Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1392&sort=award_amount
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=award_amount", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1419&sort=award_amount", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1393&sort=award_amount", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1391&sort=award_amount" }, "data": [ { "type": "Grant", "id": "2304", "attributes": { "award_id": "2025954", "title": "LTER: Coastal Oligotrophic Ecosystem Research", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "LONG TERM ECOLOGICAL RESEARCH" ], "program_reference_codes": [], "program_officials": [ { "id": 6330, "first_name": "Paco", "last_name": "Moore", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-01", "end_date": "2025-02-28", "award_amount": 4750800, "principal_investigator": { "id": 6335, "first_name": "John", "last_name": "Kominoski", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 207, "ror": "https://ror.org/02gz6gg07", "name": "Florida International University", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 6331, "first_name": "James", "last_name": "Fourqurean", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 6332, "first_name": "Evelyn E", "last_name": "Gaiser", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 6333, "first_name": "Jennifer S", "last_name": "Rehage", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 6334, "first_name": "Kevin", "last_name": "Grove", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 207, "ror": "https://ror.org/02gz6gg07", "name": "Florida International University", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "Coastal ecosystems like the Florida Everglades provide many benefits and services to society including protection from storms, habitat and food for important fisheries, support of tourism and local economies, filtration of fresh water, and burial and storage of carbon that offsets greenhouse gas emissions. The Florida Coastal Everglades Long Term Ecological Research (FCE LTER) program addresses how and why coastal ecosystems and their services are changing. Like many coastal ecosystems, the Florida Everglades has been threatened by diversion of fresh water to support urban and agricultural expansion. At the same time, sea-level rise has caused saltwater intrusion of coastal ecosystems which stresses freshwater species, causes elevation loss, and contaminates municipal water resources. However, restoration of seasonal pulses of fresh water may counteract these threats. Researchers in the FCE LTER are continuing long-term studies and experiments to understand how changes in freshwater supply, sea-level rise, and disturbances like tropical storms interact to influence ecosystems and their services. The science team is guided by a diversity and inclusion plan to attract diverse scientists at all career stages. The team includes resource managers – who use discoveries and knowledge from the FCE LTER to guide effective freshwater restoration – and an active community of academic and agency scientists, teachers and other educators, graduate, undergraduate, and high school students. The project has a robust education and outreach program that engages the research team with the general public to advance science discoveries and protection of coastal ecosystems.\n\nThe FCE LTER research program addresses how increased pulses of fresh and marine water will influence coastal ecosystem dynamics through: (i) continued long-term assessment of changes in biogeochemistry, primary production, organic matter, and trophic dynamics in ecosystems along freshwater-to-marine gradients with a focus on how these affect accumulation of carbon and related elevation change, (ii) meteorological studies that evaluate how the climate drivers of hydrologic presses and pulses are changing, (iii) social-ecological studies of how governance of freshwater restoration reflects the changing values of ecosystem services, and (iv) use of high-resolution remote sensing, coupled with models to forecast landscape-scale changes. A new experimental manipulation will determine drivers and mechanisms of resilience to saltwater intrusion. Data syntheses integrate month-to-annual and inter-annual data into models of water, nutrients, carbon, and species patterns and interactions throughout the Everglades landscape to compare how ecosystems with different productivities and carbon stores respond (maintain, increase, or decline) to short- (pulses) and long-term changes (presses) in hydrologic connectivity. Synthesis efforts will use data from national and international research networks aimed at understanding how chronic presses and increasing pulses determine ecosystem trajectories, addressing one of the most pressing challenges in contemporary ecology.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10061", "attributes": { "award_id": "2227301", "title": "Mentor-Connect Forward: Leadership Development and Outreach for ATE", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)", "Advanced Tech Education Prog" ], "program_reference_codes": [], "program_officials": [ { "id": 692, "first_name": "Virginia", "last_name": "Carter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-01", "end_date": "2027-08-31", "award_amount": 4796313, "principal_investigator": { "id": 25939, "first_name": "Elaine", "last_name": "Craft", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 25936, "first_name": "Richard H", "last_name": "Roberts", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 25937, "first_name": "Emery", "last_name": "DeWitt", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 25938, "first_name": "Pamela J", "last_name": "Silvers", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1878, "ror": "", "name": "Florence-Darlington Technical College", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true }, "abstract": "This project will support community and technical colleges and their faculty to submit proposals to, and maximize their benefit from, funding through the Advanced Technological Education (ATE) Program. ATE grants increase faculty ability and institutional capacity to address the need for a skilled technical workforce. The persistent need for highly skilled technicians is recognized and well-documented, but educational programs have been upended by disrupters like COVID. Virtual instruction has become essential across all disciplines, and overall enrollments have declined, as have college budgets. Meanwhile, the critical and growing need for technicians in advanced technology industries remains. Although the ATE Program is uniquely positioned to help colleges address technician education challenges, colleges must develop and submit grant proposals to access this funding. For the ATE Program to impact two-year institutions of higher education (2-yr IHEs) and educate the skilled technical workers needed by industry, barriers to becoming an ATE grantee must be mitigated. Prior awards have made strides toward reducing barriers, engaging more two-year college technician educators, developing STEM faculty leaders, expanding mentoring capacity, and increasing impacts of the ATE Program. Even so, there are still many two-year colleges that have not yet benefited from the ATE Program.\n\nMentor-Connect Forward: Leadership Development and Outreach for ATE (M-C Forward) will: 1) advance technician education in new and proven ways by expanding engagement of geographically and demographically diverse 2-yr IHEs and STEM faculty with the ATE Program; 2) stimulate use of ATE-developed resources; 3) encourage and support the submission of proposals by new and previous grantee institutions; 4) develop leaders and mentors among those who receive ATE funding; and 5) support and guide new principal investigators (PIs) to help them become successful grantees. The project builds on successes and lessons learned from prior projects and leverages the work of other funded mentoring projects. Peer mentoring and technical assistance will leverage problem-based learning to engage college teams in sustainable, faculty-lead improvement of technician education courses and programs. ATE Program information and grant proposal instructions and development strategies will be provided via workshops, webinars, online resources, and a help desk. A Mentor Fellows internship program will build mentoring capacity in the ATE Program. An existing Resource Repository will be enhanced by a new intake, review, and user support system, and will benefit from contributions from other ATE-funded mentoring initiatives. New instructional resources and support to guide first-time PIs, PI 101, will promote leadership development, reduce the learning curve, support improved project outcomes, and encourage development of subsequent proposals. Mentor-Connect will be responsive to, and continuously improved by, rigorous evaluation of all project activities. This project is funded by the Advanced Technological Education program that focuses on the education of technicians for the advanced-technology fields that drive the Nation's economy.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12279", "attributes": { "award_id": "1C06OD036014-01", "title": "Biomaterial Manufacturing Suite in Support of NIH/NIAID and the Global Infectious Disease Research Community", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "NIH Office of the Director" ], "program_reference_codes": [], "program_officials": [ { "id": 28173, "first_name": "YONG", "last_name": "Chen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-09-06", "end_date": "2026-11-30", "award_amount": 4798286, "principal_investigator": { "id": 26529, "first_name": "Rebecca", "last_name": "Bradford", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1788, "ror": "https://ror.org/03thhhv76", "name": "American Type Culture Collection", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "Biomaterial Manufacturing Suite in Support of NIH/NIAID and the Global Infectious Disease Research Community PROJECT DIRECTOR: REBECCA BRADFORD, MBA, MS, PMP® Project Summary The project is to construct and commission a Biomaterial Manufacturing Suite (BMS) as an expansion within the High Containment Facility (HCF) currently under design at the American Type Culture Collection (ATCC). ATCC is a non-profit entity in Manassas, Virginia, serving the Federal Government for over 50 years through our Federal Solutions (AFS) Division. The proposed aim of the BMS is to provide modern and reproducible large-scale biomaterial manufacturing capabilities for priority pathogens. Residing within the soon-to-be-built HCF, the BMS will offer the National Institute of Health and the National Institute of Allergy and Infectious Diseases (NIH/NIAID) high-throughput and rapid development pipelines for biomaterials of public health concern, including those of epidemic or pandemic potential. The BMS will directly support Federal Agencies and the infectious disease research communities by optimizing pathogenic organisms’ growth, production, and characterization for downstream use. By funding the BMS within the planned facility, AFS can enhance our support to NIH/NIAID through our ability to offer large-scale stocks of well-characterized challenge materials at no cost to the research community through AFS managed programs, including BEI Resources. In turn, this will accelerate infectious disease research for vaccine and therapeutic development in outbreak situations and serve as biological standards for developing detection assays. AFS’ current modular 7,500 ft2 HCF was built in 2007 as a temporary solution to facilitate the expanding needs of AFS’ Health and Human Services (HHS) programs. The facility is now over- extended with respect to lifespan, capacity, and capabilities. AFS dutifully maintains the upkeep of the current HCF to support the extensive NIH/NIAID requests for biological products to advance our medical countermeasures and arsenal against variants for the recent onslaught of the COVID- 19 pandemic. As a non-profit organization, ATCC has committed several million dollars to design and construct a new HCF to enhance and modernize our support to NIH. The explicit goal of this funding is to include the design, construction, and commissioning of the BMS within the facility footprint to provide critical biological manufacturing capabilities in the biomedical space to accelerate translational research for vaccine and therapeutic development.", "keywords": [ "Acceleration", "American Type Culture Collection", "Biocompatible Materials", "Biological", "Biological Products", "COVID-19 pandemic", "Communities", "Containment", "Development", "Disease Outbreaks", "Federal Government", "Funding", "Goals", "Growth", "Health", "Human", "Infectious Diseases Research", "Longevity", "Modernization", "National Institute of Allergy and Infectious Disease", "Nonprofit Organizations", "Organism", "Pathogenicity", "Production", "Public Health", "Reproducibility", "Research", "Resources", "Translational Research", "United States National Institutes of Health", "Variant", "Virginia", "cost", "design", "design and construction", "detection assay", "epidemic potential", "manufacture", "manufacturing capabilities", "medical countermeasure", "pandemic potential", "priority pathogen", "programs", "service programs", "therapeutic development", "vaccine development" ], "approved": true } }, { "type": "Grant", "id": "9022", "attributes": { "award_id": "272201700012I-0-759302000001-2", "title": "Task B08: Development and Use of a Non-Human Primate Model of SARS-CoV-2 Infection", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-03-27", "end_date": "2020-07-26", "award_amount": 4821458, "principal_investigator": { "id": 24838, "first_name": "KAREN", "last_name": "THOMPSON", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1789, "ror": "", "name": "BATTELLE CENTERS/PUB HLTH RES & EVALUATN", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1789, "ror": "", "name": "BATTELLE CENTERS/PUB HLTH RES & EVALUATN", "address": "", "city": "", "state": "OH", "zip": "", "country": "United States", "approved": true }, "abstract": "This contract provides for the development and standardization of non-human primate models of infectious diseases, and may include efficacy testing of candidate products, including GLP studies to support licensure.", "keywords": [ "2019-nCoV", "COVID-19", "Contracts", "Development", "Infection", "Licensure", "Modeling", "Standardization", "Therapeutic", "animal model development", "efficacy testing", "infectious disease model", "nonhuman primate", "novel coronavirus", "novel vaccines" ], "approved": true } }, { "type": "Grant", "id": "15701", "attributes": { "award_id": "1U54AI191253-01", "title": "Center for Multiscale Immune Systems Modeling", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 32567, "first_name": "MEGHAN ANN", "last_name": "HARTWICK", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-06-13", "end_date": "2030-05-31", "award_amount": 4874388, "principal_investigator": { "id": 32568, "first_name": "Cliburn C", "last_name": "Chan", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 20611, "first_name": "Roger Keith", "last_name": "Reeves", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 246, "ror": "https://ror.org/00py81415", "name": "Duke University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true } ] } ], "awardee_organization": { "id": 246, "ror": "https://ror.org/00py81415", "name": "Duke University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "The Center of Excellence (CoE) is a research initiative that brings together experts from various fields to develop innovative solutions for multi-scale modeling in infectious and immune-mediated disease (IID). The CoE consists of the: Administrative Core (AC), Community Development and Education Core (CDEC), Model and Data Sharing Core (MDSC), and three Research Projects (RP). Each component plays a crucial role. The AC serves as a central hub, connecting various entities, and plays a critical role in pivoting CoE resources during disease outbreaks. It administers the Opportunities Fund, supporting proposals from investigators across NIAID- sponsored modeling groups. The CDEC will develop educational resources, build communities of practice and learning, organize research experiences for graduate students and postdoctoral fellows, and set up document sharing facilities, messaging platforms, and a centralized website to facilitate knowledge sharing. The MDSC will develop an informatics infrastructure that enables seamless integration of data and models across different scales, facilitating more accurate predictions and informed decision-making. The RPs focus on bridging models of host-virus interactions across biological scales. RP1 models humoral defense against viral pathogens, using antibody-antigen molecular dynamics at the molecule scale to understand the constraints limiting the evolution of immune repertoires at the individual scale. RP2 models the immune cell as a target of viral infection, using agent-based models of lymphoid tissue at the cell scale to inform host-pathogen dynamics at the individual scale. RP3 models the interactions between individuals and populations, using agent based models of host-pathogen interactions at the individual scale to inform stochastic epidemic models at the population scale. The research focuses on modeling a set of clinically important viruses, including HIV-1, SARS-CoV-2, Epstein Barr Virus (EBV), and others. The models can be used to study disease pathogenesis, the effect of medical interventions, and disease transmission in heterogeneous population networks. Key strengths of the proposed CoE are (1) the ability to coordinate administrative approaches and technologies for the infectious disease modeling community; (2) a collaborative environment that encourages knowledge sharing, innovation, and the development of cutting- edge solutions; (3) balanced representation of the experimental and computational communities within each Core and RP; (4) extensive experience with IID modeling, team science, education, and community development; (5) robust informatics infrastructure for model and data sharing that already hosts large-scale NIH- funded projects; (6) exceptional strengths integrating generative deep learning with computational modeling in the MDSC and RPs, and (7) the importance of the proposed research to develop more accurate IID models that can inform public health policy and decision-making. The unique strengths of the proposed CoE make it an ideal platform for advancing IID research, developing innovative solutions to complex problems, and responding during infectious disease outbreaks, epidemics and pandemics.", "keywords": [ "2019-nCoV", "Acceleration", "Address", "Antibodies", "Antibody Repertoire", "Antibody Response", "Antigens", "Artificial Intelligence enhanced", "Biological", "Biological Models", "Cells", "Clinical", "Cloud Computing", "Code", "Collaborations", "Communicable Diseases", "Communication", "Communities", "Community Developments", "Community Health Education", "Community of Practice", "Complex", "Computer Models", "Data", "Data Set", "Decision Making", "Dedications", "Development", "Disease", "Disease Outbreaks", "Education", "Educational workshop", "Emergency Situation", "Ensure", "Epidemic", "Escape Mutant", "Event", "Evolution", "Fostering", "Funding", "Funding Opportunities", "Goals", "Grant", "HIV-1", "Heterogeneity", "Human Herpesvirus 4", "Immune", "Immune system", "Immunological Models", "Individual", "Infection", "Information Systems", "Infrastructure", "Intervention", "Knowledge", "Leadership", "Learning", "Licensing", "Link", "Lymphoid Tissue", "Mediating", "Medical", "Mentors", "Metadata", "Modeling", "National Institute of Allergy and Infectious Disease", "Organism", "Outcome", "Pathogenesis", "Play", "Policies", "Policy Making", "Population", "Population Heterogeneity", "Positioning Attribute", "Postdoctoral Fellow", "Printing", "Public Health", "Publications", "Reproducibility", "Research", "Research Personnel", "Research Project Grants", "Resources", "Retrieval", "Role", "Running", "Science", "Scientific Advances and Accomplishments", "Services", "Strategic Planning", "Students", "System", "Technology", "Therapeutic Intervention", "Training", "Training Programs", "United States National Institutes of Health", "Viral", "Virus", "Virus Diseases", "Virus-Cell Membrane Interaction", "career", "collaborative environment", "community building", "computational platform", "computer framework", "data infrastructure", "data integration", "data modeling", "data resource", "data sharing", "deep learning", "design", "disease model", "disease transmission", "education resources", "experience", "experimental study", "graduate student", "higher education", "immunological intervention", "in silico", "infectious disease model", "informatics infrastructure", "innovation", "interdisciplinary approach", "learning community", "meetings", "molecular dynamics", "multi-scale modeling", "new epidemic", "novel", "open source", "outbreak preparedness", "outbreak response", "pandem" ], "approved": true } }, { "type": "Grant", "id": "9175", "attributes": { "award_id": "75N92020C00019-P00002-9999-1", "title": "RAPID ACCELERATION OF DIAGNOSTICS (RADX) TECH PROGRAM: PROJECT NO 5218 MATMACORP SARS-COV-2 HIGH THROUGHPUT LABORATORY CAPACITY SCALE-UP", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Biomedical Imaging and Bioengineering (NIBIB)" ], "program_reference_codes": [], "program_officials": [], "start_date": "2020-08-29", "end_date": "2021-04-30", "award_amount": 4947000, "principal_investigator": { "id": 24935, "first_name": "PHIL", "last_name": "KOZERA", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1804, "ror": "", "name": "MATERIALS/ MACHINES CORPORATION/AMERICA", "address": "", "city": "", "state": "NE", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1804, "ror": "", "name": "MATERIALS/ MACHINES CORPORATION/AMERICA", "address": "", "city": "", "state": "NE", "zip": "", "country": "United States", "approved": true }, "abstract": "MatMaCorp is an animal health diagnostics company that collaborates with agencies including the Department of Homeland Security (DHS) Science and Technology group and USDA's Meat Animal Research Center (USMARC). In February of 2020, we shifted focus to human health in response to the COVID-19 pandemic. We are working to utilize our portable diagnostic platform, the Solas 8 fluorescent detection device and proprietary tests, with features supportive of rapid, mobile human diagnostics. Our device uses molecular probes to detect and identify specific DNA or RNA (target) sequences, in addition to a mutation or variation (SNP) within a sequence. Additional Features: · Touchscreen interface · USB Ports · Wi-Fi enabled · Mobile Application · Automated calling of results Additionally, our assays are lyophilized and do not require pipettes, centrifuges, or refrigeration and have a twelve-month shelf life. The Covid-19 kits are made for lab-use or field-use, providing flexibility and accessibility. Whether at a workplace, in a lab, or in a mobile testing center, results can be generated in real-time without specialized lab equipment, technical skills, or controlled conditions.", "keywords": [ "2019-nCoV", "Animal Experimentation", "Animals", "Biological Assay", "COVID-19", "COVID-19 pandemic", "DNA", "Detection", "Devices", "Diagnostic", "Freeze Drying", "Health", "Human", "Laboratories", "Life", "Meat", "Molecular Probes", "Mutation", "RADx Tech", "RNA", "Refrigeration", "Science", "Security", "Technical Expertise", "Technology", "Testing", "Time", "Variant", "Workplace", "diagnostic platform", "flexibility", "laboratory equipment", "mobile application", "portability", "programs", "response", "scale up", "touchscreen", "wireless fidelity" ], "approved": true } }, { "type": "Grant", "id": "4919", "attributes": { "award_id": "1137725", "title": "Puerto Rico Center for Environmental Neuroscience", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)", "Centers for Rsch Excell in S&T" ], "program_reference_codes": [], "program_officials": [ { "id": 17732, "first_name": "Victor", "last_name": "Santiago", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2011-09-01", "end_date": "2017-08-31", "award_amount": 4985003, "principal_investigator": { "id": 17736, "first_name": "Mark", "last_name": "Miller", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1359, "ror": "", "name": "University of Puerto Rico Medical Sciences Campus", "address": "", "city": "", "state": "PR", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 17733, "first_name": "Joshua J", "last_name": "Rosenthal", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 17734, "first_name": "Maria A", "last_name": "Sosa", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 17735, "first_name": "Bruno", "last_name": "Marie-Bordes", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1359, "ror": "", "name": "University of Puerto Rico Medical Sciences Campus", "address": "", "city": "", "state": "PR", "zip": "", "country": "United States", "approved": true }, "abstract": "Human activities are altering the environment at an alarming rate. A multidisciplinary approach is essential to understand the complex interplay between molecular, cellular, and behavioral responses by organisms under these increasingly stressful conditions. The nervous system is the interface between an organism and its environment. \n\nThe Puerto Rico Center for Environmental Neuroscience (PRCEN) will combine neuroscience (the study of the nervous system and behavior) and environmental science (the study of local ecosystem environments) to tackle environmental issues in Puerto Rico's tropical setting. The Center will combine neuroscientists from the Institute of Neurobiology and the Dept. of Anatomy of the University of Puerto (UPR) Medical Sciences campus and environmental scientists from the Environmental Sciences Program and the Depts. of Biology and Chemistry of the UPR Rio Piedras. The alliance will bring together cutting-edge techniques normally associated with cellular and molecular neuroscience with expertise in local ecosystems and environmental science to create a novel field that will require participants to move outside of their comfort zones and learn about entirely new areas of research. \n\nObjectives of the center will be to: (1) establish research programs in the new field of environmental neuroscience, (2) enhance research productivity through faculty and infrastructure development, (3) increase the numbers of minority students attaining advanced degrees in interdisciplinary science, and (4) generate community understanding of the work being done in the Center. \n\nThe research subprojects focus on four local ecosystems: terrestrial, freshwater rivers, estuaries, and marine systems. The habitats under study are intimately connected: contaminants in the mountains make their way into rivers, pass through the estuaries, and end up in the sea. \n\nThe oceans subproject is designed to understand the consequences of environmental pressures on tropical corals, using state of the art molecular-cellular techniques. \n\nThe estuaries project will focus on the blue crab, which supports one of the largest fisheries industries in the United States. This project will use high resolution monitoring to track the presence of contaminants and other environmental stressors, and correlate the resulting environmental data with physiological monitoring of heart and endocrine functioning in this crab. \n\nThe freshwater studies will monitor contaminants in three representative Puerto Rican rivers. Four animal models (zebrafish, mosquitofish, and two types of prawn) will be exposed to pollutants found in the three rivers, and a range of physiological and behavioral parameters will be examined. \n\nFinally, the terrestrial project will use sophisticated molecular biology and electro-physiology to examine the nervous systems of fruit flies from different habitats in Puerto Rico. The standard laboratory-reared fruit fly (Drosophila) is a prized and widely-used model system in neurobiology laboratories throughout the world. However, there is a paucity of studies examining this animal in the wild, especially with respect to the specific habitats in which they are living.\n\nIntellectual Merit\nThe conceptual linchpin of the PRCEN is that the nervous system is the interface between an organism and its environment; a multidisciplinary approach is essential to understand the complex interplay of molecular, cellular, organismal, and ecosystem dynamics faced by organisms under the increasingly stressful conditions created by human impacts on the environment. We refer to this approach as environmental neuroscience. The program will be unified by the central hypothesis that a full understanding of the consequences of pollution and climate change requires dialogue between investigators monitoring environmental conditions and organismal biologists using that information to determine how environment affects function. \n\nBroader Impact\nThe PRCEN center will change the way we look at environmental problems, and will create a new category of scientists prepared for the environmental challenges developing from human activities. The Center will impact a large number of minority students by tapping into the collective student population of over 19,000. Our undergraduate participants will integrate closely with ongoing NSF sponsored mentorship initiatives such as the Lewis Stokes Alliance for Minority Participation, the Research Experience for Undergraduates Program, and the Undergraduate Research Mentoring Program. Our graduate students will have access to broad training here, and will also be given the opportunity to take courses and train stateside at places like the Marine Biological Laboratory in Woods Hole, MA. Finally, our studies will integrate with local organizations such as the San Juan Bay Estuary Program to coordinate community outreach targeting K-12 education.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "2872", "attributes": { "award_id": "1914777", "title": "CREST Center for Advanced, Functional Materials: Phase II", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)", "Centers for Rsch Excell in S&T" ], "program_reference_codes": [], "program_officials": [ { "id": 8620, "first_name": "Luis", "last_name": "Cubano", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-01-31", "end_date": "2027-01-31", "award_amount": 4997433, "principal_investigator": { "id": 8625, "first_name": "Kimberley", "last_name": "Cousins", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 957, "ror": "", "name": "University Enterprises Corporation at CSUSB", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 8621, "first_name": "Timothy D", "last_name": "Usher", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 8622, "first_name": "Douglas C", "last_name": "Smith", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 8623, "first_name": "Renwu", "last_name": "Zhang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 8624, "first_name": "Sara", "last_name": "Callori", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 957, "ror": "", "name": "University Enterprises Corporation at CSUSB", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The Centers of Research Excellence in Science and Technology program provides support to enhance the research capabilities of minority-serving institutions through the establishment of centers that effectively integrate education and research. With National Science Foundation support, California State University San Bernardino will build on the accomplishments with their Phase I Center by advancing knowledge in functional materials, while providing quality undergraduate research experiences for historically underrepresented students. The Phase II Center for Advanced Functional Materials will support the development of new materials and promote understanding of structure/function relationships in a range of functional materials. The Phase II Center will continue partnerships with the University of Nebraska-Lincoln Materials Research Center, the University of Buffalo Department of Chemistry, and NASA Armstrong Research Center. New Phase II partners include California State University Santa Barbara, California State University, Pomona and the National Institute of Standards and Technology. \n\nThe U.S. Government's \"Materials Genome Initiative\" highlights the importance of functional materials development for building the technologies of the future. The Phase II Center exploits both the structure of the molecular components of the materials, as well as the formulation of single component and hybrid materials, to better understand the relationships between structure and function, working towards design of materials for practical applications. Interdisciplinary teams of researchers will push the boundaries on what is known about ferroelectric, piezoelectric, ferromagnetic and multiferroric materials. Based on systematic study of structure versus function in, for example, single crystal organic/organometallic crystalline materials, thin films of organic and inorganics, and bulk and thin film polymers; materials will be modified to enhance the desired function. Theoretical models will be used to explain observed phenomenon on a molecular level, and simulated structure design with database searching for known analogs will guide the selection of additional materials to prepare and evaluate.\n\nThe Phase II Center project will contribute to the production of the next generation of STEM workforce including underrepresented students by: 1) strengthening proven pre-college and community college recruiting strategies; 2) retaining students through experienced mentoring, relevant research, and leveraging strong support programs; and 3) career success through early internship and research experiences leading to graduate admissions, advanced degrees and STEM professions. Project enhancements include implementation of a new Master's Program in Materials Science.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14542", "attributes": { "award_id": "2345176", "title": "NSF Convergence Accelerator Track J Phase 2: Cultivate IQ - Empowering Regional Food Systems", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "Convergence Accelerator Resrch" ], "program_reference_codes": [], "program_officials": [ { "id": 26489, "first_name": "Michael", "last_name": "Reksulak", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-12-15", "end_date": null, "award_amount": 4998818, "principal_investigator": { "id": 26825, "first_name": "Meredith", "last_name": "Adkins", "orcid": null, "emails": "[email protected]", "private_emails": null, "keywords": "[]", "approved": true, "websites": "[]", "desired_collaboration": "", "comments": "", "affiliations": [] }, "other_investigators": [ { "id": 26821, "first_name": "Chase", "last_name": "Rainwater", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26822, "first_name": "Kristen E", "last_name": "Gibson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26823, "first_name": "Ngan H", "last_name": "Le", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 31187, "first_name": "Donald J", "last_name": "Malone", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 586, "ror": "", "name": "University of Arkansas", "address": "", "city": "", "state": "AR", "zip": "", "country": "United States", "approved": true }, "abstract": "Disruptions in food supply linked to the global pandemic, conflict, and climate change have exposed vulnerabilities in the globalized agricultural-food supply chain resulting in an increased focus on the risks to domestic food and nutrition security. This project will advance the practice of use-inspired convergence research and novel data-driven techniques to address the resiliency of local and regional food systems. Findings from this research will extend understanding of barriers to wholesale and institutional procurement of local food and how technological solutions can be employed. This project will democratize access to data insights by harnessing the capabilities of advanced Artificial Intelligence and Machine Learning (AI/ML) techniques, ensuring usability by historically excluded groups, including farmers of color and indigenous communities. The technology developed will support rural development and the economic livelihoods of small farmers and food businesses. Furthermore, enhanced knowledge of consumer insights and market channels will reduce food losses and enhance crop diversification, supporting climate-smart resiliency in agricultural value chains. More broadly, the technology will increase the availability of safe and nutritious local food, supporting integrative health in American communities.<br/><br/>The first phase of this use-inspired research project entailed extensive investigation of user needs and low-fidelity prototype development of Cultivate IQ, a data-driven technology platform that will strengthen the resiliency of regional food systems. In the second phase, we will build the platform components, including refinement of the computational models leveraging AI/ML to forecast market prices and demand, and deliver other production and consumer data insights to food distributors, such as food hubs, and small and mid-sized farmers. The project team includes academic and industry partners and key collaborators from the public and private sector who will deploy a technology solution at a scale that has significant implications for the grand challenge of food and nutrition security. The project aims to support producers’ access to cost of production profitability analysis, as well as user-friendly dashboards for geographically relevant and actionable data insights across key decision points in the food supply chain, such as price and consumer demand forecasting for specialty crops (fruits, vegetables, and nuts), regionally grown and processed meat, and value-added products. This key data will inform small food and farm business decisions by utilizing AI/ML techniques such as predictive models for future food demand. Additionally, the technology will leverage advances in AI/ML computer vision, alongside geospatial technologies and imagery, to analyze crops, including the identification of crop types and anomalies, vegetation index, and the estimation of cropland sizes across a region. Cultivate IQ’s market insights will create regional supply efficiencies and support production planning to meet the growing demand for local and sustainable products.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "602", "attributes": { "award_id": "2033521", "title": "A1: KnowWhereGraph: Enriching and Linking Cross-Domain Knowledge Graphs using Spatially-Explicit AI Technologies", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 1326, "first_name": "Lara", "last_name": "Campbell", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-09-01", "end_date": "2022-08-31", "award_amount": 4998900, "principal_investigator": { "id": 1331, "first_name": "Krzysztof W", "last_name": "Janowicz", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 320, "ror": "", "name": "University of California-Santa Barbara", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 1327, "first_name": "Dean A", "last_name": "Rehberger", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1328, "first_name": "Pascal", "last_name": "Hitzler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1329, "first_name": "Wenwen", "last_name": "Li", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1330, "first_name": "Mark P", "last_name": "Schildhauer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 320, "ror": "", "name": "University of California-Santa Barbara", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The NSF Convergence Accelerator supports use-inspired, team-based, multidisciplinary efforts that address challenges of national importance and will produce deliverables of value to society in the near future.The goal of this project is to improve data-driven decision making and data analytics, specifically data analytics that involve geographic data. This project will create the “KnowWhereGraph” – a knowledge graph tool that specifically enables other data-analysis knowledge tools that have a geospatial component. GeoEnrichment describes the process by which data becomes augmented with a wide range of auxiliary information tailored to a geospatial study area (such as demographic data). GeoEnrichment tools significantly reduce the costs involved in acquiring, entering, and cleaning geo-data. Unfortunately, currently available geoenrichment services provide access to only pre-defined categories of information, do not effectively handle interconnected data, offer limited support for data integration, and are generally expensive. This project plans to make data-driven decision making and data analytics substantially more effective, accessible, and affordable. The project will merge novel Artificial Intelligence-based geoenrichment technologies with a knowledge graph that brings together open, cross-domain, densely integrated data spanning the human-environment interface. This project’s work is enabled by an open, freely usable knowledge graph. These graphs are a combination of scalable, Web-standard technologies, specifications, and data cultures for representing densely interconnected statements derived from structured or unstructured data across domains, in both human and machine-readable ways. The technology tools are designed to be useful to and useable by researchers, analysts, decision-makers, and the interested public in any domain or cross-domain activity requiring geospatial intelligence. This project includes strong partnerships with non-academic and academic stakeholders including 4 for-profit organizations, 2 government agencies, and one non-profit, as well as five academic partnerships: ESRI (Geographic Information Systems); Oliver Wyman, (commodity markets and supply chains), Princeton Climate Analytics (weather and climate information services), In10T (digital agriculture, farm partnerships); US Geological Survey (USGS), Natural Resources Conservation Service within the U.S. Department of Agriculture (USDA): and DirectRelief (humanitarian aid); as well as University of California Santa Barbara(UCSB), Kansas State University (K-State), Michigan State University (MSU), Arizona State University (ASU), and University of Southern California(USC). Additional partnerships are expected to develop during this Phase II effort. The “KnowWhereGraph” will be a valuable element of the Convergence Accelerator Phase II cohort, providing geospatial tools to the other projects within the cohort. In addition the project plans to focus on several strategic application areas that are likely to benefit US society, including: COVID-19 related supply chain disruptions and the US food, agriculture, and energy sectors, and their attendant supply chains generally; environmental policy issues relative to interactions among agricultural sustainability, soil conservation practice, and farm labor; and delivery of emergency humanitarian aid, within the US and internationally. Anytime knowing “where” is key, this project’s tools may be helpful. Formally, a knowledge graph consists of a massive set of statements, constructed from inter-connected node- and edge-labeled resources, allowing multiple, heterogeneous edges for the same nodes. A collection of definitional statements specifying the meaning of the knowledge graph's vocabulary is called its (KG) schema or ontology. The ontology is critical for rigorous logical interpretation and machine-actionability. Several innovations in knowledge graph technology will drive the project: (I) creating an open, web-accessible knowledge graph, with attendant methods and tools, to enable contributions to the graph from a range of sources; (II) developing strategies for semantically lifting imagery data, such as remotely sensed imagery and drone imagery, into this graph, thereby integrating vast amounts of data; (III) developing novel spatially-explicit AI-based methods, models, and services to enable geoenrichment on top of this graph; and (IV) developing both programmatic (application program interface, API) and human-accessible interfaces for the KnowWhereGraph. By merging the flexibility, expressive power, and community-driven features of open graph technologies with multi-format geospatial data and advanced geospatial intelligence, the KnowWhereGraph is designed to become a rich, integrative information resource that can transform and converge discovery, analysis, and synthesis within and across a multitude of fields and sectors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1392, "pages": 1419, "count": 14184 } } }