Grant List
Represents Grant table in the DB
GET /v1/grants?sort=program_reference_codes
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=program_reference_codes", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=program_reference_codes", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=program_reference_codes", "prev": null }, "data": [ { "type": "Grant", "id": "768", "attributes": { "award_id": "2050640", "title": "Planning Virtual Strategies to Prepare Science and Mathematics Teachers in Mississippi", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)" ], "program_reference_codes": [], "program_officials": [ { "id": 1805, "first_name": "Susan", "last_name": "Carson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-01", "end_date": "2023-02-28", "award_amount": 124992, "principal_investigator": { "id": 1809, "first_name": "Mitchell M", "last_name": "Shears", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 396, "ror": "https://ror.org/01ecnnp60", "name": "Jackson State University", "address": "", "city": "", "state": "MS", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 1806, "first_name": "Abu O", "last_name": "Khan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1807, "first_name": "Alicia K", "last_name": "Jefferson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 1808, "first_name": "Nadine", "last_name": "Gilbert", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 396, "ror": "https://ror.org/01ecnnp60", "name": "Jackson State University", "address": "", "city": "", "state": "MS", "zip": "", "country": "United States", "approved": true }, "abstract": "This project aims to serve the national need for skilled secondary science and mathematics teachers in high-need school districts. To do so, the project seeks to lay the foundation for secondary-education certification programs adapted to the novel demands of pre- and post-COVID teaching/learning environments. Conceived initially as a response to the COVID-19 pandemic, the project aims to use technology and virtual approaches to deliver remote learning opportunities for future teachers. As such, the project will enable Jackson State University to explore the feasibility of a large-scale effort to increase use of evidence-based, distance-learning strategies in teacher education. Examples of strategies include virtual simulations, digital credentialing, and online social and emotional learning. The work will be situated in the urban setting of the Mississippi State capital. This project at Jackson State University includes partnerships with Hinds Community College and Jackson Public Schools, a high-need school district. The long-term goal of this collaborative effort is plan how to recruit, support, and graduate teachers who will help meet the shortage of science and mathematics teachers at high-need schools often staffed by rotating long- and short-term substitute teachers. The project builds on the conceptual framework of Jackson State’s College of Education and Human Development vision of the “responsive educator” who provides and embodies: 1) a Committed Response; 2) a Knowledgeable Response; 3) a Skillful Response; and 4) a Professional Response. Additionally, the project builds on the current infrastructure of the University’s Physics and Mathematics Education curriculum. The goals of this Capacity Building project are to: 1) develop evidence-based innovative models and strategies for recruiting, preparing, and supporting teachers; 2) create plans for collecting data to determine need, interest, and capacity for increasing STEM teacher development; and 3) establish the infrastructure for preparing a Track 1: Scholarship & Stipend proposal in the future. This Capacity Building project is supported through the Robert Noyce Teacher Scholarship Program (Noyce). The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 teachers to become STEM master teachers in high-need school districts. It also supports research on the persistence, retention, and effectiveness of K-12 STEM teachers in high-need school districts.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": "4096", "attributes": { "award_id": "1607069", "title": "2016 Cellular & Molecular Fungal Biology GRC, Plymouth, New Hampshire, June 19-24, 2016", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Symbiosis Infection & Immunity" ], "program_reference_codes": [], "program_officials": [ { "id": 13758, "first_name": "Michael", "last_name": "Mishkind", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2016-07-01", "end_date": "2017-06-30", "award_amount": 15000, "principal_investigator": { "id": 13759, "first_name": "Amy", "last_name": "Gladfelter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 226, "ror": "https://ror.org/05rad4t93", "name": "Gordon Research Conferences", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 226, "ror": "https://ror.org/05rad4t93", "name": "Gordon Research Conferences", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true }, "abstract": "This project will facilitate the attendance and participation of early career scientists in the Gordon Research Conference on Cellular and Molecular Fungal Biology to be held at the Holderness School, June 19-24, 2016. The goal of the conference is to disseminate information about fungal biology among an interdisciplinary group of researchers, and to increase our collective understanding of basic fungal biology and its application to socially important problems. Fungi are essential parts of the terrestrial nutrient cycle, play a central role in the development of biofuels, and produce many critically important chemicals. These diverse applications of fungi require the interdisciplinary acquisition and application of fundamental fungal biology. This project will support the convergence and exchange of new findings amongst an interdisciplinary group of scientists dedicated to the study of fungi. \n\nThe intellectual merit of the project is rooted in the meeting's highly interdisciplinary and interactive format. The meeting will feature topics that integrate multiple time and space scales for different questions in fungal biology to promote interactions amongst researchers with diverse perspectives within the community. There is a specific emphasis on integrating mathematical modeling and biophysics as a new addition to this meeting and an entire session is dedicated to the interface of fungal biology with the physical sciences. The meeting enables cross-fertilization of ideas, from cell biology to evolution, that occurs in and outside of the sessions and especially between junior and senior scientists. Young investigators emphasize from previous meetings how interactive the conference is and how responsive it is to the presentation of their work.\n\nThis conference has broad impacts on training and is dedicated to extending the research community by emphasizing women and members of underrepresented groups in inviting speakers. The current invited speakers are approximately 50% women, including several Latinas. The small size of the meeting and the emphasis on discussion (40% of meeting time is dedicated to discussions) encourages active participation. Poster sessions are featured without competing events to focus attention on the most junior scientists, who often have the newest data. The GRC on Cell and Molecular Fungal Biology also is dedicated to research that applies basic knowledge to socially important questions involving filamentous fungi, particularly mutualisms with plants (mycorrhizae), parasitism with plants (plant pathology) and animals (animal pathology), and industrial mycology (enzyme production). The interactions among researchers focused on both basic and socially important research speeds research aimed at solving societal problems caused by or that can be improved by fungi.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3328", "attributes": { "award_id": "1811163", "title": "Advancing the Design of Visualizations for Informal Science Engagement", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)", "AISL" ], "program_reference_codes": [], "program_officials": [ { "id": 10551, "first_name": "Chia", "last_name": "Shen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2018-10-01", "end_date": "2019-12-31", "award_amount": 249677, "principal_investigator": { "id": 10553, "first_name": "Jennifer", "last_name": "Frazier", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1082, "ror": "https://ror.org/0037yf233", "name": "Exploratorium", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 10552, "first_name": "Joyce", "last_name": "Ma", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1082, "ror": "https://ror.org/0037yf233", "name": "Exploratorium", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants. This project is a two-day conference, along with pre- and post-conference activities, with the goal of furthering the informal science learning field's review of the research and development that has been conducted on data visualizations that have been used to help the public better understand and become more engaged in science. The project will address an urgent need in informal science education, providing a critical first step towards a synthesis of research and technology development in visualization and, thus, to inform and accelerate work in the field in this significant and rapidly changing domain.\n\nThe project will start with a Delphi study by the project evaluator prior to the conference to provide an Emerging Field Assessment on data visualization work to date. Then, a two-day conference at the Exploratorium in San Francisco and related activities will bring together AISL-funded PIs, computer scientists, cognitive scientists, designers, and technology developers to (a) synthesize work to date, (b) bring in relevant research from fields outside of informal learning, and (c) identify remaining knowledge gaps for further research and development. The project team will also develop a website with videos of all presentations, conference documentation, resources, and links to social media communities; and a post-conference publication mapping the state of the field, key findings, and promising technologies. \n\nThe initiative also has a goal to broaden participation, as the attendees will include a diverse cadre of professionals in the field who contribute to data visualization work.\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": "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": "3840", "attributes": { "award_id": "1707069", "title": "WERF: Determining the fate and major removal mechanisms of microplastics in water and resource recovery facilities", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "EnvE-Environmental Engineering" ], "program_reference_codes": [], "program_officials": [ { "id": 12614, "first_name": "Mamadou", "last_name": "Diallo", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-08-01", "end_date": "2021-07-31", "award_amount": 304892, "principal_investigator": { "id": 12616, "first_name": "Belinda", "last_name": "Sturm", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 415, "ror": "", "name": "University of Kansas Center for Research Inc", "address": "", "city": "", "state": "KS", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 12615, "first_name": "Edward", "last_name": "Peltier", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 415, "ror": "", "name": "University of Kansas Center for Research Inc", "address": "", "city": "", "state": "KS", "zip": "", "country": "United States", "approved": true }, "abstract": "Proposal: 1707069\nPI: Belinda Sturm\n\nThe focus of this project is the fate of microplastics (plastics < 5mm) in the liquid and biosolids discharged from water resource and recovery facilities (WRRFs). Microplastics are typically entrained within activated sludge and ultimately released to the environment through biosolids. The detrimental effects of plastics on marine vertebrates is well-documented and a major environmental concern. In this project the transport pathways for plastics will be identified. The results of this study will help reduce harmful marine ecosystem impacts. The PIs will engage municipalities through a full-scale sampling campaign and will disseminate the data in a web-based database that is publically accessible. They will continue to collaborate with high school teachers to refine teaching modules dealing with topics focused on microplastics and emerging contaminants.\n\nMicroplastics are likely to be removed when they are adsorbed or entrained within the activated sludge floc structure. The main hypothesis is that the sludge structure and extracellular polymeric substances (EPS) content are controlling variables to microplastic removal. In particular, the assumption is that microbial aggregates with high surface areas and high EPS content can capture more microplastics. To test this hypothesis the PIs will conduct a survey of select WRRFs with different primary and secondary treatment processes. To further quantify microplastics capture efficiencies, the PIs will determine the effect of EPS on microplastic adsorption and retention efficiency within lab-scale and pilot-scale reactors and compare conventional and aerobic granular sludge processes for microplastic adsorption. The activated sludge process, and particularly gravity sedimentation, was not designed to remove low density microplastic particles. Microplastics are likely to be removed when they are adsorbed or entrained within the activated sludge floc structure. As microplastic loads to WRRFs increase, it is important to study the effect of niche separation of microplastic-associated microorganisms on activated sludge process performance. One outcome of the research will be a better understanding the fate of microplastics in WRRFs. Results of this project will provide a framework for comprehensive management of microplastics contamination in WRRFs.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "1024", "attributes": { "award_id": "2136142", "title": "S2I2: Impl: The Molecular Sciences Software Institute", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [], "program_officials": [ { "id": 2505, "first_name": "Richard", "last_name": "Dawes", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-01", "end_date": "2026-07-31", "award_amount": 3825190, "principal_investigator": { "id": 2510, "first_name": "Thomas D", "last_name": "Crawford", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 244, "ror": "", "name": "Virginia Polytechnic Institute and State University", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 2506, "first_name": "Shantenu", "last_name": "Jha", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 2507, "first_name": "Teresa L", "last_name": "Head-Gordon", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 2508, "first_name": "Theresa L", "last_name": "Windus", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 2509, "first_name": "Dominika", "last_name": "Zgid", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 244, "ror": "", "name": "Virginia Polytechnic Institute and State University", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "The Molecular Sciences Software Institute (MolSSI) is supported by a joint award from the Divisions of Chemistry (CHE) and Molecular and Cellular Biosciences (MCB) and the Office of Advanced Cyberinfrastructure (OAC). Since its launch in 2016, the MolSSI has served as a nexus for the broad computational molecular sciences community by providing software expertise, community engagement and leadership, and education and training. Through a broad array of software infrastructure projects, teaching workshops, and community outreach, the MolSSI catalyzes the scientific advances needed to solve emerging scientific computing Grand Challenges. In its next phase, supported by this award, the MolSSI will capitalize on this success by continuing and extending its efforts for an even broader impact on our community's ability to address key scientific areas, including developing new energy technologies, fighting COVID-19 and future pandemics, developing climate solutions, exploring quantum information sciences, artificial intelligence and machine learning, and developing a more diverse and resilient workforce.Through the MolSSI's Software Scientists – a team of software engineering experts, drawn from the molecular sciences, computer science, and applied mathematics – the Institute will promote improved interoperability of community codes, easier deployment on heterogenous computing architectures, and greater parallel scalability of existing and emerging theoretical models. The MolSSI will help train the next generation of computational molecular scientists in modern software engineering tools and best practices through its Education Initiative that annually reaches thousands of students worldwide and its Software Fellowship program, which has already benefitted nearly 100 graduate students and postdoctoral fellows across the U.S. The MolSSI's Software Workshop program will bring the community together to identify and address the highest priority challenges and the MolSSI's Discovery, Outreach, and Sustainability programs will provide a key mechanism for community buy-in, provide insight into the needs of the molecular sciences community, and facilitate interactions among its members. The MolSSI's ultimate goal is to enable new science and broader impacts by building a community of molecular scientists prepared to provide solutions to problems impacting national health, social, environmental, and economic challenges.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": "2816", "attributes": { "award_id": "1925596", "title": "CC* Compute: Accelerating Computational Research for Engineering and Science (ACRES) at Clarkson University, A Campus Cluster Proposal", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Campus Cyberinfrastructure" ], "program_reference_codes": [], "program_officials": [ { "id": 8385, "first_name": "Kevin", "last_name": "Thompson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-07-01", "end_date": "2021-06-30", "award_amount": 396950, "principal_investigator": { "id": 8387, "first_name": "Joshua", "last_name": "Fiske", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 597, "ror": "https://ror.org/03rwgpn18", "name": "Clarkson University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 8386, "first_name": "Brian", "last_name": "Helenbrook", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 597, "ror": "https://ror.org/03rwgpn18", "name": "Clarkson University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Clarkson University is building a computational cluster (ACRES: Accelerating Computation Research for Engineering and Science) to support data and computationally intensive projects aligned with Clarkson's four interdisciplinary research themes: Data Analytics, Healthy World Solutions, Advanced Materials Development, and Next Generation Healthcare. ACRES facilitates the conduct of high-impact, collaborative research that requires access to high-performance computing (HPC) resources, enables research currently not practical/feasible, and also supports student-learning opportunities through credit-bearing courses, undergraduate research, and an existing NSF REU site focusing on HPC. As a campus resource, ACRES is made available to any faculty member or student at the University according to queueing policies implemented to ensure fair-access. And, ACRES supports Clarkson's increased focus on computational research and a cluster hire of computationally active faculty. \n\nThe ACRES compute cluster replaces an existing, five-year-old high-performance compute cluster whose computational capacity provided 1.05M core-h/yr. Research need for computational capacity has grown to an identified total of 8.5M core-h/yr. ACRES is sized to meet current demands and modest near-term growth with unused computational capacity being shared via the Open Science Grid (OSG) to benefit the broader scientific community. This new computational resource provides 9.8M core-h/year through 1120 cores, high-speed Infiniband interconnect, four NVIDIA Tesla V100 GPUs, and 40 TB of scratch storage.\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": "3584", "attributes": { "award_id": "1654828", "title": "Collaborative Research: The Impact of Face-to-Face and Remote Interviewing", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)", "LSS-Law And Social Sciences" ], "program_reference_codes": [], "program_officials": [ { "id": 11632, "first_name": "Reginald", "last_name": "Sheehan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2017-05-01", "end_date": "2021-04-30", "award_amount": 145095, "principal_investigator": { "id": 11634, "first_name": "Debra", "last_name": "Poole", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1001, "ror": "https://ror.org/02xawj266", "name": "Central Michigan University", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 11633, "first_name": "Christopher", "last_name": "Davoli", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1001, "ror": "https://ror.org/02xawj266", "name": "Central Michigan University", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "Despite widespread dissemination of best-practice standards for conducting forensic interviews, many jurisdictions lack the expertise to skillfully investigate crimes involving child witnesses. An efficient way to ensure that all jurisdictions have access to highly trained child interviewers is to conduct remote (live-streaming video) forensic interviews. Remote interviewing could reduce investigative response time, spare investigative resources, and accelerate case disposition. However, the ability of remote interviewing to elicit eyewitness evidence from children has not been sufficiently tested and, therefore, will certainly prompt challenges regarding children?s testimonial reliability. The current project is a comprehensive and theoretically grounded evaluation of the effectiveness of remote interviewing of child witnesses. Results will be disseminated to scientists and forensic professionals through publications and presentations, thereby informing policies and guidelines for the use of remote forensic interviews with children. Because remote interviewing increases access to specialized expertise, project results will also impact how children are questioned by electronic means in non-forensic contexts. The project will provide research training to dozens of students at two research sites and promote greater awareness of evidence-based practice through outreach to practitioners who work with child witnesses. \n\nUsing an established paradigm that produces salient touching experiences, individual children at two sites (ages 4 to 8 years) will be told that a male assistant can no longer touch their skin when he delivers a germ education program. The assistant will touch each child once and realize an impending mistake before he completes a second touch. Afterward, children will hear a story from their parents that contains misinformation about the experience, including narrative about a nonexperienced touch. During interviews conducted in traditional face-to-face or remote formats, children will answer questions about the germ education event and answer a series of questions that tests their ability to distinguish experienced from suggested events. By comparing the completeness and accuracy of children?s testimonies across formats, this study will determine whether remote interviewing elicits testimony that is comparable in quality to the testimony elicited by face-to-face interviewing. Measures of behavioral inhibition and executive function will determine whether remote interviewing is beneficial for children who are behaviorally inhibited or contraindicated for typically-developing children who have poor cognitive control.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3072", "attributes": { "award_id": "1934962", "title": "HDR TRIPODS: Collaborative Research: Foundations of Greater Data Science", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "HDR-Harnessing the Data Revolu" ], "program_reference_codes": [], "program_officials": [ { "id": 9528, "first_name": "Huixia", "last_name": "Wang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-09-15", "end_date": "2022-08-31", "award_amount": 814165, "principal_investigator": { "id": 9534, "first_name": "Mujdat", "last_name": "Cetin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 464, "ror": "https://ror.org/022kthw22", "name": "University of Rochester", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 9529, "first_name": "Alex", "last_name": "Iosevich", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 9530, "first_name": "Daniel", "last_name": "Gildea", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 9531, "first_name": "Daniel", "last_name": "Stefankovic", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 9532, "first_name": "Tong Tong", "last_name": "Wu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 464, "ror": "https://ror.org/022kthw22", "name": "University of Rochester", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "The University of Rochester and Cornell University jointly establish the Greater Data Science Cooperative Institute (GDSC). The GDSC is based on two founding tenets. The first is that enduring advances in data science require combining techniques and viewpoints across electrical engineering, mathematics, statistics, and theoretical computer science. The investigators' goal is to forge a consensus perspective on data science that transcends any individual field. The second is that data-science research must be grounded in an application domain. This helps to ensure that assumptions about the availability and quality of data are realistic, and it allows methodological results to be tested experimentally as well as theoretically. As such, the GDSC aims to consider applications in medicine and healthcare, an important application domain and one for which advances in data science can have a direct, positive impact on society. The GDSC aims to tackle foundational questions that are motivated by problems in healthcare, obtain solutions that fuse domain expertise with application-agnostic methodologies, and ultimately yield scientific advances that impact the way healthcare is provided. The GDSC aims to leverage the physical proximity of the two institutions, and the unique strengths in each of the core disciplines above and in medicine.\n\nThe GDSC's cross-disciplinary research directions include: (i) Topological Data Analysis. The challenges that high-dimensional, incomplete, and noisy data present are great, but in many applications, exploiting the topological nature of the problem is possible. GDSC aims to develop new fundamental methods and theory to rigorously explore the promise of this unique approach. (ii) Data Representation. Data compression, embeddings, and dimension reduction play a fundamental role in data science. Inspired by new core challenges in biomedical imaging, genomics, and neural-spike training data, GDSC aims to develop novel source models and distortion measures, and ultimately seek a unifying theoretical framework across domains and disciplines. (iii) Network & Graph Learning. Many of the fundamental challenges in applying data science to non-homogeneous populations are best explored through a network or graph structure. GDSC aims to develop new techniques for parameter-dependent eigenvalue problems in spectral community detection, density-estimation methods on networks, and a theoretical framework for time-varying graphical models to study dynamic variable relations in time-evolving networks. (iv) Decisions, Control & Dynamic Learning. Sequential decisions are high-stakes in medicine. GDSC aims to utilize systems and control-engineering methods to improve health and disease management and develop new foundational theories and methods for label-efficient active learning and dynamic treatment regimes. (v) Diverse & Complex Modalities. Big data is complex data, and major new innovations are needed. GDSC aims to develop theoretical frameworks for inference under computational and privacy constraints and for high-dimensional data without parametric model assumptions. Text, image, and audio data present further challenges. To address such challenges, GDSC aims to explore transition systems for graph parsing of natural language and new fusion approaches for fully multimodal analysis. \n\nThis project is part of the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea activity.\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": "15679", "attributes": { "award_id": "1R01HL176493-01", "title": "Pathogenic Mechanism and Therapeutic Approaches for Exercise Intolerance in Post-Acute Sequelae of COVID-19", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Heart Lung and Blood Institute (NHLBI)" ], "program_reference_codes": [], "program_officials": [ { "id": 32514, "first_name": "EMMANUEL FRANCK", "last_name": "MONGODIN", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-04-01", "end_date": "2029-01-31", "award_amount": 633045, "principal_investigator": { "id": 32524, "first_name": "Michael G", "last_name": "Risbano", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32525, "first_name": "Lianghui", "last_name": "Zhang", "orcid": "", "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 848, "ror": "", "name": "UNIVERSITY OF PITTSBURGH AT PITTSBURGH", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Post-acute sequelae of COVID-19 (PASC) is an emerging public health priority with up to 18% prevalence. Noteably, almost 30% patients diagnosed with PASC experence exercise intolerance. This activity limitation continues to negatively impact our workforce, and poses a persistent socialeconimic burden on our society. Our Post-Covid Recovery Clinic, a RECOVERY Vital site, has evaluated exercise intolerant PASC for nearly 4 years. We recently discovered pathophysiologic endotypes that contribute to exercise intolerance in PASC via invasive cardiopulmonary exercise testing (iCPET). Yet, the molecular drivers for this population remain elusive. Four- years after the onset of the pandemic we are left without PASC-defining biomarkers, or targeted therapeutics. Thus, it is crucial to investigate the interconnected molecular and pathophysiologic links in exercise intolerant PASC, a task uniquely within our team’s expertise. Angiotensin-converting enzyme 2 (ACE2) is not just an entry receptor for SARS-CoV-2 but also an enzyme with a protective function through regulation of the renin- angiotensin system. Studies have shown that a high level of plasma ACE2 is associated with an increased risk of SARS-CoV-2-related mortality. Our preliminary data showed that the catalytic activity of increased plasma ACE2 was significantly impaired in the exercise intolerant PASC patients, and closely correlated with reduced exercise capacity as measured by peak oxygen consumption evaluated during iCPET. Furthermore, to study the pathogenic mechanism of exercise intolerance in PASC, we established a novel PASC mouse model. In this model, we observed the persistence of the SARS-CoV-2 RNAs in lung microvascular ECs, impaired ACE2 activity, chronic pulmonary inflammation, along with a significant reduction in exercise capacity. Thus, we hypothesize that dysfunctional ACE2 shed from pulmonary ECs is a major driver for exercise intolerance in PASC and an engineered solube ACE2 with enhanced ACE2 activity will improve exercise capacity of PASC. To test our hypotheses, we will investigate the predictive value of ACE2 activity as a clinical biomarker and assess its association with exercise capacity over 12 months in PASC patients in Aim 1. We will define an engineered soluble ACE2 with enhanced ACE2 activity as an innovative therapeutic intervention to improve exercise capacity and vascular function in the PASC mouse model in Aim 2. Furthermore, we will explore the mechanism of ACE2 dysfunction shed from the pulmonary vasculature in Aim 3. If successful, we will identify a diagnostic and therapeutic paradigm urgently needed for PASC patients experiencing exercise intolerance, and remediate the deficient response to this global public health threat.", "keywords": [ "2019-nCoV", "ACE2", "Acute Lung Injury", "Adult", "Affect", "Binding", "Biological Markers", "Blood Vessels", "COVID-19", "COVID-19 mortality", "COVID-19 patient", "Cardiopulmonary", "Cell surface", "Characteristics", "Chronic", "Circulation", "Clinic", "Clinical assessments", "Data", "Diagnosis", "Diagnostic", "Disease Progression", "Disintegrins", "Endothelial Cells", "Endothelium", "Engineering", "Enzymes", "Exercise", "Exercise Test", "Fatigue", "Functional disorder", "Health", "Impairment", "Inflammation", "Knock-in", "Knockout Mice", "Left", "Link", "Long COVID", "Lung", "Measures", "Medicine", "Metalloproteases", "Modeling", "Molecular", "Outpatients", "Oxygen Consumption", "Pathogenicity", "Pathology", "Patients", "Peptides", "Plasma", "Population", "Post-Acute Sequelae of SARS-CoV-2 Infection", "Predictive Value", "Prevalence", "Proteins", "Public Health", "Pulmonary Inflammation", "Questionnaires", "RNA", "Recovery", "Regulation", "Renin-Angiotensin System", "Risk", "SARS-CoV-2 infection", "Site", "Societies", "Symptoms", "Testing", "Therapeutic", "Therapeutic Intervention", "clinical biomarkers", "clinical infrastructure", "design", "dosage", "endothelial dysfunction", "exercise capacity", "exercise intolerance", "experience", "improved", "innovation", "knock-down", "lung microvascular endothelial cells", "mortality", "mouse model", "novel", "pandemic disease", "post SARS-CoV-2 infection", "post-COVID-19", "public health priorities", "receptor", "remediation", "research clinical testing", "response", "symptom cluster", "targeted treatment", "treatment optimization" ], "approved": true } } ], "meta": { "pagination": { "page": 1, "pages": 1392, "count": 13920 } } }