Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=3&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=4&sort=-program_reference_codes", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=-program_reference_codes" }, "data": [ { "type": "Grant", "id": "1986", "attributes": { "award_id": "2030865", "title": "Collaborative Research: RAPID: Forest productivity and expression in a low-emissions present: A RAPID response to the COVID-19 Emissions Reduction Event", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [ "7914" ], "program_officials": [ { "id": 5303, "first_name": "Elizabeth", "last_name": "Blood", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-15", "end_date": "2021-06-30", "award_amount": 2163, "principal_investigator": { "id": 5304, "first_name": "Nathan G", "last_name": "Swenson", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "State and federal policies have significantly limited human activities to keep the U.S. population safe during the COVID-19 pandemic. This has resulted in a significant decrease of atmospheric inputs from the reduction in automobile and air travel. The unprecedented and dramatic reduction in traffic in major metropolitan areas where emissions are consistently high is transforming the atmosphere, even at continental scales. The COVID-19 event presents a unique, ephemeral, and rare opportunity to study how forests would respond to dramatically cleaner air in the United States. This award will explore how North American forests that have experienced a life-time of the byproducts of human transportation respond by examining responses from the genetic and molecular levels to the forest scale. The research will be conducted at a large forest plot near the Washington DC metropolitan area with a long history of forest research and adjacent to a National Ecological Observatory Network (NEON) tower. These linkages provide opportunities to scale the molecular research to potential ecosystem responses to emissions reduction efforts. The Education Office at Smithsonian Environmental Research Center (SERC), which works with thousands of high school students and their teachers every year will incorporate results into classroom activities at the SERC Education Center.Knowing how trees and forested ecosystems respond to a transformed atmosphere is critical for providing projections of the Earth system under ongoing global change. This proposal provides a unique opportunity to explore the potential consequences of future policy by evaluating what could happen if emissions were dramatically reduced. The project provides an unprecedented opportunity to study the impacts from the genomic, physiological, population, community, ecosystem level given the ongoing research at these levels and leveraging existing infrastructure and data provided by the Smithsonian (Forest GEO), US Forest Service (FIA plots), and NSF (NEON). The research will focus on gene expression profiles of two species (beech and red maple) to explore whether they will exhibit parallel shifts favoring maximal growth in all size classes compared to pre-Covid-19 conditions. The research will examine how leaf chlorophyll content at the end of the growing season will predict gene expression differences. The research will also explore gene pathways that deal with reactive oxidative stress (ROS) reactions, repair, and stress signaling and the physiological responses for growth and reproduction for this and next growing seasonThis 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": "1423", "attributes": { "award_id": "2035153", "title": "RAPID: Time-critical Airborne Measurements to Quantify Ozone Impacts of Emissions Changes during the COVID-19 Pandemic Response in the United States", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)" ], "program_reference_codes": [ "7914" ], "program_officials": [ { "id": 3682, "first_name": "Sylvia", "last_name": "Edgerton", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-07-01", "end_date": "2021-06-30", "award_amount": 199418, "principal_investigator": { "id": 3684, "first_name": "Eric", "last_name": "Kort", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3683, "first_name": "Mackenzie L", "last_name": "Smith", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "This RAPID project will investigate the atmospheric impacts of the large changes in pollutant emissions due to the massive social and economic slowdown of activity related to the Covid-19 pandemic in the U.S. The research includes the conduct of systematic light aircraft flights to survey urban and industrial emissions sources in the atmospheres of Denver CO and Houston TX to assess the effects of the emissions changes on the production of ozone. Quantifying the impact of such a large emissions change on urban ozone formation rates and yields provides a rigorous and nearly unprecedented check on the models used for U.S. regulatory and research purposes.The researchers will conduct twenty 5-hour research flights surveying concentrations of ozone (O3), nitrogen oxides (NOx), carbon monoxide (CO), carbon dioxide (CO2), methane (CH4), and water vapor (H2O) in the atmosphere over the cities of Houston TX and Denver CO. The scientists will collaborate with both academic and government modelers to infuse the unique data from this study into a 3-D WRF-Chem research chemical transport model (CTM) to challenge and improve the representation of ozone chemistry, both for this acute situation and under routine emissions scenarios. Historical, highly detailed, research-quality atmospheric data are available for both cities, including data from recent field campaigns in Denver and in Houston. Both cities represent tractable area sources appropriate for study using light aircraft. Houston and the surrounding areas are home to the majority of the U.S. gasoline refining capacity, as well as significant petrochemical industrial capacity. Denver has a substantial number of mobile sources and the region hosts a high level of oil and natural gas activity. This research will provide a benchmark for chemical rates and yields in models. The project takes advantage of this unique opportunity to assess the effects of dramatically changed emissions on ozone production and will gather the data needed to challenge and improve regulatory and research models in the U.S.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": "1919", "attributes": { "award_id": "2037958", "title": "RAPID: The Long-Term Effects of Covid-19: Decisions, Discovery, and Impact in the Space Sciences", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [ "7914" ], "program_officials": [ { "id": 5094, "first_name": "Mary", "last_name": "Feeney", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-09-15", "end_date": "2022-08-31", "award_amount": 163564, "principal_investigator": { "id": 5095, "first_name": "Janet A", "last_name": "Vertesi", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 191, "ror": "https://ror.org/00hx57361", "name": "Princeton University", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 191, "ror": "https://ror.org/00hx57361", "name": "Princeton University", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true }, "abstract": "What will happen to science in the wake of COVID-19? Between present work disruptions and a forthcoming recession, we expect significant challenges for federally-funded science. COVID-19 catches scientists in a double bind of both strained budgets and social distancing in the laboratory that make sustaining research programs much more complicated than before. The virus’ varied impact in different states also complicates researcher’s collaborations across different institutions. The tough decisions that scientists make now to navigate the current crisis will have an impact on the coming generation of scientists’ careers, research, and experiments. To examine COVID-19’s emerging impacts on science, we look to a case of federally-funded big science disrupted by the current crisis: planetary and space sciences. These scientists and engineers collaborate on long-term projects that build and command spacecraft that explore the solar system. Through online participation and interviews, we will analyze how planetary scientists build the tools and maintain the relationships they need to get the job done, while largely confined to their homes. Building upon previous NSF-supported research, we will develop a repertoire for action, indicating what scientific communities can do to weather the storm, keep lines of discovery open, maintain investments in diversity and in infrastructure, and organize successful lobbying efforts. In this way we can help to ensure the broadest possible outcomes and benefits from public investment in science during the crisis. This project examines how the relational work of infrastructuring science hold up under extreme economic crisis, and social distancing. The research will examine how researchers plan for the future in uncertain times, how computer-mediated communication impacts decision-making, and how economic and social crises impact diversity initiatives in the sciences. Responses to financial crises shape the social and intellectual organization of science at the level of everyday practice and over the long durée. Further, moments of crisis help surface the often-invisible social relations that scientists depend upon to get the job done. The present COVID-19 crisis, however, makes past periods of uncertainty appear trivial in scale and scope. This project undertakes a rapid-response one-year observational period among the planetary science community, seizing the opportunity to follow a scientific community in depth at its time of greatest potential transformation during a period that promises long-term consequences of decades or more. This federally-funded science is experiencing considerable effects of the crisis, with laboratories are shut down or open under social distancing guidelines, expanding the timeline and expense associated with project delivery, and disruption to established patterns of collaboration. Further, planetary scientists will produce their decadal survey this year: a community engagement study conducted once every ten years to determine the coming decade’s priorities for spacecraft development and scientific investment. As a result, decisions with lasting import will be made in ephemeral, fleeting video-conferenced meetings and text messages, available for a digital ethnographer to attend on the spot but impossible to retrieve after the fact. Using virtual ethnography and online interviews this project will follow three future missions -- the developing Europa Clipper, a proposed mission to Neptune, and an Interstellar Probe – and this year's planned Decadal Survey. The project will also examine the social media conversations that now constitute frontstage chatter among scientists. Examining these ephemeral and undocumented critical interactions will allow the researchers to document a crucial year in the history of the field and to develop novel insights into the relationship between governance and scientific outcomes, discovery, and impact. They will also develop a science funding continuity toolkit for publicly-funded scientists to take action, indicating what scientific communities can do to weather the storm, keep lines of discovery open, maintain workforce diversity, and maximize scientific impact in unprecedented times.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": "1993", "attributes": { "award_id": "2030862", "title": "Collaborative Research: RAPID: Forest productivity and expression in a low-emissions present: A RAPID response to the COVID-19 Emissions Reduction Event", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)" ], "program_reference_codes": [ "7914" ], "program_officials": [ { "id": 5326, "first_name": "Elizabeth", "last_name": "Blood", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-05-15", "end_date": "2022-04-30", "award_amount": 106942, "principal_investigator": { "id": 5328, "first_name": "Sean M", "last_name": "McMahon", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 711, "ror": "https://ror.org/01pp8nd67", "name": "Smithsonian Institution", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 5327, "first_name": "Melissa", "last_name": "McCormick", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 711, "ror": "https://ror.org/01pp8nd67", "name": "Smithsonian Institution", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true }, "abstract": "State and federal policies have significantly limited human activities to keep the U.S. population safe during the COVID-19 pandemic. This has resulted in a significant decrease of atmospheric inputs from the reduction in automobile and air travel. The unprecedented and dramatic reduction in traffic in major metropolitan areas where emissions are consistently high is transforming the atmosphere, even at continental scales. The COVID-19 event presents a unique, ephemeral, and rare opportunity to study how forests would respond to dramatically cleaner air in the United States. This award will explore how North American forests that have experienced a life-time of the byproducts of human transportation respond by examining responses from the genetic and molecular levels to the forest scale. The research will be conducted at a large forest plot near the Washington DC metropolitan area with a long history of forest research and adjacent to a National Ecological Observatory Network (NEON) tower. These linkages provide opportunities to scale the molecular research to potential ecosystem responses to emissions reduction efforts. The Education Office at Smithsonian Environmental Research Center (SERC), which works with thousands of high school students and their teachers every year will incorporate results into classroom activities at the SERC Education Center.Knowing how trees and forested ecosystems respond to a transformed atmosphere is critical for providing projections of the Earth system under ongoing global change. This proposal provides a unique opportunity to explore the potential consequences of future policy by evaluating what could happen if emissions were dramatically reduced. The project provides an unprecedented opportunity to study the impacts from the genomic, physiological, population, community, ecosystem level given the ongoing research at these levels and leveraging existing infrastructure and data provided by the Smithsonian (Forest GEO), US Forest Service (FIA plots), and NSF (NEON). The research will focus on gene expression profiles of two species (beech and red maple) to explore whether they will exhibit parallel shifts favoring maximal growth in all size classes compared to pre-Covid-19 conditions. The research will examine how leaf chlorophyll content at the end of the growing season will predict gene expression differences. The research will also explore gene pathways that deal with reactive oxidative stress (ROS) reactions, repair, and stress signaling and the physiological responses for growth and reproduction for this and next growing seasonThis 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": "1362", "attributes": { "award_id": "2037368", "title": "EAGER: Exploring impacts of scholarships, cross-institutional networks, and co-curricular activities on Navajo student and faculty leadership development", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)" ], "program_reference_codes": [ "7699", "7916" ], "program_officials": [ { "id": 3511, "first_name": "Brandon", "last_name": "Jones", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-10-31", "end_date": "2022-10-31", "award_amount": 9113, "principal_investigator": { "id": 3512, "first_name": "JENNY S", "last_name": "NAKAI", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 170, "ror": "https://ror.org/05fs6jp91", "name": "University of New Mexico", "address": "", "city": "", "state": "NM", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 170, "ror": "https://ror.org/05fs6jp91", "name": "University of New Mexico", "address": "", "city": "", "state": "NM", "zip": "", "country": "United States", "approved": true }, "abstract": "This project will examine the impacts of scholarship support, opportunities to participate in network activities across institutions, virtual workshops, and discussion of issues impacting well-being and persistence with peers and mentors on retention and leadership development of students, recent graduates, and faculty in geoscience, environmental science, and related STEM fields. The PIs will support network building activities between the University of New Mexico, Navajo Technical University, Dine College, and the Center for Diverse Leadership in Science (CDLS). The project will support a new faculty fellows program and early career fellows program with participants from partnering institutions. Leadership development for faculty fellows will include committing to utilizing more inclusive teaching and mentoring practices over the course of this grant which would support Navajo student retention. To develop leadership capacity in early career fellows, the PIs will engage in cross-cultural interaction, develop a mentoring network, and provide opportunities for connection with students, recent graduates, and faculty from multiple institutions and through CDLS. Student retention and leadership development will also benefit from multiple activities: 1) Financial support via stipends for students and recent graduates from Navajo Technical University and Dine College, 2) Computing stipends to support laptops and broadband internet access for participation in the network, 3) Opportunities for support through individual meetings with peer and vertical mentors, and community talking circles on COVID, health and wellbeing, and leadership, and 4) Opportunities for participation in virtual workshops and research and outreach projects pertaining to environmental science and other green STEM fields at each of the participating institutions.This project responds to the COVID-19 historical conjuncture that has disproportionately impacted vulnerable populations such as the Navajo Nation. The pandemic created an environment where Navajo students have difficulty accessing essential as well as educational resources. This is inhibiting their ability to be retained in geoscience, environmental science, and other STEM fields where their diverse perspectives and leadership is needed. This project will counter these barriers with professional development opportunities and funding to directly support Navajo students, recent graduates, and early career professionals. The PIs will focus on faculty development that will support retention of Navajo students in STEM while simultaneously hoping to boost retention rates of indigenous students in geoscience, green STEM, and STEM more broadly, through experiential learning opportunities, financial support, and mentorship. The virtual workshops and leadership-focused talking circles will serve to support both early career and faculty fellows to become champions for diversity in geoscience and other fields.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": "1403", "attributes": { "award_id": "2027013", "title": "RAPID: Fast Holographic Assay for Viral Infection with Application to COVID-19", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [ "7573", "7914" ], "program_officials": [ { "id": 3627, "first_name": "Elizabeth", "last_name": "Mann", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-04-01", "end_date": "2022-03-31", "award_amount": 200000, "principal_investigator": { "id": 3629, "first_name": "David G", "last_name": "Grier", "orcid": "https://orcid.org/0000-0002-4382-5139", "emails": "[email protected]", "private_emails": "", "keywords": "['Soft condensed matter physics']", "approved": true, "websites": "['https://physics.nyu.edu/grierlab/', 'https://physics.nyu.edu/grierlab/publications.html']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 167, "ror": "https://ror.org/0190ak572", "name": "New York University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 3628, "first_name": "Kent", "last_name": "Kirshenbaum", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 167, "ror": "https://ror.org/0190ak572", "name": "New York University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Non-technical AbstractConventional diagnostic tests for viral infections focus on the biochemical properties of pathogens; they require costly reagents and multiple processing steps by highly trained personnel. This RAPID program instead uses fast and inexpensive optical techniques to detectthe physical properties of viral pathogens. The breakthrough that enables this new approach to medical diagnostics is a technique called holographic particle characterization (HPC). HPC creates laser holograms of specially prepared test beads and uses those holograms to monitor small changes in the beads’ properties that occur when molecules or virus particles bind to their surfaces. Originally developed for fundamental research in soft condensed matter physics, HPC already has been demonstrated to provide fast and sensitive immunoassays in model systems. These measurements are fast, inexpensive and can be performed automatically with minimal human intervention. The next step is to create libraries of test beads for different target diseases and to demonstrate that HPC can diagnose those diseases - first in the research laboratory, and then in a clinical setting. The anticipated product of this work is a new platform for diagnosing viral infections that can meet the need for fast, accurate and cost-effective testing under the strains imposed by public health crises.Technical AbstractThere is an urgent need for new technologies to detect viral pathogens. Holographic binding assays can detect the presence of virus particles and antibodies in fluid media through their influence on the optical properties of functionalized probe beads. The micrometer-scale beads that will be developed for this program will incorporate chemical groups on their surfaces to selectively bind specific targets, such as the SARS-CoV-2 virus responsible for COVID-19 or the antibodies that are produced in response to infection. Bound targets increase the apparent size of a bead and alter its light-scattering properties. Both of these effects can be resolved directly by holographic particle characterization, a comparatively new platform technology that has the demonstrated ability to measure the diameter and refractive index of micrometer-scale colloidal spheres with part-per-thousand precision. A statistical sample consisting of thousands of single-bead measurements can be completed in a matter of minutes using commercial instrumentation for holographic particle characterization. Specialized reagents are not required. Multiplexed assays for multiple targets can be performed with libraries of functionalized beads that are distinguished by their base diameters and refractive indexes. Each such assay can therefore simultaneously diagnose a viral infection both by the presence of virions, and also by the presence of antibodies. This RAPID program will deliver scalable syntheses of probe beads for diagnosing viral infection and automated protocols for performing holographic binding assays, enabling high-throughput medical diagnostics.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": "1682", "attributes": { "award_id": "2031901", "title": "EAGER: CPR-COVID-19 Prevention Robot in Dense Areas", "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": [ "7495", "7916" ], "program_officials": [ { "id": 4406, "first_name": "Erion", "last_name": "Plaku", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-15", "end_date": "2021-05-31", "award_amount": 120000, "principal_investigator": { "id": 4408, "first_name": "Dinesh", "last_name": "Manocha", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": "['Robotics']", "approved": true, "websites": "['http://gamma.umd.edu', 'https://gamma.umd.edu/researchdirections/covid19/c19', 'https://arxiv.org/abs/2008.06585']", "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4407, "first_name": "Aniket", "last_name": "Bera", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "Motivated by the COVID-19 pandemic, this project will develop a robot to understand whether pedestrians in public places or offices are maintaining social distancing guidelines. The project will develop new methods that leverage machine learning, computer vision, and robot motion planning to ascertain the positions of pedestrians as they move in a confined area. Real-time understanding of pedestrian movements can assist social distancing efforts, minimizing the spread of COVID-19, and can more broadly enhance human-robot interactions.The underlying challenges include development of new navigation algorithms that can compute collision-free paths for a robot in medium and high-density crowds. Navigation among pedestrians will be formulated as a Partially-Observable Markov Decision Process and solved using deep reinforcement learning, particularly focusing on Proximal Policy Optimization. The pedestrian-tracking approach will be based on a novel concept of Frontal Reciprocal Velocity Obstacles, which uses an elliptical approximation of each pedestrian motion and estimates the underlying dynamics by considering intermediate goals and collision avoidance. The planned approach will also be able to handle occlusions among pedestrians by moving the robot in an intelligent way to improve the information that it receives from its sensors. The project will use commodity sensors, including cameras and 2D LIDARs, to understand pedestrian movements and check for social distance constraints. Finally, this project will investigate techniques to influence pedestrian behavior using robots.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": "2099", "attributes": { "award_id": "2032729", "title": "EAGER: Documenting and Analyzing Use of Robots for COVID-19", "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": [ "7495", "7916" ], "program_officials": [ { "id": 5648, "first_name": "Erion", "last_name": "Plaku", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-10-01", "end_date": "2021-03-31", "award_amount": 68962, "principal_investigator": { "id": 5650, "first_name": "Robin R", "last_name": "Murphy", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": "['Robotics']", "approved": true, "websites": "['http://roboticsforinfectiousdiseases.org/index.html', 'http://roboticsforinfectiousdiseases.org/index.html']", "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 5649, "first_name": "Angela", "last_name": "Clendenin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 282, "ror": "", "name": "Texas A&M Engineering Experiment Station", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The robotics community needs to learn and prepare for future infectious diseases and future disasters. Understanding the role of robotics in preventing, responding to, and mitigating the consequences of pandemics could have a profound impact on the future of robotics research and convergence research in general. This understanding could identify applications where robotics are impacting, or could impact, the response to the COVID-19 pandemic disaster. Roboticists could then concentrate on those applications and gaps while the relevant agencies could have confidence in the systems. This project will guide the rapid innovation of robots for the remainder of the COVID-19 pandemic and inform future convergence research on autonomous robots by creating and analyzing a database of press and social media reports on how ground and aerial robots are being used throughout the world for the response. The project has two novel components that distinguish it from simple data gathering and archiving and that will ensure its utility for research. One, by archiving, curating, and analyzing the comprehensive use of robots worldwide for COVID-19 response and creating a sustainable nexus permitting incorporation of new reports during the evolving pandemic and supporting additional analyses. Two, the novel cross-disciplinary framework will provide a standard set of schemas for capturing data on the use of robots for disasters. Not only will the framework and plan of work establish how robots are being used, it is expected to use the experts’ unique domain knowledge to identify missed opportunities for application.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": "1701", "attributes": { "award_id": "2040489", "title": "EAGER: Home-based DIY Interactive Information Physicalization for Young Children and their Parents", "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": [ "7367", "7916" ], "program_officials": [ { "id": 4452, "first_name": "Dan", "last_name": "Cosley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-10-01", "end_date": "2023-09-30", "award_amount": 300000, "principal_investigator": { "id": 4454, "first_name": "Yi-Luen E", "last_name": "Do", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 172, "ror": "", "name": "University of Colorado at Boulder", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 4453, "first_name": "Danielle", "last_name": "Szafir", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 172, "ror": "", "name": "University of Colorado at Boulder", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "Public discourse during the COVID-19 pandemic surfaced the central role data serves in shaping individual and community action. Data literacy is the ability to constructively reason with data. Fostering data literacy has largely been the domain of formal educational systems and expert tools. Informal educational approaches have the potential to overcome barriers to interacting with data by fostering data literacy through casual engagement. This research explores how informal learning, through creation and interaction with physical data representations (physicalizations), may foster increased data literacy and engagement. The project team will design a series of do-it-yourself (DIY) activities for young children to construct physicalizations from household materials. These activities will enable children to explore COVID-19 and other data in familial contexts. They are expected to help them reason about the pandemic and everyday information through embodied data sensemaking and creative processes of physical construction. This project serves the national interest by promoting universal data understanding to advance national data literacy, health, and welfare. It will directly support education and foster diversity by disseminating information physicalization kits to families across the nation. Resulting tools will be released as open source so that other researchers, designers, and developers can use them for diverse information physicalization projects.The project will advance the field of information visualization with new physical and tangible representations and techniques. Through an iterative design methodology of participatory workshops and interviews, involving families, the project will: (1) develop a novel toolkit and instructions for families to build interactive information physicalizations, using common household materials and mobile computers; (2) connect the toolkit to COVID-19 and environmental citizen science data; (3) understand emergent phenomena involving how kids and families engage with information physicalizations, through grounded theory analysis of video and interview data; (4) assess effects of the information physicalizations on data literacy; and (5) develop implications for the design and crafting of tangible interfaces, using everyday materials, which facilitate sensemaking and learning in informal settings.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": "1862", "attributes": { "award_id": "2041415", "title": "EAGER: NewsStand CoronaViz: A Map Query Interface for Tracking the Spread of COVID-19", "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": [ "7364", "7916" ], "program_officials": [ { "id": 4925, "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": "2020-10-01", "end_date": "2022-09-30", "award_amount": 150000, "principal_investigator": { "id": 4926, "first_name": "Hanan", "last_name": "Samet", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "With the rapid continuing spread of COVID-19, it is clearly important to be able to track its progress over time in order to be better prepared to anticipate its emergence and spread in new regions as well as declines in its presence in regions thereby leading to or justifying \"reopening\" decisions. There are many applications and web sites that monitor officially released numbers of cases which are likely to be the most accurate methods for tracking the progress of COVID-19; however, they do not necessarily paint a complete picture. To begin filling any gaps in official reports, the project will develop the NewsStand CoronaViz (abbreviated as CoronaViz) web application aimed at allowing users to explore the geographic spread in discussions about COVID-19 through analysis of keyword prevalence in geotagged news articles and tweets in relation to the real spread of COVID-19 as measured by the confirmed cases numbers reported by the authorities.CoronaViz users will have access to dynamic variants of the disease-related variables corresponding to the number of confirmed cases, active cases, deaths, and recoveries (where they are provided) via a map query interface. They will also have the ability to step forward and backward in time using both a variety of temporal window sizes (day, week, month, or combinations thereof) in addition to user-defined varying spatial window sizes specified by direct manipulation actions (e.g., pan, zoom, and hover) as well as textually (e.g., by the name of the containing continent, country, state or province, or county). The result is an animation and that also supports zooming which means that users zoom in on a map they get more data rather than magnified data as is the case in most existing systems. CoronaViz is not restricted to COVID-19 and can be used for other diseases such as Ebola. Having a system such as CoronaViz is useful should the COVID-19 pandemic return.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": 3, "pages": 1392, "count": 13920 } } }