Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1385&sort=-id
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-id", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1397&sort=-id", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1386&sort=-id", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1384&sort=-id" }, "data": [ { "type": "Grant", "id": "448", "attributes": { "award_id": "2152580", "title": "CAREER: Memory-Efficient, Heterogeneity-Aware and Robust Architecture for Federated Intelligence on Edge Devices", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 886, "first_name": "Alexander", "last_name": "Jones", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-09-01", "end_date": "2026-02-28", "award_amount": 181584, "principal_investigator": { "id": 887, "first_name": "Cong", "last_name": "Wang", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 239, "ror": "https://ror.org/02jqj7156", "name": "George Mason University", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "The recent trend of migrating computation from the centralized cloud to distributed edge devices is reshaping the landscape of today’s Internet, especially under the unprecedented challenges of the COVID19 pandemic. With privacy being a critical concern in data aggregation, Federated Learning emerges as a promising solution to such privacy-utility challenge. It pushes the computation towards consumer’s edge devices, where the data is generated. By exchanging statistical information, the participants perform collaborative learning in a distributed fashion. Unfortunately, the original design still faces new system-architectural challenges from limited memory, software/hardware heterogeneity, security and statistical diversity from different edge devices. The overarching goal of this CAREER project is to design, optimize and implement a memory-efficient, heterogeneity-aware and robust architecture for federated learning on consumer’s edge devices. In particular, it aims to: 1) remove the memory barriers of running the computational-intensive learning tasks; 2) resolve the software and hardware heterogeneity among various kinds of devices; 3) secure the information exchange and the machine learning backend. The research will provide a stack of solutions to address the urging needs in realizing collaborative intelligence on edge devices with computation/memory/energy-efficiencies, security and robustness. This research will address an urgent problem to bridge the gap between the vast data available from consumer’s edge devices and the rising interest of utilizing such private data to improve our wellbeing. The algorithms and tools developed in this CAREER project will lay the foundations to a plethora of new applications on massively distributed edge devices, as the essential elements for building a smart, connected and resilient community. The CAREER program will advance STEM education by developing new educational components related to machine learning, edge computing and security. This includes diverse outreach plans of cybersecurity summer camps, junior research symposium, high school instructor mentorship, coding competitions and the inclusion of underrepresented minority and women engineers. The potential use cases will be also explored with the collaborating industrial partners to enrich their business models.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": "447", "attributes": { "award_id": "2129705", "title": "The Louis Stokes Alliances for Minority Participation (LSAMP) 2021 Principal Investigators/Project Directors Meeting", "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": 884, "first_name": "Martha", "last_name": "James", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-15", "end_date": "2022-07-31", "award_amount": 215422, "principal_investigator": { "id": 885, "first_name": "Christopher", "last_name": "Botanga", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 238, "ror": "https://ror.org/05ekwbr88", "name": "Chicago State University", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 238, "ror": "https://ror.org/05ekwbr88", "name": "Chicago State University", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "The Louis Stokes Alliances for Minority Participation (LSAMP) program assists universities and colleges in diversifying the science, technology, engineering, and mathematics (STEM) workforce through their efforts at significantly increasing the numbers of students from historically underrepresented minority populations(African-Americans, Hispanic Americans, American Indians or Alaska Natives, NativeHawaiians or Other Pacific Islanders) to successfully complete high-quality degree programs in STEM. Chicago State University will lead an Organizing Committee to develop and hold a Principal Investigators/Project Directors (PI/PD) meeting. The conference will take place in a hybrid format over two days at the beginning of October, with both in-person attendance and virtual attendance at all the in-person sessions. The meeting will provide a forum for discussing the accomplishments of the program over the last 30 years, as well as the challenges and opportunities going forward, especially in light of COVID19 impacts. All LSAMP PIs and PDs will be invited to the meeting. As the last LSAMP PI/PD meeting was held in 2019, this meeting will provide the opportunity to foster and renew connections, to share information and resources gained in addressing pandemic-related issues, and plot a course going forward for the LSAMP community to meet the challenges of post-pandemic academia for groups underrepresented in STEM.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": "446", "attributes": { "award_id": "2044841", "title": "CAREER: Memory-Efficient, Heterogeneity-Aware and Robust Architecture for Federated Intelligence on Edge Devices", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 882, "first_name": "Alexander", "last_name": "Jones", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-01", "end_date": "2021-10-31", "award_amount": 0, "principal_investigator": { "id": 883, "first_name": "Cong", "last_name": "Wang", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 237, "ror": "", "name": "Old Dominion University Research Foundation", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 237, "ror": "", "name": "Old Dominion University Research Foundation", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "The recent trend of migrating computation from the centralized cloud to distributed edge devices is reshaping the landscape of today’s Internet, especially under the unprecedented challenges of the COVID19 pandemic. With privacy being a critical concern in data aggregation, Federated Learning emerges as a promising solution to such privacy-utility challenge. It pushes the computation towards consumer’s edge devices, where the data is generated. By exchanging statistical information, the participants perform collaborative learning in a distributed fashion. Unfortunately, the original design still faces new system-architectural challenges from limited memory, software/hardware heterogeneity, security and statistical diversity from different edge devices. The overarching goal of this CAREER project is to design, optimize and implement a memory-efficient, heterogeneity-aware and robust architecture for federated learning on consumer’s edge devices. In particular, it aims to: 1) remove the memory barriers of running the computational-intensive learning tasks; 2) resolve the software and hardware heterogeneity among various kinds of devices; 3) secure the information exchange and the machine learning backend. The research will provide a stack of solutions to address the urging needs in realizing collaborative intelligence on edge devices with computation/memory/energy-efficiencies, security and robustness. This research will address an urgent problem to bridge the gap between the vast data available from consumer’s edge devices and the rising interest of utilizing such private data to improve our wellbeing. The algorithms and tools developed in this CAREER project will lay the foundations to a plethora of new applications on massively distributed edge devices, as the essential elements for building a smart, connected and resilient community. The CAREER program will advance STEM education by developing new educational components related to machine learning, edge computing and security. This includes diverse outreach plans of cybersecurity summer camps, junior research symposium, high school instructor mentorship, coding competitions and the inclusion of underrepresented minority and women engineers. The potential use cases will be also explored with the collaborating industrial partners to enrich their business models.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": "445", "attributes": { "award_id": "2044107", "title": "SCC-CIVIC-PG Track A:CaReDeX: Enabling Disaster Resilience in Aging Communities via a Secure Data Exchange", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 876, "first_name": "Linda", "last_name": "Bushnell", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-01-15", "end_date": "2021-06-30", "award_amount": 49999, "principal_investigator": { "id": 881, "first_name": "Nalini", "last_name": "Venkatasubramanian", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 177, "ror": "", "name": "University of California-Irvine", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 877, "first_name": "Nikil D", "last_name": "Dutt", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 878, "first_name": "Sharad", "last_name": "Mehrotra", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 177, "ror": "", "name": "University of California-Irvine", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, { "id": 879, "first_name": "Julie M", "last_name": "Rousseau", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 880, "first_name": "LIsa M", "last_name": "Gibbs", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 177, "ror": "", "name": "University of California-Irvine", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Disasters over the years have shown that a disproportionate number of older adults suffer fatalities and injuries during extreme events. A large number of older adults live in age-friendly communities and senior health facilities (SHFs) that promote independent living. During a crisis, older adults are often unable to shelter safely in place or evacuate on their own due to a range of physical conditions (need for life-sustaining equipment, impaired mobility) and cognitive afflictions (e.g. dementia, Alzheimer’s). Seamless access to information about the living facilities (e.g., floor plans, operational status, number of residents) and about the residents (e.g.,health conditions such as need for dialysis, oxygen, personal objects to reduce anxiety) can empower first responders to improve response outcomes during disasters. Such information, typically held by caregivers and in the logs maintained by the organizations, is inaccessible and/or unavailable at the time of response. This proposal seeks to create a novel community contributed data-exchange platform, entitled CareDEX, that will empower organizations to readily assimilate, ingest, store and exchange information, both apriori and in real-time, with response agencies to protect and care for the elderly in extreme events. Using CareDEX, SHFs will be able to share information about an individual’s changing health conditions, their personalized needs and identify those in need of specialized triage and critical care. Given the sensitive nature of personal information, e.g. health profiles, ability status, CareDEX will incorporate techniques to balance the need for individual privacy with authorized release of information to responders when needed. The pilot 4-month planning effort will involve 2 workshops and a demonstration pilot study that will focus on bringing stakeholders from the emergency response and senior living communities to identify specific information needs, design protocols for collection and sharing of such data, and explore privacy/security concerns. The workshops and pilot will address simulated emergency scenarios, e.g a wildfire event requiring evacuation of seniors and a complex event when the fire occurs during a pandemic such as Covid19. The goal of the workshops would be to help identify the requirements which will guide the research, design, and development of CareDEX. The planning workshops will engage a diverse group of students and postdoctoral researchers and thereby contribute to the education of the next generation of citizens in interdisciplinary topics that are relevant to communities worldwide.This project is in response to Track B - CIVIC Innovation Challenge - Resilience to Natural Disasters a collaboration with NSF and the Department of Homeland Security.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": "444", "attributes": { "award_id": "2031647", "title": "Connecting Researchers in Sharing and Re-Use of Research Data and Software", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 874, "first_name": "Martin", "last_name": "Halbert", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-12-01", "end_date": "2022-11-30", "award_amount": 46793, "principal_investigator": { "id": 875, "first_name": "Guenter", "last_name": "Waibel", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 236, "ror": "", "name": "University of California, Office of the President, Oakland", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 236, "ror": "", "name": "University of California, Office of the President, Oakland", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Open science practices have gained widespread adoption, globally, with the help of federal funding andpublisher policies, as well as the increasing visibility and growing awareness of the value of sharingwork. This has been largely evident in light of the current COVID19 pandemic, with data sharing drivingmany areas of research, and open software resources must evolve to meet the needs of researchers. To meet the emerging demands and growing requirements of the research community who need support for both data and software sharing, Dryad and California Digital Library partnered in 2018 and Dryad and Zenodo partnered in 2019. These partnerships have allowed for the three organizations to re-think the data and publishing processes, explore ways for data curation, software preservation, and for output re-use to be tied together more seamlessly. This project is a one-day, invitational workshop bringing together researchers and adjacent community members with diverse backgrounds to discuss needs, challenges, and priorities for re-using research data and software. The goal of the meeting is to develop pathways for consistent engagement with individuals and groups across the diverse scientific disciplines in order to be connected with and responsive to researchers' needs and goals. Meeting topics include dataset re-use, deposition guidance, curation standards and requirements, integrations and relationships between data and code, and advocacy and adoption. The anticipated outputs are a set of requirements and needs to better enable data and software sharing and re-use.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": "443", "attributes": { "award_id": "1618919", "title": "RCN: EcoHealth Net 2.0: A One Health approach to disease ecology research & education", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 868, "first_name": "Samuel", "last_name": "Scheiner", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2016-09-01", "end_date": "2022-08-31", "award_amount": 499897, "principal_investigator": { "id": 873, "first_name": "Jonathan H", "last_name": "Epstein", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 869, "first_name": "Christine K", "last_name": "Johnson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 276, "ror": "", "name": "University of California-Davis", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, { "id": 870, "first_name": "Aaron Bernstein", "last_name": "Dr.", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 871, "first_name": "Deborah T", "last_name": "Kochevar", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 872, "first_name": "Nitish", "last_name": "Debnath", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 234, "ror": "", "name": "Ecohealth Alliance inc.", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "EcoHealthNet 2.0 is global research coordination network led by EcoHealth Alliance and a strong array of scientists and institutional partners from the US and abroad. The global health community is facing increasingly complex challenges related to infectious disease. The majority of emerging diseases, such as Ebola virus, Zika virus, SARS and pandemic influenza originate in animal populations. Many disease outbreaks occur when people alter their environment (e.g., agricultural expansion, deforestation) such that contact between wildlife, livestock, and human communities is increased. Currently, scientists, public health practitioners, and policy makers are not adequately prepared to address complex global health challenges due to limited opportunities for interdisciplinary training at undergraduate, graduate or professional stages. The EcoHealth Net 2.0 project is designed to change the current science education landscape and develop a new generation of interdisciplinary scientists who will be better prepared to study, prevent and respond to environmental changes and infectious disease. This project will develop and deliver content to thousands of students and educators on a global scale, mentor ecohealth research scientists, and create lasting connectivity among scientists and policy makers from different disciplines as they advance in their careers and face complex challenges in global health. EcoHealthNet 2.0 will connect world-class research scientists from fields of medicine, ecology, veterinary medicine, epidemiology, microbiology, anthropology, climate science, data science, and economics with undergraduate and graduate STEM students from around the world to advance One Health research and education. The program has three core activities: (1) Didactic training: Selected lectures will be hosted at partner universities coupled with three 1-week workshops that will provide multidisciplinary educational opportunities for undergraduate and graduate students from the US and abroad. Workshops will teach applied skills in fields of disease ecology, science communication, and policy, providing in-person contact time with working professionals and research scientists. Lectures will be publicly webcast, reaching thousands of students and educators globally. (2) Experiential learning: Undergraduate and graduate students will be competitively selected to participate in mentored research projects that teach One Health principles and research methods. (3) Professional networking: Participants will be connected to scientific agencies and professional science and policy associations such as the USGS National Wildlife Health Center, the US Agency for International Development, the Institute of Medicine, the UN Food and Agriculture Organization, the International Association for Ecology and Health, and the One Health Alliance of South Asia.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "442", "attributes": { "award_id": "1318788", "title": "III: Small: Data Management for Real-Time Data Driven Epidemic Spread Simulations", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 864, "first_name": "Sylvia", "last_name": "Spengler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2013-09-01", "end_date": "2018-08-31", "award_amount": 515602, "principal_investigator": { "id": 867, "first_name": "K. Selcuk", "last_name": "Candan", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 865, "first_name": "Gerardo", "last_name": "Chowell-Puente", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 300, "ror": "", "name": "Georgia State University Research Foundation, Inc.", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true } ] }, { "id": 866, "first_name": "Maria Luisa", "last_name": "Sapino", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "The speed with which recent pandemics had immense global impact highlights the importance of realtime response and public health decision making, both at local and global levels. For instance, the SARS (Severe Acute Respiratory Syndrome) epidemic is estimated to have started in China in November 2002, had spread to 29 countries by August 2003, and generated a total of 916 confirmed deaths. A pandemic similar to the swine flu in 2009 is estimated to cost $360 billion in a mild scenario to the global economy and up to $4 trillion in an ultra scenario, within just the first year of the outbreak. Today, the key arsenal in the hands of decision makers who try to plan for and/or react to these outbreaks is software that enable model-driven epidemics and as well as the impacts of pharmaceutical and computer simulations for disease spreading. These software help predict geo-temporal evolution of non-pharmaceutical control measures and interventions, relying on data and models including social contact networks, local and global mobility patterns of individuals, transmission and recovery rates, and outbreak conditions. Unfortunately, because of the volume and complexity of the data and the models, the varying spatial and temporal scales at which the key transmission processes operate and relevant observations are made, today running and interpreting simulations to generate actionable plans are extremely difficult.If effectively leveraged, models reflecting past outbreaks, existing simulation traces obtained from simulation runs, and real-time observations incoming during an outbreak can be collectively used for obtaining a better understanding of the epidemic's characteristics and the underlying diffusion processes, forming and revising models, and performing exploratory, if-then type of hypothetical analyses of epidemic scenarios. More specifically, the proposed epidemic simulation data management system (epiDMS) will address computational challenges that arise from the need to acquire, model, analyze, index, visualize, search, and recompose, in a scalable manner, large volumes of data that arise from observations and simulations during a disease outbreak. Consequently, epiDMS fill an important hole in data-driven decision making during health-care emergencies and, thus, will enable applications and services with significant economic and health impact.The key observation is that the modeling and execution can be significantly reduced using a data-driven approach that supports data and simulation reuse in new settings and contexts. Relying on this observation, in order to support data-driven modeling and execution of epidemic spread simulations, this team will develop+ an epidemic data and model store (epiStore) to support acquisition and integration of relevant data and models.+ a novel networks-of-traces (NT) data model to accommodate multi-resolution, interconnected and inter-dependent, incomplete/imprecise, multi-layer (networks), and temporal (time series or traces) epidemic data.+ algorithms and data structures to support indexing of networks-of-traces (NT) data sets, including extraction of salient multi-variate temporal features from inter-dependent parameters, spanning multiple simulation layers and geo-spatial frames, driven by complex dynamic processes operating at different resolutions.+ algorithms to support the analysis of networks-of-traces (NT) datasets, including identification of unknown dependencies across theinput parameters and output variables spanning the different layers of the observation and simulation data.The proposed NT data model and algorithms will be brought together in an epidemic simulation data management system (epiDMS). For broadest impact, the proposed epidemic simulation data management system (epiDMS) will be designed in a way that interfaces with the popular Global Epidemic and Mobility (GLEaM) simulation engine, a publicly available software suit to explore epidemic spreading scenarios at the global scale. To achieve necessary scalabilities, epiDMS will employ novel multiresolution data partitioning and resource allocation strategies and will leverage massive parallelism.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "441", "attributes": { "award_id": "1257773", "title": "Stress hormone effects on disease resistance, tolerance and transmission", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 861, "first_name": "Irwin", "last_name": "Forseth", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2013-08-15", "end_date": "2019-07-31", "award_amount": 610123, "principal_investigator": { "id": 863, "first_name": "Lynn", "last_name": "Martin", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 235, "ror": "https://ror.org/032db5x82", "name": "University of South Florida", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 862, "first_name": "Thomas R", "last_name": "Unnasch", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 235, "ror": "https://ror.org/032db5x82", "name": "University of South Florida", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "Superspreaders are disproportionately responsible for the infections of other hosts. Perhaps the best-known human superspreader was Typhoid Mary, who caused 53 deaths due to Salmonella bacteria transmission. Although the frequency of \"Typhoid Marys\" is unclear, they are probably not rare. Superspreading is implicated in the rapid expansion of SARS (Sudden Acute Respiratory Syndrome) and HIV across the globe. For most infectious diseases, 20% of hosts cause 80% of infections. The goal of this research is to determine whether glucocorticoids, major vertebrate stress hormones that have been implicated in disease transmission, are involved in superspreading. Stress hormones could impact superspreading by affecting how parasites (or vectors, such as mosquitos and biting flies) choose hosts on which to feed, how hosts resist or tolerate parasites, or how hosts transmit parasites to other hosts or vectors. Surprisingly, there has never been a systematic study of the effects of stress hormones on all aspects of one complex host-vector-parasite system. This knowledge gap is significant and deserves attention because many anthropogenic and natural factors alter stress hormone regulation, and these factors are increasingly important in the context of global change. By knowing how and when stress hormones affect host-parasite interactions, we may become better able to predict and control zoonotic disease outbreaks. Intellectual merit: To investigate the role of stress hormones in superspreading, interactions among zebra finches (ZEFI), Culex pipiens mosquitos, and West Nile virus (WNV) will be studied. WNV was chosen because it has decimated some songbird populations and is thought responsible for more than 33,000 human infections and 1150 deaths. ZEFI and Culex were chosen because their genomes have been sequenced, providing opportunities for strong experimental approaches. Stress hormones are predicted to impact i) ZEFI behavior to Culex exposure, ii) Culex blood-feeding preference on ZEFI, iii) ZEFI resistance to WNV infection, iv) ZEFI tolerance of WNV infection, and/or v) ZEFI competency to transmit WNV to Culex. Ultimately, data will be used to determine directly when stress hormones have the largest impacts, information valuable for human and wildlife populations.Broader impacts: In animals, superspreading appears important for the transmission of several zoonotic diseases (infections that spill from animal into human populations) such as West Nile virus and some hantaviruses. In the context of global change, basic research on understanding superspreading has significant societal value because zoonotic diseases are predicted to become more prevalent. Collaboration with the Tampa Museum of Science and Industry, which attracts more than one million guests annually, will include the development of a Science Works Theater that helps the public understand disease ecology. Training workshops for Hillsborough County high school teachers will also be held, providing teachers tools to train incipient scientists in modern disease biology. For USF students, about 40% of whom come from under-represented backgrounds, robust learning experiences will be provided. Individuals on the project will learn animal husbandry, minor surgeries, how to work in a high-security infectious disease research facility, modern lab assays, data analysis, and scientific writing.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "440", "attributes": { "award_id": "955897", "title": "EcoHealthNet: Ecology, Environmental Science and Health Research Network", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [], "program_officials": [ { "id": 855, "first_name": "Samuel", "last_name": "Scheiner", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2010-09-01", "end_date": "2015-08-31", "award_amount": 497121, "principal_investigator": { "id": 860, "first_name": "Peter", "last_name": "Daszak", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 234, "ror": "", "name": "Ecohealth Alliance inc.", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 856, "first_name": "Gregory E", "last_name": "Glass", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 857, "first_name": "Jonathan A", "last_name": "Patz", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 858, "first_name": "Alonso", "last_name": "Aguirre", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 859, "first_name": "Jonathan H", "last_name": "Epstein", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 234, "ror": "", "name": "Ecohealth Alliance inc.", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] } ], "awardee_organization": { "id": 234, "ror": "", "name": "Ecohealth Alliance inc.", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Infectious diseases play a key role in ecosystems: regulating wildlife populations, mediating inter-specific competition, causing dramatic population declines, even driving local extinctions of wildlife. During the last two decades, ecologists have led the growth of a new field of disease ecology, developing theoretical and practical research that understands these interactions. However, integration of disease ecology into veterinary and human health sciences has been slow, partly due to the slow response of health science curricula to incorporate these advances. This lack of integration, and the significance of pathogens shared among animals and humans (zoonoes) has led to repeated calls for increased collaboration among ecologists, veterinarians and public health researchers. The objective of this award is to develop \"EcoHealthNet,\" a new \"Ecohealth Alliance\" linking Centers of Excellence in NGOs, Universities, and Research Societies and fusing the fields of Conservation Medicine, Medical Geography, and the \"One Medicine\" or \"One Health\" concept. EcoHealthNet will fill a critical role in bringing together ecologists, environmental biologists and the disciplines more traditionally involved in infectious diseases - veterinary medical, human medical and public health researchers. It will provide mentored training opportunities for more than 100 graduate students, openly recruited from the medical (human and veterinary), ecological, epidemiological, microbiological, economic, and environmental science fields. The training will include workshops in epidemiology, mathematical modeling of infectious disease, and field epidemiology; and international applied field research in ongoing, well-supported programs such as the ecology of Nipah virus, Avian Influenza, rodent pathogen diversity in urban America; West Nile Virus and SARS ecology. Over the five years of this project, over 100 students from diverse backgrounds will be trained in tackling the global problem of emerging diseases which threaten wildlife conservation, public health and development. Research findings will be disseminated through peer-reviewed publications, media interviews, conference presentations, and congressional briefings, in close collaboration with national and intergovernmental agencies that cover conservation, development, trade issues, and public health. Network members will help make data publicly available via online databases, via the student section of the International EcoHealth Association, the Wildlife Trust Alliance and the EcoHealth Alliance.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "439", "attributes": { "award_id": "2214320", "title": "RAPID: STEM faculty support to address impacts from COVID-19 on Tribal Colleges and Universities Program institutions", "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": 853, "first_name": "Lura", "last_name": "Chase", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-03-01", "end_date": "2023-02-28", "award_amount": 169465, "principal_investigator": { "id": 854, "first_name": "Paula", "last_name": "Roth", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 165, "ror": "https://ror.org/05mchsq43", "name": "Keweenaw Bay Ojibwa Community College", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 165, "ror": "https://ror.org/05mchsq43", "name": "Keweenaw Bay Ojibwa Community College", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "A goal of the Tribal Colleges and Universities Program (TCUP) is to increase the science, technology, engineering and mathematics (STEM) instructional and research capacities of specific institutions of higher education that serve the Nation's indigenous students. Expanding the STEM curricular offerings at these institutions expands the opportunities of their students to pursue challenging, rewarding careers in STEM fields, provides for research studies in areas that may be culturally significant, and encourages a community and generational appreciation for science and mathematics education, and sustainability of capacity gains is significantly enhanced by retaining the talent of credentialed STEM faculty. This project aligns directly with that goal.The coronavirus pandemic of 2020 caused major disruptions to institutions of higher education. However, for tribal colleges and universities, whose core operating funds are directly aligned with student enrollment, drops in enrollment equate to loss of funding. To mitigate against detrimental effects on STEM instructional capacity, this award will support the position of one full-time STEM faculty member, as well as other resources to maintain Keweenaw Bay Ojibway Community College’s STEM program as it recovers from the impact of the pandemic.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": 1385, "pages": 1397, "count": 13961 } } }