Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=2&sort=-principal_investigator
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-principal_investigator", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=-principal_investigator", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=-principal_investigator", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-principal_investigator" }, "data": [ { "type": "Grant", "id": "15664", "attributes": { "award_id": "2438012", "title": "I-Corps: Translation Potential of an Enhanced Fluorescence-based Diagnostic Technology for the Detection of Lyme Disease", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "I-Corps" ], "program_reference_codes": [], "program_officials": [ { "id": 31316, "first_name": "Jaime A.", "last_name": "Camelio", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-12-01", "end_date": null, "award_amount": 50000, "principal_investigator": { "id": 32172, "first_name": "Nathaniel", "last_name": "Cady", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 571, "ror": "", "name": "SUNY at Albany", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this I-Corps project is the development of an enhanced fluorescence-based diagnostic technology for the detection of antibodies and other biomarkers for disease diagnostics. The base technology has been demonstrated for diagnosing high profile diseases including COVID-19 and Lyme disease. For this I-Corps effort, Lyme disease has been chosen as the beachhead market due to the current diagnostic challenges, and the growing market for fast and accurate Lyme disease diagnostic technologies. The accepted standard for Lyme disease, known as standard two-tiered testing (STTT) is time consuming, requires specialists to run, and can be unreliable, especially for early stages of the disease. This technology has proven to alleviate these pain points, providing rapid and accurate Lyme disease diagnosis, especially for early Lyme disease patients. The platform has also been utilized for detecting RNA-protein and DNA-protein interactions, which potentially broadens its utility for a large number of different disease diagnostic applications, biomarker discovery, and biological / pharmaceutical research applications. The technology may have impact in several clinical and biological research fields. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a photonics-based Lyme disease diagnostic platform. Lyme disease is the most common vector-borne disease in the United States and, despite advances, remains a considerable diagnostic challenge. Confirmatory diagnosis requires a second test, performed in series, often in batches, and at a centralized laboratory. This delay can lead to considerable morbidity in disseminated Lyme disease. This technology is a low-cost, highly sensitive, fluorescence-based platform, which provides a rapid, easy-to-use, and highly accurate Lyme test that could be used outside traditional clinical laboratories or for more rapid and accurate diagnosis within clinical laboratories. The proof-of-principle research positions the technology as a rapid (<40 minutes total test time) and reliable alternative to traditional Lyme tests, while retaining the full sophistication of a two-tiered testing system. 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": "15662", "attributes": { "award_id": "2401975", "title": "Excellence in Research: a PEC-AbP Dual Signal Amplification Method and its Mechanistic Study of Signal Transduction for DNA Sensing", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "HBCU-EiR - HBCU-Excellence in" ], "program_reference_codes": [], "program_officials": [ { "id": 961, "first_name": "Aleksandr", "last_name": "Simonian", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-12-01", "end_date": null, "award_amount": 599991, "principal_investigator": { "id": 32171, "first_name": "Peng", "last_name": "He", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32170, "first_name": "Jianjun", "last_name": "Wei", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 708, "ror": "", "name": "North Carolina Agricultural & Technical State University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "DNA sensing techniques have been widely applied in daily life such as medical diagnosis, biowarfare defense, forensic science, and environmental monitoring, and were significantly promoted during the past pandemic, e.g., reverse transcription polymerase chain reaction (RT-PCR) test for COVID-19. Rapid DNA detection with high sensitivity, specificity, and accuracy is in high demand, however limited by signal readout. This project is aimed at developing an innovative dual signal amplification method by integrating two different signal amplification methods, i.e., materials science- and optical-based. The research goals are to strengthen signal readouts and build field-friendly DNA sensors that are amenable to point-of-need applications with ultrasensitivity. The discovery of fundamental science and transformative technology will potentially enable a reliable multiplexed high-throughput DNA analysis platform that may greatly benefit health care in society and facilitate research and applications in biomedical and life science. The scientific learning of this interdisciplinary research performed at the HBCU (NC A&T) and MSI (UNC Greensboro) will advance sensing mechanism understanding, instruct and train students especially underrepresented students, in research and education, and engage K-12 STEM educators and students in science. Genetic information with or without variation coded within nucleic acids, indicating an illness or health outcome, is termed a nucleic acid biomarker, thus plays a crucial role in precision medicine. Sensitive and selective detection of nucleic acid biomarkers with rapid signal amplification is the key for early screening and diagnosis of human diseases. This project is aimed at developing an innovative dual signal amplification method and understanding the signal transduction mechanism for enhanced DNA sensing. The work is built on the seamless integration between amplification-by-polymerization (AbP) in DNA sensing for optical clarity change on surface based on effective mass growth upon DNA recognition and in-planar metallic film nanoarrays for plasmon-exciton coupling (PEC) optical enhancement. The research will be conducted in three stages to (1) fully explore the potential of the AbP-PEC dual signal amplification platform, (2) investigate the fundamental mechanism of the amplified signal transduction pertaining to the AbP-produced film thickness and plasmonic nanoslit structure, and (3) optimize the AbP-PEC platform for a portable DNA sensor in point-of-care diagnostics. The outcome may be transformative towards a multiplexed, rapid, highly sensitive, visible (by naked eyes) analysis of DNA in biofluids. 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": "15661", "attributes": { "award_id": "2509179", "title": "Conference: Building Teams to Build Better Epidemiological Models: Balancing Participation from Mathematical and Social, Behavioral, and Economic Sciences", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "MSPA-INTERDISCIPLINARY" ], "program_reference_codes": [], "program_officials": [ { "id": 1173, "first_name": "Joseph", "last_name": "Whitmeyer", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-12-01", "end_date": null, "award_amount": 29940, "principal_investigator": { "id": 32169, "first_name": "Dana", "last_name": "Pasquale", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 246, "ror": "https://ror.org/00py81415", "name": "Duke University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "This award will support two separate one-day virtual conferences entitled “Building Teams to Build Better Epidemiological Models: Balancing Participation from Mathematical and Social, Behavioral, and Economic Sciences” (https://sites.duke.edu/betterepidemiologicalmodelsconference/), to be held in January 2025. In a crisis such as the COVID-19 pandemic, mathematical models played their role in designing, developing, deploying, and evaluating public health strategies with different levels of success. Still, all were confronted with prioritizing public health or economic viability. To frame a sound pandemic response strategy, mathematical models are primary tools that must incorporate behavioral components and frameworks to be more efficient and useful for public health policy interventions and the evaluation of the economic impact of such measures. The COVID-19 pandemic highlights the need to develop mathematical methodologies, new techniques, and innovative approaches designed to incorporate the new paradigm of behavioral dynamics into the transmission dynamics of human diseases. Multidisciplinary teams are needed to innovate new mathematical methodologies which incorporate human behavioral and social dynamics. This award will be used to support a conference to bring together mathematical and social / behavioral / economic scientists to develop improved epidemiological models which can protect both public health and the economy. Applicants will be selected to balance these research areas, with attention given during the selection process to ensure that women and members of underrepresented groups are fully considered with an eye to broadening participation. The standard framework for the mathematical modeling of infectious diseases is the basic Kermack-McKendrick model, a compartmental model framed in ordinary differential equations and their extensions to stochastic and hybrid models. Mixing is a random process in this framework, and this characteristic has pervaded in models for prediction and forecasting and is one, but not unique, of the most challenging and important topics in modeling infectious diseases: how to modify the basic assumption of the homogeneous population in the model to incorporate significant behavioral effects robustly and effectively. For example, there have been several efforts in literature to integrate behavior; one of them is the one that assumes that agents that interact during the transmission of the disease are rational, i.e., the individuals behave in a way consistent with a rational evaluation of risks. This model type is based on economic thinking in which costs and benefits are balanced, where there is a trade-off that rational agents resolve. The problem in epidemiology is that many of the actions of natural agents during an epidemic do not adapt to this hypothesis; therefore, applying this type of modeling requires the development of innovative ideas, alternative conceptual frameworks, and new mathematical techniques and methodologies. Scientific teams which can innovate and parameterize mathematical models which are tractable, represent an analogue of human behavior and transmission, work across a variety of domains and settings, and can be used to test interventions are needed. 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": "15660", "attributes": { "award_id": "2413062", "title": "NSF-ANR MCB/PHY: Virus self-assembly, from test tube to cell cytoplasm", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "Molecular Biophysics" ], "program_reference_codes": [], "program_officials": [ { "id": 15289, "first_name": "Wilson", "last_name": "Francisco", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-12-15", "end_date": null, "award_amount": 987566, "principal_investigator": { "id": 32168, "first_name": "William", "last_name": "Gelbart", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 3324, "first_name": "Roya", "last_name": "Zandi", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 153, "ror": "", "name": "University of California-Riverside", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] } ], "awardee_organization": { "id": 151, "ror": "", "name": "University of California-Los Angeles", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Coming out of the most severe and destructive viral pandemic of the past 100 years, the importance of understanding how viruses “work” is clear. Most viruses – including polio, yellow fever, Dengue, and SARS, etc. – have RNA genomes that are quickly turned or “translated” into viral proteins in host cells that self-assembled into new virus particles called capsids. Elucidating how this process happens is a high priority for preventing and treating these infections. This project sets out to connect in vivo experiments carried out in live cells with in vitro experiments carried out in a test tube with purified viral capsid proteins and RNA genome. While test tube studies allow for full control of the types and numbers of components and solution conditions in which they are interacting, live cells studies, on the other hand, involve viral RNA and capsid proteins in the presence of many unknown components whose effects on RNA translation and self-assembly into capsids have not yet been determined. The fundamental understanding that results from this research will enhance the ability to develop anti-viral treatments. Graduate students will be trained in an inter-/cross-disciplinary range of physical, chemical, biological, and translational medicine concepts and methods. Active outreach efforts aim at enhancing interest and understanding of science amongst budding scientists and lay persons of all kinds will be conducted. This project will be performed by an international collaboration between five different research groups in the US and France, each specializing in different experimental and theoretical techniques and each having extensive experience with one or the other of the plant (cowpea chlorotic mottle virus [CCMV]) and mammalian (hepatitis B [HepB]) viruses under study. These viruses were chosen because how significantly they differ in their host cell and capsid structure, so that general principles of viral self-assembly can be established. It is the goal of this project to elucidate the differences between in vitro and in cellulo viral processes by progressively adding to RNA and capsid protein a series of molecules that play key roles in the viral “life” cycle, mimicking the crowded interior of the cell. Using cell-free cytoplasmic (ribosome-rich) extract, viral RNA will be translated into protein products and the time course of capsid assembly will be investigated by a combination of experimental techniques, including magnetic resonance, X-ray scattering, and fluorescence and electron microscopies. Coarse-grained molecular dynamics computations and phenomenological theory will be used to analyze these kinetic data and to compare with what is learned using the same experimental techniques applied to corresponding virus assembly in test tubes, where all concentrations and solution conditions are controlled. This collaborative US/France project is supported by the US National Science Foundation and the French Agence Nationale de la Recherche, where NSF funds the US investigator and ANR funds the partners in France. 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": "15657", "attributes": { "award_id": "2436332", "title": "MPOPHC: Incorporation of Game Theory Tools to Improve the Policy Making to Mitigate Epidemics of Respiratory Diseases", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "MATHEMATICAL BIOLOGY" ], "program_reference_codes": [], "program_officials": [ { "id": 622, "first_name": "Zhilan", "last_name": "Feng", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-01-01", "end_date": null, "award_amount": 360000, "principal_investigator": { "id": 32166, "first_name": "Gokce", "last_name": "Dayanikli", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32165, "first_name": "Pamela P", "last_name": "Martinez", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 281, "ror": "", "name": "University of Illinois at Urbana-Champaign", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "During the COVID-19 pandemic, it was observed that individuals did not always follow mitigation policies closely. Instead, they behaved according to their own objectives, where demographic and socioeconomic factors seemed to have influenced their responses to the set policies. Therefore, this project aims to improve the policymaking processes to mitigate the transmission of respiratory pathogens by incorporating the individuals’ decision-making and socio-demographic heterogeneities. To do this, the investigators propose to develop and study game theoretical mathematical models, as well as simulation tools and numerical approaches that can be adapted to specific public health problems of interest to practitioners and researchers. These tools will be made publicly available. This project will also involve interdisciplinary training for graduate students in applied mathematics, statistics, operations research, epidemiology, and quantitative biology. To model many interacting agents, the investigators will develop and study extensions of mean field games (MFGs). First, they will focus on building multi-population MFGs and graphon games to incorporate socio-demographic heterogeneities while finding the Nash equilibrium responses of individuals under different disease mitigation policies (e.g., vaccination policies and non-pharmaceutical interventions). Furthermore, different equilibrium notions to incorporate altruism in the populations will be explored through the introduction of mixed multi-population MFGs that include both cooperative and non-cooperative individuals. Later, the investigators will focus on finding optimal mitigation policies by using Stackelberg MFGs that include the optimization of a regulator (e.g., a governmental institution). The extensions of Stackelberg MFGs that include heterogeneities in the mean field populations, altruistic behaviors, and possible state variables for the regulator will be developed and analyzed. Surveys and analyses of publicly available data will be conducted to calibrate and parameterize the mathematical models to capture real-life patterns. Finally, numerical approaches and simulation toolboxes will be implemented to solve large dimensional and more complex models, which will allow policymakers to adapt and parametrize our models according to their specific needs. This award is co-funded by the NSF Division of Mathematical Sciences (DMS) and the CDC Coronavirus and Other Respiratory Viruses Division (CORVD). 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": "15656", "attributes": { "award_id": "2502655", "title": "I-Corps: Translation potential of plant PYR1 biosensors for the rapid testing of environmental contaminants", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "I-Corps" ], "program_reference_codes": [], "program_officials": [ { "id": 602, "first_name": "Ruth", "last_name": "Shuman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-01-01", "end_date": null, "award_amount": 50000, "principal_investigator": { "id": 32164, "first_name": "Ian", "last_name": "Wheeldon", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 153, "ror": "", "name": "University of California-Riverside", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this I-Corps project is the development of sensors for a wide array of previously undetectable chemicals. Global industrialization has created advanced materials and chemicals that persist in the environment with lasting effects on human health. Current technologies that test for environmental contaminants using chromatographic methods and laboratory test kits are slow, expensive, and inaccessible to consumers. This chemical sensor technology may provide portable test strips (similar to those used to test for COVID-19) to test for small molecules characteristic of pharmaceuticals, pesticides, and per- and polyfluoroalkyl substances (or PFAS). This technology may make field-based and in-home testing of pesticides and PFAS possible for the first time, giving consumers and regulators a way to alleviate safety concerns about pollutants in drinking water and food. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of PYR1 biosensors, plant hormone receptors that, when mutated, may be used to identify a wide variety of chemicals, including environmental contaminants (e.g., organophosphate pesticides and PFAS). Ligand recognition occurs exclusively in the PYR1 subunit, not the HAB1 partner, which makes the system significantly easier to engineer for new ligands than previously developed methods. The efficacy of these sensors has been demonstrated in yeast, bacteria, plants, and in vitro to test for substances of abuse in blood, urine, and saliva. These sensors also have been stabilized for high temperature and used as sensors in living plants. To date, the sensors have been designed for hundreds of target molecules, and ongoing refinement of the pipeline methodology makes it possible to identify sensors for new targets in less than a week. 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": "15655", "attributes": { "award_id": "2436340", "title": "MPOPHC: Quantitative design of effective testing-based policies through infection trajectory modeling", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "MATHEMATICAL BIOLOGY" ], "program_reference_codes": [], "program_officials": [ { "id": 622, "first_name": "Zhilan", "last_name": "Feng", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-01-01", "end_date": null, "award_amount": 968765, "principal_investigator": { "id": 32163, "first_name": "Stephen", "last_name": "Kissler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32162, "first_name": "Daniel B", "last_name": "Larremore", "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": "Diagnostic tests play a crucial role in the management of infectious disease transmission. Testing is the fastest most reliable way to inform a person whether they are infected, and thus whether they should adjust their behavior to prevent onward spread. Testing policies have long contributed to public health, including in the control of HIV, tuberculosis, and malaria. During the COVID-19 pandemic, various test-based policies were successful, including pre-event screening (e.g., testing before entering a sporting event), traveler screening (e.g., testing before boarding a flight), and regular screening (e.g., weekly testing at universities). Such policies could also help control the spread of other existing and novel respiratory pathogens. However, we currently lack a robust, data-driven framework to estimate the potential impact of testing-based infection control strategies in general. To fill this gap, this project will develop a flexible modeling framework to simulate how different testing policies might perform for various pathogens, tests, and human behavioral scenarios. This project will also develop the statistical tools needed to infer how diagnostic test results, infectiousness, and behavior relate to one another, informed by data on SARS-CoV-2 and other respiratory pathogens. To maximize the impact of these findings, this project will build mature, open-source software products to compare testing-based policies, accompanied by tutorials for policymakers and a new open-source data hub to consolidate information relevant to testing-based policies. The successful completion of this project will improve our ability to control existing respiratory pathogens and enhance our preparedness for future pandemics. Fundamental to this project is the characterization of how infectiousness, detectability, symptoms, and behaviors change over the course of a respiratory infection – a collection of features called an infection trajectory. While the details of an infection trajectory can be omitted for some types of policy assessments, testing-based policies depend critically on an accurate and statistical understanding of infection trajectories. Infection trajectory-based models allow for the separation of individual-level features of disease transmission from the between-host dynamics, permitting a “plug-and-play” approach to policy design, without compromising the ability to tailor solutions to local needs and populations. This project’s policy modeling framework will develop a stochastic description of infection trajectories, represented by a joint distribution of an infection’s measurable variables. This will allow the researchers to assess variability in policy outcomes and to identify cross-policy interactions. This project will develop a framework to infer infection trajectory distributions from multimodal data and will deploy that framework to guide the design of studies for collecting new infection trajectory data. Finally, this project will create a suite of software, educational, and data tools for informing infection trajectories and associated policies. For the public health policy community, successful completion of this project will produce new, high-quality policy design models and assessment tools, complemented by educational and interactive exploration webpages. For the scientific community, this project will provide statistical tools and data sharing standards for infection trajectory data, supporting advances in virology and modeling. This award is co-funded by the NSF Division of Mathematical Sciences (DMS) and the CDC Coronavirus and Other Respiratory Viruses Division (CORVD). 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": "15654", "attributes": { "award_id": "2434162", "title": "Equipment: Course-Based Undergraduate Research Experiences: Engaging Historically Underrepresented Students Using Stress Block Image Correlation Simulation", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "HSI-Hispanic Serving Instituti" ], "program_reference_codes": [], "program_officials": [ { "id": 2964, "first_name": "Sonja", "last_name": "Montas-Hunter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-01-01", "end_date": null, "award_amount": 185515, "principal_investigator": { "id": 32161, "first_name": "Ariful", "last_name": "Bhuiyan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32158, "first_name": "Jana M", "last_name": "Willis", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 32159, "first_name": "Magdy", "last_name": "Akladios", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 32160, "first_name": "Serkan", "last_name": "Caliskan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 590, "ror": "https://ror.org/01t817z14", "name": "University of Houston - Clear Lake", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Educational Instrumentation (EI) track aims to engage students in course-based undergraduate research experiences (CUREs) in a lab-led freshman physics course (PHYS 2425) along with eight other courses. This approach will provide students with valuable opportunities to conduct various hypothesis-driven research projects related to fatigue loading using the ElectroForce (EF) 3330 equipment and an in-house developed innovative fixture called the Stress Block (SB). Economic shifts, societal changes, alternative career paths, and the lingering effects of COVID-19 have all impacted undergraduate enrollment. With a strong job market for non-degree roles, more high school graduates are considering direct entry into the workforce. However, in today’s competitive job market, the value of higher education remains critical, offering specialized skills and advantages that can elevate quality of life. For many physics and mechanical engineering undergraduates, insufficient high school preparation can create obstacles in problem-solving and understanding complex measurements, often hindering success in rigorous university programs. CUREs will provide essential support by allowing students to apply theoretical concepts to real-world scenarios, reinforcing understanding through hands-on learning. This experience will also enable students to build a supportive network with faculty and peers, contributing to their professional growth. Through active participation, CUREs will foster a sense of ownership and deeper engagement with learning. The SBICS-CUREs project, utilizing ElectroForce (EF) 3330 and Digital Image Correlation (DIC) technology, is designed to enhance these experiences while also contributing to reducing the gender gap in STEM fields. The hypothesis for this project proposes that integrating the ElectroForce (EF) 3330 equipment with a custom-designed Stress Block (SB) fixture in a freshman physics course will significantly enhance students’ understanding and application of hypothesis-driven research. The specific aims are to (1) connect the SB attachment to the ElectroForce (EF) 3330 and (2) apply DIC techniques on samples tested with this setup. The methodology includes six steps: 3D printing samples, speckle deposition for image correlation, setting up a GoPro for reference images, mounting the SB fixture on the ElectroForce (EF) 3330, applying sinusoidal loads, and conducting DIC analysis to assess deformation and strain. This process gives students hands-on testing and simulation experience, bridging theoretical knowledge with real-world applications. Reflective learning is central to this project, utilizing DIC software like Ncorr, a free tool for full-field, non-contact optical measurements of deformation and strain in mechanical components. Findings will be shared through conferences, peer-reviewed publications, and YouTube videos, with plans to connect with industry leaders like Boeing, KBR, and agencies such as NASA and National Science Foundation. Additionally, partnerships with local Independent School Districts (ISDs) will enable high school students to participate, building a recruitment pipeline for UHCL STEM programs. The HSI Program aims to enhance undergraduate STEM education and build capacity at HSIs. Projects supported by the HSI Program will also generate new knowledge on how to achieve these aims. 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": "15652", "attributes": { "award_id": "2430389", "title": "NSF I-Corps Hub (Track 1): Northwest Region", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "I-Corps Hubs" ], "program_reference_codes": [], "program_officials": [ { "id": 602, "first_name": "Ruth", "last_name": "Shuman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-01-01", "end_date": null, "award_amount": 15000000, "principal_investigator": { "id": 32157, "first_name": "Richard", "last_name": "Lyons", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 32156, "first_name": "Sosale S", "last_name": "Sastry", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 176, "ror": "", "name": "University of California-Berkeley", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this I-Corps Hubs project is the development of infrastructure needed for entrepreneurial training for academic science, technology, engineering, and math (STEM) researchers and high potential community teams. This training will accelerate the commercialization of cutting-edge technologies and enhance regional innovation. It will also support workforce readiness in a region that is rapidly changing as the result of post-pandemic, economic and geographic dynamics of “meta cities,” and net in and out migration to and from rural and underserved areas throughout the region. In addition, Hub activities will provide the training needed to power other NSF initiatives promoting commercialization and innovation. Developing these entrepreneurial skills for both academic researchers and throughout the region’s workforce amplifies the economic and societal impact of NSF and other-funded basic research while accelerating the growth of startups, providing economic benefit to the region and beyond. This will be accomplished in an inclusive way to multiply opportunities, increases national competitiveness, and secures an economic future for all. This I-Corps Hubs project is based on the aim to advance the translation of deep technologies into societal and economic impact. This collaboration covers a large geographic area, inclusive of both urban and rural locations throughout Alaska, California, Oregon, and Washington. The region shares distinct commonalities between the proposed Partners and synergies that may be leveraged to serve a uniquely diverse population and maximize economic impact throughout the region. The proposed Hub activities will be designed to support regional and national I-Corps training through team expansion, fuel regional and national economic growth, produce actionable entrepreneurial research, and broaden participation among underrepresented areas and populations. The Hub Partners share a mission to reduce time and risk associated with translating top research from lab-to-market, while expanding educational and economic opportunity throughout the region. Through education, evidence, and experience, the Hub will drive creation of sustainable, scalable technology-based startups with both regional and national impacts. The Hub will strive to raise awareness of the value of entrepreneurship among science and engineering faculty and students, using a variety of programs designed for inclusivity and meeting scientists and engineers at their knowledge and skill level, whether they are curious about the fit of their technology to solve an industry problem or are committed company founders. 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": "15651", "attributes": { "award_id": "2501232", "title": "Advantaging the National Artificial Intelligence Research Resource (NAIRR) Pilot: Leveraging the COVID-19 HPC Consortium Experience", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "NAIRR-Nat AI Research Resource" ], "program_reference_codes": [], "program_officials": [ { "id": 32154, "first_name": "Sharon", "last_name": "Geva", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-02-15", "end_date": null, "award_amount": 896755, "principal_investigator": { "id": 32155, "first_name": "John", "last_name": "Towns", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 15575, "first_name": "Christine R", "last_name": "Kirkpatrick", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 281, "ror": "", "name": "University of Illinois at Urbana-Champaign", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "This project supports the broader efforts of the National Artificial Intelligence Research Resource (NAIRR) Pilot to address how powerful Artificial Intelligence (AI) resources can be used to accelerate scientific understanding and discovery and further the capabilities of AI models. It also develops efficient processes for providing these resources to researchers. This project builds on the successful model of, and lessons learned from, the COVID-19 HPC Consortium (C19HPCC), which demonstrated the power of public-private partnerships in addressing global challenges. By applying these lessons to the NAIRR Pilot, the project creates a robust framework for future government-academia-industry collaborations. This not only enhances the NAIRR Pilot but also paves the way for the full NAIRR program, ultimately supporting a broader range of research efforts and fostering innovation in artificial intelligence. The project leverages lessons learned from the C19HPCC to enhance the National Artificial Intelligence (NAIRR) Pilot. The C19HPCC was a collaborative effort that brought together high-performance computing (HPC) resources from government, academia, and industry to accelerate research and discovery in the fight against COVID-19. The primary goals are to develop efficient processes for allocating AI resources, improve proposal review mechanisms, establish effective reporting methods, foster partnerships across government, academia, and industry, and establish and evolve governance structures and coordination mechanisms to manage the diverse set of resources and stakeholders involved. The scope includes leveraging prior policies, procedures, and tools from the C19HPCC to support the NAIRR Pilot and ultimately the full NAIRR program. By applying these methods, the project aims to create a robust framework for future AI research and innovation. 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": 2, "pages": 1392, "count": 13920 } } }