFT MEASUREMENTS, ACCURATE PHYSICAL PARAMETER ESTIMATES, MORE ACCURATE WEAK LENSING STUDIES, AND MORE PRECISE COSMOLOGICAL MEASUREMENTS WITHOUT THE NEED FOR MORE TELESCOPE TIME.
Grant for Research
Contractor
University of California (REGENTS OF THE UNIVERSITY OF CALIFORNIA AT RIVERSIDE)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
07/08/2021
Obligated Amount
$127k
80NSSC21M0130 - ADVANCED CAPABILITIES PLANNED FOR THE NEXT GENERATION OF AUTONOMOUS AND INCREASINGLY AUTONOMOUS AIR VEHICLES WILL INCLUDE NONTRADITIONAL COMPONENTS BASED ON ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, AND COMPLEX OPTIMIZATION AND PLANNING ALGORITHMS.
Cooperative Agreement
Contractor
Boeing (BOEING COMPANY, THE)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
06/29/2021
Obligated Amount
$526.6k
80NSSC21K1151 - IMPROVING HIGH RESOLUTION (M SCALE) MAPPING OF SNOW COVERED AREAS IN COMPLEX FORESTED TERRAIN IS CRUCIAL TO UNDERSTANDING CHANGES AND RELATED RESPONSES OF SPECIES AND WATER SYSTEMS TO CLIMATE CHANGE. PLANET LABS, INC. (PLANET) IS A PROMISING NEW SOURCE OF COMMERCIAL HIGH-RESOLUTION IMAGERY THAT CAN BE USED IN ENVIRONMENTAL SCIENCE, AS IT HAS BOTH HIGH SPATIAL (0.7-3.0 M) AND TEMPORAL (1-2 DAY) RESOLUTION. HOWEVER, ITS IMMEDIATE UTILITY WITH RESPECT TO INFERRING SNOW COVER IS MORE RESTRICTIVE DUE TO THE LIMITATIONS IN THE NUMBER AND BANDWIDTH OF THE NEAR-INFRARED (NIR) BAND, WHICH MAKES DISTINGUISHING SNOW PIXELS FROM OTHER LAND COVER PIXELS CHALLENGING USING A TRADITIONAL RADIOMETRIC INDEX (SUCH AS THE NORMALIZED DIFFERENCE SNOW INDEX, NDSI), AND THEREFORE REQUIRES AN ALTERNATIVE APPROACH. WE WILL EXTEND A MACHINE LEARNING FRAMEWORK BASED ON CONVOLUTIONAL NEURAL NETWORKS TO IMPROVE SNOW COVER MAPPING IN COMPLEX TERRAIN AND FORESTED REGIONS IN FOREST GAPS AND BETWEEN SPARSE TREES. WE WILL COUPLE GROUND AND AIRBORNE-DERIVED SNOW OBSERVATIONS WITH PLANET IMAGERY IN DIFFERENT MOUNTAIN SYSTEMS IN WASHINGTON, CALIFORNIA, AND COLORADO, USA. THESE SITES ARE IDEAL CANDIDATES FOR OUR ANALYSIS AS THEY DIFFER IN CLIMATE AND TOPOGRAPHIC FEATURES AND ARE SITES WHERE GROUND AND AIRBORNE SNOW OBSERVATIONS AT HIGH RESOLUTION (3M) HAVE BEEN COLLECTED BY THE NASA AIRBORNE SNOW OBSERVATORY (ASO) AND SNOWEX MISSIONS. WHILE BASIC WORKFLOWS WILL BE DEVELOPED USING PLANET DATA, THIS PROPOSAL WILL BE CONSIDERING DATA FROM OTHER SMALLSAT PROVIDERS. THE AVAILABILITY OF HIGH RESOLUTION SNOW MAPS CAN IMPROVE WATER, FOREST AND ECOSYSTEMS MANAGEMENT, INFORM CORRECTIONS FOR COARSER RESOLUTION SNOW PRODUCTS AND ALBEDO ESTIMATES ACROSS FORESTED REGIONS.
Grant for Research
Contractor
University of Washington (UNIVERSITY OF WASHINGTON)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
06/28/2021
Obligated Amount
$132.3k
80NSSC21K0980 - SPATIOTEMPORAL QUANTIFICATION OF SURFACE WATER AND FLOODING IS ESSENTIAL FOR RESEARCH ON HYDROLOGICAL CYCLES. SATELLITE REMOTE SENSING IS THE ONLY MEANS OF MONITORING THESE DYNAMICS ACROSS VAST AREAS AND OVER TIME. SEVERAL REGIONAL TO GLOBAL SURFACE WATER DATA SETS HAVE BEEN DEVELOPED USING OPTICAL TIME-SERIES, EITHER FROM MODIS-TYPE SENSORS WITH COARSE SPATIAL RESOLUTION BUT DAILY FREQUENCY, OR BASED ON THE ENTIRE LANDSAT ARCHIVE. DESPITE ITS HIGH SPATIAL RESOLUTION, THE 16-DAY REPEAT FREQUENCY OF LANDSAT MEANS THAT SHORT LIVED HAZARDOUS FLOODING AND THE MAXIMUM EXTENT OF LARGE FLOODS ARE LIKELY MISSED. MEANWHILE, SPATIALLY COARSER MODIS-TYPE SENSORS MAY MISS SMALL WATER BODIES AND FLOODS ENTIRELY. IN ADDITION, TWO LIMITATIONS WHEN MAPPING INUNDATION WITH OPTICAL DATA HAVE BEEN DETECTING WATER UNDER VEGETATION AND CLOUD OBSCURATION, WHICH OFTEN COINCIDES WITH FLOODS. BOTH ISSUES CAN BE OVERCOME BY FUSING MULTIPLE OPTICAL WITH SYNTHETIC APERTURE RADAR (SAR) DATA, TAKING ADVANTAGE OF COMPLEMENTARY OBSERVATION PROPERTIES INCLUDING SAR S ABILITY TO PENETRATE THROUGH CLOUDS. THUS, COMBINING OBSERVATIONS AND SPECTRAL PROPERTIES OF THE NEWLY AVAILABLE SENTINEL 1 SAR (S1) AND SENTINEL 2 (S2) SERIES OF SATELLITES WITH LANDSAT 8 (L8) HOLDS PROMISE FOR GLOBAL SURFACE WATER AND FLOOD MAPPING WITH IMPROVED SPATIAL AND TEMPORAL RESOLUTION AND ACCURACY. TO ACCURATELY CAPTURE MAXIMUM EXTENT OF ALL FLOODS IN NEAR REAL TIME, THE KEY OBJECTIVES ARE TO (1) MAP FLOODING DYNAMICS GLOBALLY, USING MACHINE LEARNING APPLIED TO TIME-SERIES OF MULTI-SENSOR OPTICAL (L8, S2) AND RADAR (S1) TIME SERIES DATA, (2) ASSESS THE ACCURACY OF THE MAPPED FLOOD EXTENT, AND (3) TEST THE ABILITY OF OUR ALGORITHMS TO MAP (A) EPHEMERAL FLOODS IN A DYNAMIC DRYLAND RIVER SYSTEM (B) A COMPLEX DELTA INCLUDING INUNDATED VEGETATION IN WESTERN CANADA (LEVERAGING FIELD VALIDATION DATA ON EXTENT OF INUNDATED VEGETATION COLLECTED DURING NASA S ARCTIC BOREAL VULNERABILITY EXPERIMENT), (C) EXTREME FLOODING IN NORTH CAROLINA (DURING HURRICANES IN 2016, 2018 AND 2019), AND (D) SMALL WATER BODIES (< 5HA) IN IRRIGATED AREAS (I.E. ARKANSAS, THE U.S. STATE WITH THE 3RD LARGEST IRRIGATED AREA, WHERE HUNDREDS OF SMALL RESERVOIRS HAVE BEEN CONSTRUCTED SINCE THIS PROPOSAL IS SIGNIFICANT TO THIS NASA SOLICITATION AS IT WILL ENABLE IMPROVED QUANTIFICATION OF FLOOD EXTENT DYNAMICS AND WATER QUANTITY. THE ALGORITHMS AND MAPS PRODUCED CAN BE USED FOR BETTER MAPPING OF FLOODS DURING HAZARDOUS CONDITIONS AND ASSESSMENT OF HOW CHANGES IN LAND COVER AND LAND USE AND CLIMATE IMPACT SURFACE WATER AND FLOOD DYNAMICS.2015).
Grant for Research
Contractor
ITRE/NC STATE UNIVERSITY (NORTH CAROLINA STATE UNIVERSITY)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
06/28/2021
Obligated Amount
$140.2k
80NSSC21K1185 - WE PROPOSE TO COMPLETE THE IDENTIFICATION OF INTERSTELLAR DUST IMPACTS IN NASA S STARDUST INTERSTELLAR DUST COLLECTOR, USING A COMBINATION OF OPTICAL AND SEM IMAGING, DEEP MACHINE LEARNING USING CONVOLUTIONAL NEURAL NETWORKS, AND CANDIDATE IMPACT
Grant for Research
Contractor
University of California (REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
06/28/2021
Obligated Amount
$196k
80NSSC21M0173 - A PICTURE CAN BE WORTH A THOUSAND WORDS AND THIS DESCRIBES THE DATA NECESSARY TO IDENTIFY AND TRACK GLOBAL LAND COVER CHANGE. CITIZEN SCIENCE APPS AND SOCIAL MEDIA ARE GENERATING ENORMOUS AMOUNTS OF DATA IN THE FORM OF PHOTOGRAPHS UPLOADED TO THE CLOUD. PHOTOGRAPHS SUBMITTED VIA THE GLOBE OBSERVER APP PROVIDE THE LINK BETWEEN SPACE AND EARTH, FOSTERING AN UNDERSTANDING OF EARTH S PHYSICAL PROCESSES AND NATURAL PHENOMENON. THE VOLUME OF PHOTOGRAPHS IS OUTPACING HUMAN ABILITY TO ORGANIZE, CHARACTERIZE, EVALUATE AND CLASSIFY DATA FOR SEARCH, COMPARISON, CHANGE DETECTION, AND PREDICTION. THIS IS WHERE THE HACK COMES IN. THIS PROPOSAL WILL INCLUDE A YEAR OF ACTIVITIES TO EXPLORE AND CREATE MACHINE LEARNING (ML) TOOLS TO SEGMENT, CHARACTERIZE, CLASSIFY, AND LABEL COMPONENTS OF LAND COVER PHOTOGRAPHS FROM THE GLOBE OBSERVER (GO) LAND COVER APP. DATA PREPARATION CHOOSES IMAGE REPLICATES FROM THE GLOBE OBSERVER DATA SET (E.G., DOWNLOAD IMAGES, IDENTIFY LOCATIONS IN CLOSE PROXIMITY OVER A RANGE OF ECOSYSTEMS). PREPARATION OF WORKSHOPS INCLUDES DESIGNING OUTREACH AND APPLICATION MATERIALS, AND COMPLETING THE IRB TRAINING. DESIGNING WORKSHOPS STARTS WITH PREPARING DATA AND OTHER RESOURCES FOR COLLABORATION, PRACTICING GO ACTIVITIES, RECORDING VIDEO AND CREATING HOMEWORK ASSIGNMENTS. ORGANIZING DATA AND SAMPLE LOCATIONS WILL INVOLVE COLLABORATION THROUGH JUPYTER NOTEBOOKS. DESIGN OF SOCIAL COMPONENTS FOR DAILY SCHEDULES INCLUDES MEET-AND-GREET, PHYSICAL EXERCISE, BREAKS, GAMES, AND MEALS.
Cooperative Agreement
Contractor
NEW MEXICO DEPT. OF AGRICULTUR (NEW MEXICO STATE UNIVERSITY)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
06/28/2021
Obligated Amount
$99.7k
80LARC21CA005 - AEROFUSION-MLUQ: MARS LANDER AERODYNAMIC MODEL DATABASE FUSION USING MACHINE LEARNING WITH EMBEDDED UNCERTAINTY QUANTIFICATION
Definitive Contract - 541715 Research and Development in the Physical, Engineering, and Life Sciences
Contractor
UNIVERSITY OF FLORIDA
Contracting Agency/Office
National Aeronautics and Space Administration»Langley Research Center
Effective date
06/11/2021
Obligated Amount
$100k
80LARC21CA002 - MULTI-FIDELITY SIMULATION AND UNCERTAINTY QUANTIFICATION OF MARS LANDER AERODYNAMICS TO VALIDATE COMPUTATIONAL FLUID DYNAMICS SOLVERS, ASSESS AND BALANCE UNCERTAINTY SOURCES, INTEGRATE RESULTS AND ANALYSIS, ESTABLISH HIGH-PERFORMANCE WORKFLOWS.
Definitive Contract - 541715 Research and Development in the Physical, Engineering, and Life Sciences
Contractor
University of Southern California (UNIVERSITY OF SOUTHERN CALIFORNIA)
Contracting Agency/Office
National Aeronautics and Space Administration»Langley Research Center
Effective date
06/09/2021
Obligated Amount
$100k
80NSSC21K0737 - THE COMPOSITION OF THE SOLAR CORONA AND THE SOLAR WIND OFTEN DIFFERS FROM THAT OF THE SOLAR PHOTOSPHERE, TYPICALLY WITH A RELATIVE ENRICHMENT OF ELEMENTS WITH LOW FIRST IONIZATION POTENTIAL (FIP EFFECT). THIS CHEMICAL FRACTIONATION IS POORLY UNDERSTOOD BUT IT CAN PROVIDE CRUCIAL CLUES ABOUT THE PHYSICAL PROCESSES AT WORK IN THE SOLAR OUTER ATMOSPHERE: SURELY ORIGINATING IN THE CHROMOSPHERE WHERE THE FIRST IONIZATION OCCURS, AND LINKED TO THE CORONAL HEATING MECHANISM, BUT CARRYING ITS SIGNATURE THROUGHOUT THE MANY LAYERS AND MAGNETIC STRUCTURING OF THE CORONA AND INTO THE SOLAR WIND. THE VARIATION OF THE CHEMICAL FRACTIONATION, BOTH IN SPACE AND IN TIME, CAN THEREFORE BE USED AS A TRACER OF THE MASS AND ENERGY FLOW THROUGHOUT THE SOLAR ATMOSPHERE. STUDIES OF TEMPORAL VARIATIONS OF THE ELEMENTAL ABUNDANCES USING SKYLAB DATA HINTED AT A SYSTEMATIC INCREASE OF LOW-FIP ELEMENTS ENHANCEMENT (UP TO ALMOST AN ORDER OF MAGNITUDE) IN AN ACTIVE REGION (AR) OVER ABOUT 7 DAYS [1]. ONLY A COUPLE OF MORE RECENT STUDIES HAVE INVESTIGATED THE TEMPORAL VARIATIONS OF FIP IN ARS AND SUGGESTED A MORE COMPLEX RELATIONSHIP WITH AR AGE [2,3], WARRANTING MORE EXTENSIVE ANALYSES. WE PROPOSE TO USE CURRENT SPECTROSCOPIC OBSERVATIONS WITH IRIS AND HINODE/EIS, COVERING FROM THE CHROMOSPHERE TO THE TRANSITION REGION (TR) AND THE CORONA, TO MEASURE THE FIP EFFECT IN ARS AT HIGH SPATIAL RESOLUTION, WITH CADENCE OF A FEW HOURS (OR HIGHER), AND OVER AT LEAST A WEEK, IN ORDER TO COVER A SIGNIFICANT PORTION OF THE AR EVOLUTION. WE WILL COMBINE CORONAL SPECTRA WITH TR AND CHROMOSPHERIC SPECTRA TO REVEAL POSSIBLE CORRELATIONS BETWEEN THE CHEMICAL FRACTIONATION OBSERVED IN THE OUTER SOLAR ATMOSPHERE WITH PLASMA PROPERTIES IN THE LOWER ATMOSPHERE (E.G., NON-THERMAL BROADENING). A LARGE NUMBER OF COORDINATED HINODE-IRIS OBSERVATIONS SUITABLE FOR THIS TYPE OF STUDY ARE PUBLICLY AVAILABLE, INCLUDING FOR INSTANCE THE IRIS-HINODE OBSERVING PLAN 307, WHICH HAS ALREADY YIELDED LIMB-TO-LIMB MONITORING (SEVERAL HOURS A DAY) OF SEVERAL ARS. WE WILL ANALYZE THE OPTICALLY THIN EIS SPECTRAL DATA USING FIP DIAGNOSTICS BASED ON SINGLE LINE FITS (AS IN [2,3]), AND ALSO BY USING A NEW INVERSION METHOD [4], WHICH INFERS THE PLASMA EMISSION MEASURE AND VELOCITY DISTRIBUTION AS A FUNCTION OF TEMPERATURE. WE WILL MODIFY THIS INVERSION ALGORITHM TO INCLUDE ELEMENT ABUNDANCES AS ONE OF THE INVERTED PARAMETERS, AND CONSISTENTLY DERIVE CORONAL ABUNDANCES (TOGETHER WITH THE THERMAL DISTRIBUTION, THE VELOCITY, AND NON-THERMAL BROADENING) FOR A LARGE SET OF AR SPECTRAL OBSERVATIONS. WE WILL ALSO APPLY IRIS2 INVERSIONS TO THE OPTICALLY THICK MG II H & K LINES, A NOVEL DATABASE BASED ON MACHINE AND DEEP LEARNING TECHNIQUES THAT ALLOWS THE INFERENCE OF THE THERMODYNAMIC CONDITIONS OF THE LOWER ATMOSPHERE FROM IRIS SPECTRA BY TAKING INTO ACCOUNT NON- LTE CONDITIONS IN THE CHROMOSPHERE [5]. THESE UNIQUE MEASUREMENTS AND APPLICATION OF STATE-OF-THE-ART INVERSION CODES WILL ALLOW US TO DERIVE CHEMICAL FRACTIONATION AND CONNECT IT TO OBSERVABLES SUCH AS FLOWS, THERMAL AND NON-THERMAL BROADENING THROUGHOUT THE SOLAR ATMOSPHERE, AS A FUNCTION OF THE AR EVOLUTION AND CENTER TO LIMB VARIATIONS. THESE RESULTS WILL DETERMINE WHETHER OR HOW THESE VARIATIONS ARE RELATED TO CONDITIONS IN THE CHROMOSPHERE, WHERE THE FIP EFFECT IS THOUGHT TO ORIGINATE, AND, IN TURN, WILL PROVIDE NOVEL AND MUCH-NEEDED OBSERVATIONAL CONSTRAINTS ON MODELING AND THEORY OF CHEMICAL FRACTIONATION [6] THAN SO FAR AVAILABLE. OUR INVESTIGATION WILL PROVIDE UNIQUE CONSTRAINTS ON CHEMICAL FRACTIONATION AND ADDRESS SOME OF THE MAIN GOALS OF THE IRIS AND HINODE MISSIONS, SUCH AS UNDERSTANDING THE MASS AND ENERGY FLOWS IN THE SOLAR OUTER ATMOSPHERE. THE ELEMENTAL ABUNDANCE OF SOLAR WIND STREAMS IS ALSO THE BEST-KNOWN DISCRIMINATOR BETWEEN VARIOUS STATES OF THE WIND CONSEQUENTLY, THE PROPOSED STUDY IS ALSO OF GREAT INTEREST IN IN-SITU OBSERVATIONS SUCH AS SOLAR ORBITER AND PSP.
Grant for Research
Contractor
Government of the United States (SMITHSONIAN INSTITUTION)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
06/09/2021
Obligated Amount
$171.3k
75A50121C00057 - DASCENA R&D EFFORT FOR COVIAGE: RAPID DEPLOYMENT OF AN ACCESSIBLE MACHINE LEARNING SOFTWARE FOR COVID-19 SEVERITY PREDICTIONS WILL PROGRESS IN WORK SEGMENTS WITH KEY DELIVERABLES BEING DUE DURING THE BASE PERIOD OF PERFORMANCE OF THE CONTRACT.
Definitive Contract - 541715 Research and Development in the Physical, Engineering, and Life Sciences
Contractor
DASCENA, INC.
Contracting Agency/Office
Health and Human Services»Office of the Secretary»Office of the Assistant Secretary for Preparedness and Response»Office of Acquisition Management, Contracts, & Grants
Effective date
06/01/2021
Obligated Amount
$706.5k
80LARC21CA003 - MARS LANDER AERODYNAMIC MODEL DATABASE FUSION USING MACHINE LEARNING WITH EMBEDDED UNCERTAINTY QUANTIFICATION. PROVIDE EXPERTISE AND EFFORT THROUGH A SYNERGISTIC INVESTIGATION ANALYSIS, REDUCED-ORDER MODELS, DESIGN,AND SURROGATE MODELS.
Definitive Contract - 541715 Research and Development in the Physical, Engineering, and Life Sciences
Contractor
ITRE/NC STATE UNIVERSITY (NORTH CAROLINA STATE UNIVERSITY)
Contracting Agency/Office
National Aeronautics and Space Administration»Langley Research Center
Effective date
05/27/2021
Obligated Amount
$100k
75D30121P10648 - MACHINE LEARNING AND NETWORK MODELING IN GULF WAR ILLNESS PARADIGM
Purchase Order - 611310 Colleges, Universities, and Professional Schools
Contractor
NOVA SOUTHEASTERN UNIV (NOVA SOUTHEASTERN UNIVERSITY, INC.)
Contracting Agency/Office
Health and Human Services»Centers for Disease Control and Prevention
Effective date
05/25/2021
Obligated Amount
$126.5k
80NSSC21P1684 - INTELLEGENS - MACHINE LEARNING CODE - ALCHEMITE SOFTWARE SUITE - SOFTWARE LICENSE PLUS SUPPORT
Purchase Order - 511210 Software Publishers
Contractor
INTELLEGENS LIMITED
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
05/21/2021
Obligated Amount
$45k
80NSSC21K0543 - THE MAIN GOAL OF THE PROPOSED RESEARCH IS TO DELIVER A NOVEL METHODOLOGY BASED ON SCIENTIFIC MACHINE LEARNING (SML) METHODS TO PROVIDE HIGH QUALITY ESTIMATION OF WATER INHERENT OPTICAL PROPERTIES (IOPS).
Grant for Research
Contractor
STEVENS INSTITUTE OF TECHNOLOG (STEVENS INSTITUTE OF TECHNOLOGY (INC))
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
05/18/2021
Obligated Amount
$233.7k
70Z04021PP4501700 - MATHWORKS MASTER LICENSE
Purchase Order - 511210 Software Publishers
Contractor
HORIZON HOUSE, INC. (MATHWORKS, INC., THE)
Contracting Agency/Office
Homeland Security»US Coast Guard
Effective date
05/18/2021
Obligated Amount
$56.8k
80NSSC21K0719 - MACHINE LEARNING HAS OPENED THE DOOR FOR MUCH MORE ADVANCED SEARCHES OF NASA S TROVE OF HIGH-VALUE DATABASES. IN PARTICULAR, ADVANCES IN TRANSFER AND SELF-SUPERVISED LEARNING WITHIN THE DEEP LEARNING PARADIGM HAVE MADE IT POSSIBLE TO DEVELOP ROBUST
Grant for Research
Contractor
Association of Universities for Research in Astronomy, Inc (ASSOCIATION OF UNIVERSITIES FOR RESEARCH IN ASTRONOMY, INC.)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
05/17/2021
Obligated Amount
$50k
80NSSC21C0311 - NEUROMORPHIC MACHINE LEARNING FOR FAULT MANAGEMENT FOR SPACE VEHICLE APPLICATIONS
Definitive Contract - 541715 Research and Development in the Physical, Engineering, and Life Sciences
Contractor
NATURAL INTELLIGENCE SYSTEMS, INC.
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
05/13/2021
Obligated Amount
$125k
80NSSC21C0182 - MACHINE LEARNING-ACCELERATED GRID ENVIRONMENT
Definitive Contract - 541715 Research and Development in the Physical, Engineering, and Life Sciences
Contractor
EMERGENT SPACE TECHNOLOGIES INCORPORATED (EMERGENT SPACE TECHNOLOGIES, INC.)
Contracting Agency/Office
National Aeronautics and Space Administration»Mission Support Directorate»NASA Shared Services Center
Effective date
05/12/2021
Obligated Amount
$124.8k
75FCMC21C0013 - THE CENTER FOR CLINICAL STANDARDS AND QUALITY (CCSQ) IS IN NEED OF A CLOUD-BASED ARTIFICIAL INTELLIGENCE (AI) /MACHINE LEARNING (ML) PLATFORM INCLUDING NATURAL LANGUAGE PROCESSING (NLP) THAT: 1) ESTABLISHES A COMMON INFRASTRUCTURE FOR FUTURE AI/NLP/M
Definitive Contract - 541512 Computer Systems Design Services
Contractor
EXPLORE DIGITS INC.
Contracting Agency/Office
Health and Human Services»Centers for Medicare & Medicaid Services»Office of Acquisition and Grants Management
Effective date
05/11/2021
Obligated Amount
$1.5M

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