Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=4&sort=end_date
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=end_date", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1397&sort=end_date", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=5&sort=end_date", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=end_date" }, "data": [ { "type": "Grant", "id": "13569", "attributes": { "award_id": "2134864", "title": "Terrestrial Organics since The Oligocene (TOTO): The Rains Down in Africa", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "Marine Geology and Geophysics" ], "program_reference_codes": [], "program_officials": [ { "id": 29707, "first_name": "Joseph", "last_name": "Carlin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-15", "end_date": null, "award_amount": 613617, "principal_investigator": { "id": 6732, "first_name": "Kevin", "last_name": "Uno", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 29727, "first_name": "Rachel L", "last_name": "Lupien", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 196, "ror": "https://ror.org/00hj8s172", "name": "Columbia University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Terrestrial Organics since The Oligocene (TOTO): The Rains Down in Africa<br/><br/>Today, nearly 100 million people depend on the lands in the Sahel region, which is highly sensitive to flooding, droughts, and wildfires, putting food and other resources at risk. Africa is also rich in human evolutionary history, including early human fossil sites, evidence for multiple dispersals out of Africa, and the earliest stone tool innovations. Despite the region’s importance for understanding climate change and human evolution, there is a lack of understanding of tropical Africa over long intervals. To that end, the investigators will generate new West African records of rain, vegetation, and fire over the last 25 million years to study changes in the Sahel ecosystem, which runs east-west across Africa south of the Sahara desert, and to quantify the effects of natural cycles in Earth’s orbit and long-term changes in global and regional conditions on ecosystem change and human evolution. The investigators will convene a new African Climate Conference to facilitate knowledge sharing, networking events, and laboratory tours at Lamont to directly combat the long history of the exclusion of African researchers in Western science by forming deep, lasting collaborations.<br/><br/>The Tropics comprise half of Earth’s surface, serve as the global hydrological pump, and contain the world’s largest potential source of methane, yet there is a dearth of data and understanding of tropical climate over the Cenozoic. Tropical Africa, in particular, has been historically under-studied, despite its importance for understanding human evolution, tropical hydroclimate, and terrestrial ecosystem responses to climate change. Projections of future climate scenarios require quantification of past climatic responses to orbital forcings and boundary conditions (i.e., regional albedo, ice volume, global temperature). The investigators will generate new long-term and high-resolution precipitation, vegetation, and fire reconstructions using biomarkers preserved in a marine sediment core that capture the last 25 million years of tropical West African climate. Statistical and time series analyses will evaluate the amplitudes, periodicities, means, and relationships between hydroclimate, ecosystem, and fire proxies through time to decipher the differences in the amplitude of variability in the study windows to characterize sensitivity in the context of various boundary conditions. This project will provide crucial environmental context for the evolution of our earliest ancestors and will inform models of future terrestrial responses to global warming in this highly sensitive region.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14082", "attributes": { "award_id": "2103173", "title": "PostDoctoral Research Fellowship", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Workforce (MSPRF) MathSciPDFel" ], "program_reference_codes": [], "program_officials": [ { "id": 6631, "first_name": "Andrew", "last_name": "Pollington", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-09-01", "end_date": null, "award_amount": 150000, "principal_investigator": { "id": 30603, "first_name": "Rita", "last_name": "Teixeira da Costa", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2409, "ror": "", "name": "Teixeira da Costa, Rita", "address": "", "city": "", "state": "", "zip": "", "country": "PO", "approved": true }, "abstract": "This award is made as part of the FY 2021 Mathematical Sciences Postdoctoral Research Fellowships Program. Each of the fellowships supports a research and training project at a host institution in the mathematical sciences, including applications to other disciplines, under the mentorship of a sponsoring scientist. <br/><br/>The title of the project for this fellowship to Rita Teixeira da Costa is \"The final state conjecture and the large-scale structure of spacetime.\" The host institution for the fellowship is Princeton University, and the sponsoring scientist is Igor Rodnianski.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13312", "attributes": { "award_id": "2149848", "title": "Developing the thermodynamic solid solution models for Th, U, REE phosphates needed to identify the formation conditions of Th, U-depleted REE ores", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "Petrology and Geochemistry" ], "program_reference_codes": [], "program_officials": [ { "id": 2399, "first_name": "Rachel", "last_name": "Teasdale", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 489, "ror": "", "name": "Chico State Enterprises", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] } ], "start_date": "2022-03-01", "end_date": null, "award_amount": 425742, "principal_investigator": { "id": 29391, "first_name": "Xiaofeng", "last_name": "Guo", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 306, "ror": "https://ror.org/05dk0ce17", "name": "Washington State University", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true }, "abstract": "Rare earth elements (REE) are critical for the future of the U.S. economy, renewable energy, and national security. New technologies enhancing environmental sustainability, defense capability, and consumer products have sharply increased the demand for the REE. However, the supply of REE in the U.S. relies mostly on their import from foreign sources. Furthermore, many of the domestic deposits suffer from high concentrations of thorium (Th) and uranium (U) that contaminate the environment during mining. To deal with this issue, it is necessary to discover the conditions needed for economic concentrations of the REE to form in nature in the absence of Th or U; this requires understanding how Th and U mix with the REE in minerals and how such mixing can be avoided. This project will explore how Th and U mix with the REE in minerals through a combination of experiments and geological modeling. These results will make it possible to predict the natural environments in which Th- and U-poor REE minerals form and thereby provide geologists with the information they need to develop strategies to explore for and locate deposits of REE that can be economically and safely mined. This project also aims to educate high school, undergraduate, and graduate students in geochemistry, and prepare them for careers as scientists. The integrated education plan is committed to holding summer geochemistry schools for high school students, promoting geochemical education to student through visits to national laboratories and virtual lectures, and engaging students in the experimental and modeling methods that are used in the research project.<br/><br/>The objective of this research proposal is to generate new knowledge enabling identification of the conditions under which Th and U-depleted REE phosphate ores can form. One of the major impediments to the recovery of REE from ores in the U.S. is the radioactivity generated during their processing and refining due to the presence of high concentrations of Th and U in the main REE ore minerals, monazite and xenotime. Thus, there is a strong need to find Th, U-depleted REE ores, which, in turn, depends on developing a better understanding of their formation conditions (e.g., temperature, pressure, oxygen fugacity, pH, etc.), particularly those for which the incorporation of Th and U into phosphate structures is minimal. Whereas the properties of the aqueous species of the REE, U, and Th are now reasonably well-known for the hydrothermal conditions of REE ore formation, there is almost no information on phosphate-based REE/U/Th solid solutions. A major challenge is to correctly account for thermodynamic non-ideality due to the mixing of Th and U with the REE, which is often incorrectly assumed to be ideal and thus can lead to inaccurate or false predictions. This project will establish accurate thermodynamic models describing the incorporation of Th and U in REE phosphates that are critically needed by geochemical modelers to predict the mobilization, fractionation, and deposition of REE/U/Th in hydrothermal systems. The knowledge obtained will enable the development of new exploration techniques permitting the identification and localization of Th- and U-depleted REE ores. The project also offers unique opportunities for students to receive the interdisciplinary education and training needed to become geochemists with broad mindsets and skillsets. This includes summer geochemistry schools for high school students and teachers to develop their interest in the geochemistry of the REE and other critical metals.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14849", "attributes": { "award_id": "2412783", "title": "RNA Self-Repair Induced by Sunlight: Can a Novel Mechanism Shed Light on Life's Origins and RNA Cell Function?", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "PHYSICS OF LIVING SYSTEMS" ], "program_reference_codes": [], "program_officials": [ { "id": 780, "first_name": "Krastan", "last_name": "Blagoev", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-07-15", "end_date": null, "award_amount": 549701, "principal_investigator": { "id": 31529, "first_name": "Dimitar", "last_name": "Sasselov", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 455, "ror": "https://ror.org/03vek6s52", "name": "Harvard University", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "The integrity of the genetic information, carried by large chain molecules called nucleic acids (DNA and RNA), is vital for all organisms on Earth. When exposed to ultraviolet (UV) sunlight, DNA and RNA can form structural defects, which damage their function, cause mutations, or in severe cases - lead to cell death. But sunlight can be also a healer. The PI’s lab recently discovered that some short RNA strands can self-repair in a manner very similar to DNA. The PI observed that short RNA strands do so by developing states under UV-sunlight, which last long enough to transfer an electron to the damaged site and heal it. This discovery of RNA self-repair opens the door for a number of experimental projects on RNA’s origins and non-enzymatic replication, on RNA sequence selectivity, on tRNA function, etc. From a practical perspective, these results also have implications for how cells handle RNA damage in modern organisms, so the PI pay close attention to potential biomedical applications. Therefore, this award promotes progress in fundamental science, as well as advances in national health issues, as the handling of RNA damage by cells and viruses has become a newly active area since the pandemic. While advancing discovery, this award will also contribute to the education and training of future scientists and engineers as well. The research-based education of undergraduate and graduate students in our lab, and the high representation of women in the PIs lab will broaden participation in achieving these goals. <br/><br/>This award project plans to elucidate the mechanism of the self-repair process in RNA and to extend its generality by experimenting with an array of RNA sequences, as well as with non-canonical nucleotides like Inosine. Working with short two- and four-base sequences is just the necessary first step. In addition to longer length, the investigators will explore both the base selection and the sequence directionality. The latter turns out to make a difference, as the investigators recently showed with DNA sequences of GAT=T versus T=TAG, assigning this disparity to the importance of different stacking overlap between the G and A bases. This award is exciting and important because no existing RNA photolyase enzymes are known, and the results from this award may shed light on how cells handle damaged RNA with mechanisms that are very different from DNA repair activity as known to-date. Therefore, some results from this award may have implications to physiology and medicine. On the other hand, as there were no enzymes during the emergence of life, this award will contribute to understanding the prebiotic sequence selectivity in RNA’s early functions in prebiotic chemistry and/or as information carrier in translation or replication. The investigators will explore the long-lived charge-transfer states in tRNA-analogs and similar RNA oligos as potential functional switches in the early evolution of translation. The ability of RNA and cofactors, like NADH, to form UV-induced charge-separated states and to transfer charge in a selective manner is not only intriguing but could be of paramount importance to the emergence of primitive cell functions during the origins and early evolution of life. What is often viewed simply as damage (or lesion), could well be a life-saving functionality for a primitive cell surviving on low-fidelity non-enzymatic RNA replication. With this new approach to nucleic acid UV-induced damage, the investigators will pursue a number of experiments into the emergence of functionality at the origins of translation (e.g., aminoacylation of RNA) and non-enzymatic RNA replication.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12544", "attributes": { "award_id": "2229975", "title": "Collaborative Research: CyberTraining: Pilot: Operationalizing AI/Machine Learning for Cybersecurity Training", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "CyberTraining - Training-based" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-01-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28473, "first_name": "Houbing", "last_name": "Song", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 315, "ror": "", "name": "Embry-Riddle Aeronautical University", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "The interplay between AI and cybersecurity introduces new opportunities and challenges in the cybersecurity of AI as well as AI for cybersecurity. However, operations and configurations of AI cyberinfrastructure (CI) with a security mindset are rarely covered in the typical AI curriculum. To fill this gap, this project intends to develop hands-on training materials and provide mentored training for current and future research workforce in engineering and science-related disciplines. By transforming and integrating training materials into a course curriculum, this project aims to train potential cyberinfrastructure professionals in the CI community at large to handle AI with and for cybersecurity. This project has the potential to develop the research workforce in operating AI cyberinfrastructure with a security mindset to meet the national and economical needs and priorities of CI advancement. This project’s goal is to broaden the adoption of advanced cyberinfrastructure through training. This project develops a holistic technical approach for cybertraining: to identify, apply, and evaluate AI techniques which are inextricably related to well-defined operational cybersecurity challenges. The project intends to develop a Docker-based training platform that simulates and pre-configures a variety of scenarios to support hands-on AI cyberinfrastructure operations in the context of cybersecurity. Three levels of projects (exploratory, core, and advanced) are designed and integrated into the platform to help researchers and educators customize and develop into different education and training environments. The project democratizes the access and adoption of advanced AI cyberinfrastructure, while integrating cyberinfrastructure skills with the security mindset to foster inter-disciplinary and inter-institutional research collaborations. In addition to the dissemination through publications and social media, the outcomes from this project have the potential to benefit the greater cyberinfrastructure community and beyond, through the training and the sharing of the \"AI for and with cybersecurity\" course curriculum. This project is jointly funded by OAC and the CyberCorps program.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": "15105", "attributes": { "award_id": "2325532", "title": "SBIR Phase II: A Novel Host-Directed Broad-Spectrum Antiviral and Efficient Immunomodulatory Agent Against Coronaviruses: Lead Optimization Studies", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase II" ], "program_reference_codes": [], "program_officials": [ { "id": 773, "first_name": "Erik", "last_name": "Pierstorff", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": null, "award_amount": 1000000, "principal_investigator": { "id": 31651, "first_name": "Mohammad", "last_name": "Noshi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 356, "ror": "", "name": "Akanocure Pharmaceuticals, Inc.", "address": "", "city": "", "state": "IN", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase II project stems from the development of a virus agnostic drug that can control the current coronavirus pandemic and potentially future pandemics caused by yet unknown viruses. Since 2020, research has been chasing COVID-19 and its variants by reformulating vaccines and developing more antibodies and antivirals, but the virus has always been ahead, mutating so fast to make those approaches obsolete. Because COVID-19 is not going away, and because a dysregulated (toxic) immune response is not unique to COVID-19, and because viral threats will not stop at COVID-19, a virus and variant agnostic drug that can stop the virus from multiplying, can fix the toxic immune response, is easy to administer in an outpatient or pandemic setting (oral), and can be given early or late in the infection cycle is imperative to get ahead of viral threats. In addition to the positive effect on pandemic preparedness and decreasing the pressure on healthcare systems, such drug can positively impact the economy by preventing the devastating health effects that COVID-19 has on the cardiovascular (heart) and nervous systems, which have led to disability claims sharply rising among the working age group.<br/><br/>The proposed project focuses on the lead optimization of a candidate molecule for oral administration against coronaviruses. SARS-CoV-2 infections cause hyperinflammation and autoimmunity leading to multi-organ damage even with mild infections. The damage is cumulative and repeat infections increase the risk of long COVID. These clinical manifestations are due to persistent/chronic infections and dysregulated immune responses. An ideal treatment would not only suppress viral replication but would also restore the immune system homeostasis and healthy immune response. In Phase I, a molecule was designed, synthesized, and shown to be an efficient immunomodulatory and broad-spectrum antiviral. This molecule targets the host rather than the virus which decreases the chances of resistance and makes it virus/variant agnostic, unlike vaccines and direct-acting antivirals. In Phase II, the technical objectives focus on design, synthesis, and testing of analogs with improved drug-like properties for oral administration. Those analogs will be evaluated against several SARS-CoV-2 variants in-vitro, subjected to in-vitro ADME studies, and assessed for their effect on the production of immune mediators in virus-infected cells. The analog with the best profile will advance to in-vivo studies to test its pharmacokinetic and toxicological properties in mice, as well as its efficacy and immune modulations activity in virus-infected animal rodents.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13568", "attributes": { "award_id": "2144751", "title": "CAREER: Efficient, Dynamic, Robust, and On-Device Continual Deep Learning with Non-Volatile Memory based In-Memory Computing System", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Software & Hardware Foundation" ], "program_reference_codes": [], "program_officials": [ { "id": 977, "first_name": "Sankar", "last_name": "Basu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-15", "end_date": null, "award_amount": 500000, "principal_investigator": { "id": 8714, "first_name": "Deliang", "last_name": "Fan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 173, "ror": "", "name": "The University of Central Florida Board of Trustees", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>Over past decades, there have existed grand challenges in developing high performance and energy-efficient computing solutions for big-data processing. Meanwhile, owing to the boom in artificial intelligence (AI), especially Deep Neural Networks (DNNs), such big-data processing requires efficient, intelligent, fast, dynamic, robust, and on-device adaptive cognitive computing. However, those requirements are not sufficiently satisfied by existing computing solutions due to the well-known power wall in silicon-based semiconductor devices, the memory wall in traditional Von-Neuman computing architectures, and computation-/memory-intensive DNN computing algorithms. This project aims to foster a systematic breakthrough in developing AI-in-Memory computing systems, through collaboratively developing ahybrid in-memory computing (IMC) hardware platform integrating the benefits of emerging non-volatile resistive memory (RRAM) and Static Random Access Memory (SRAM) technologies, as well as incorporating IMC-aware deep-learning algorithm innovations. The overarching goal of this project is to design, implement, and experimentally validate a new hybrid in-memory computing system that is collaboratively optimized for energy efficiency, inference accuracy, spatiotemporal dynamics, robustness, and on-device learning, which will greatly advance AI-based big-data processing fields such as computer vision, autonomous driving, robotics, etc. The research will also be extended into an educational platform, providing a user-friendly learning framework, and will serve the educational objectives for K-12 students, undergraduate, graduate, and under-represented students.<br/><br/>This project will advance knowledge and produce scientific principles and tools for a new paradigm of AI-in-Memory computing featuring significant improvements in energy efficiency, speed, dynamics, robustness, and on-device learning capability. This cross-layer project spans from device, circuit, and architecture to DNN algorithm exploration. First, a hybrid RRAM-SRAM based in-memory computing chip will be designed, optimized, and fabricated. Second, based on this new computing platform, the on-device spatiotemporal dynamic neural network structure will be developed to provide an enhanced run-time computing profile (latency, resource allocation, working load, power budget, etc.), as well as improve the robustness of the system against hardware intrinsic and adversarial noise injection. Then, efficient on-device learning methodologies with the developed computing platform will be investigated. In the last thrust, an end-to-end DNN training, optimization, mapping, and evaluation CAD tool will be developed that integrates the developed hardware platform and algorithm innovations, for optimizing the software and hardware co-designs to achieve the user-defined multi-objectives in latency, energy efficiency, dynamics, accuracy, robustness, on-device adaption, etc.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12546", "attributes": { "award_id": "2150093", "title": "Collaborative Research: REU Site: The Socio-Ecological Role of Greenways in Urban Systems - An Interdisciplinary Approach", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "RSCH EXPER FOR UNDERGRAD SITES" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-01-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28475, "first_name": "Shannon", "last_name": "McCarragher", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 532, "ror": "", "name": "Southern Illinois University at Edwardsville", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "This project is funded from the Research Experiences for Undergraduates (REU) Sites program in the Directorate for Social, Behavioral and Economic Sciences (SBE). The REU program has both scientific and societal benefits integrating research and education. This REU Site award to University of Tennessee Chattanooga, located in Chattanooga, TN, and Southern Illinois University Edwardsville in Edwardsville, IL, will support the training of 10 students for 10 weeks for three years. Research is conducted at Chattanooga, TN, Edwardsville, IL, and Cleveland, TN. It is anticipated that a total of 30 students, primarily from schools with limited research opportunities or from an under-represented group, will be trained in the program. Students will learn how policy decisions are made and how interdisciplinary research is conducted, with many presenting the results of their work at scientific conferences and to local policymakers and community stakeholders. The research will integrate greenway networks into the broader field of urban science and improve our understanding of the environmental and human associated impacts of greenway networks in urban areas. Assessment of the program will be done through the online SALG URSSA tool. Students will be tracked after the program in order to determine their career paths.The theme for this 3-year research experience focuses on enhancing environmental resilience and sustainability by examining the interaction between human and natural systems within urban greenway networks. The research is grounded in three fundamental questions: 1) What are the human and ecological drivers of microclimate? 2) What are the human usage patterns in urban greenway networks? 3) How can empirical evidence on urban greenway dynamics inform the broader scientific community and local community stakeholders on ways to mitigate environmental impacts and social disparities in cities? Students will work in interdisciplinary teams and assess how greenways vary based on social and ecological characteristics of the greenway in each respective city. Results from each team will be combined into a larger dataset which will be used to assess greenway characteristics in varying city sizes. The findings will be shared with community leaders and stakeholders to inform them of the current impacts of their greenway system and potential opportunities for expanding the greenway network. Students will learn and apply skills related to: biodiversity; data collection, analysis, and visualization; geographic information systems (GIS); and, evidence-based policymaking. These skills will then be used to better understand the human and biological drivers of microclimate variation within greenway networks and inform policymakers as to the best ways to mitigate environmental impacts and social disparities in order to create more resilient cities.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": "14080", "attributes": { "award_id": "2103145", "title": "PostDoctoral Research Fellowship", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Workforce (MSPRF) MathSciPDFel" ], "program_reference_codes": [], "program_officials": [ { "id": 2352, "first_name": "Stefaan De", "last_name": "Winter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-09-01", "end_date": null, "award_amount": 150000, "principal_investigator": { "id": 30601, "first_name": "Paula", "last_name": "Burkhardt", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2407, "ror": "", "name": "Burkhardt, Paula Elisabeth", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is made as part of the FY 2021 Mathematical Sciences Postdoctoral Research Fellowships Program. Each of the fellowships supports a research and training project at a host institution in the mathematical sciences, including applications to other disciplines, under the mentorship of a sponsoring scientist. <br/><br/>The title of the project for this fellowship to Paula Burkhardt-Guim is \"C^0 Riemannian metrics with synthetic lower scalar curvature bounds and Ricci flow.\" The host institution for the fellowship is New York University, and the sponsoring scientist is Bruce Kleiner.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14850", "attributes": { "award_id": "2345178", "title": "Partnering to Recruit, Engage, Prepare, and Support New STEM Teachers for North Dallas Area Schools", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)", "Robert Noyce Scholarship Pgm" ], "program_reference_codes": [], "program_officials": [ { "id": 31530, "first_name": "Patrice", "last_name": "Waller", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-06-01", "end_date": null, "award_amount": 1199934, "principal_investigator": { "id": 16099, "first_name": "Mary", "last_name": "Urquhart", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 199, "ror": "", "name": "University of Texas at Dallas", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 16094, "first_name": "John", "last_name": "Zweck", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 16097, "first_name": "Kate", "last_name": "York", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 31531, "first_name": "Katherine", "last_name": "Donaldson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 199, "ror": "", "name": "University of Texas at Dallas", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "This project aims to respond to the national need of preparing and retaining high-quality teachers. Teacher shortages in science, technology, engineering, and mathematics (STEM) are becoming increasingly dire in the aftermath of the Covid-19 pandemic and its impact on attitudes regarding teaching. New strategies are needed to rise to the challenges of recruiting, preparing, and retaining K–12 teachers. This program seeks to partner to recruit, engage, prepare, and support (PREPS) new teachers in the north Dallas area to increase the number of well-prepared science and mathematics teachers and retain them in the teaching profession. The PREPS project intends to investigate and disseminate effective strategies for recruitment of STEM majors into the teaching profession. PREPS also intends to investigate and disseminate effective strategies for support and retention of these newly prepared STEM teachers. <br/><br/>This project at the University of Texas at Dallas (UT Dallas) School of Natural Sciences and Mathematics includes partnerships with at least three high-need independent school districts (ISDs) in the north Dallas area of the Dallas-Fort Worth Metroplex (DFW): Garland ISD, Mesquite ISD, and Richardson ISD. The PREPS project is part of the UTeach Dallas STEM teacher certification preparation program. Project goals include strengthening collaborations with partner ISDs for 1) quality field experiences for preservice teachers, 2) effective induction support for new teachers, 3) investigation of new pathways for recruitment into and/or completion of teacher preparation, and 4) identification of barriers to new teacher retention and strategies to address these barriers. At the university, project goals include 1) targeted recruitment into teacher preparation of STEM majors in critical teacher shortages in mathematics and the sciences, 2) identification and dissemination of effective post-pandemic messaging for teacher recruitment from a pool of undergraduate STEM majors, 3) investigation of a potential partnership with the UT Dallas School of Science and Engineering for recruitment into the teaching profession of STEM majors in additional critical shortage areas such as computer science, and 4) systematic use of data for continuous improvement. UTeach Dallas PREPS also intends to explore direct recruitment of students in local, diverse, high-needs high schools into mathematics and science majors at UT Dallas and into UTeach Dallas. The project plans to disseminate findings to multiple university-based teacher preparation national and statewide networks. UTeach Dallas PREPS intends to provide up to 54 scholarships and 40 internships, with recipients anticipated to directly impact STEM learning for up to 27,000 students in their first five years of teaching in the Dallas-Fort Worth Metroplex. Participants are expected to positively impact K–12 students through internships and in their field experiences beginning as early as their first university semester. This Track 1: Scholarships and Stipends project is supported through the Robert Noyce Teacher Scholarship Program (Noyce). The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 teachers to become STEM master teachers in high-need school districts. It also supports research on the effectiveness and retention of K-12 STEM teachers in high-need school districts.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 4, "pages": 1397, "count": 13961 } } }