Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1383&sort=-approved
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Understanding their origin will help in forecasting space weather and its impacts on spacecraft and instruments. This project addresses the Solar, Heliospheric, and Interplanetary Environment (SHINE) goal to enhance understanding of processes by which energy in the form of magnetic fields and particles are produced by the Sun and accelerated in interplanetary space. Graduate and undergraduate researchers will be supported. Further, a database of solar coronal-jet events will be created.The project is an observational and theoretical study of coronal jets to answer two science questions: (1) Where are electrons accelerated in active-region periphery jets? (2) How do flare-accelerated particles from active-region periphery jets escape into the heliosphere? The approach combines high-quality observations with state-of-the-art numerical simulations. The team will select and analyze a set of coronal jets at active-region peripheries from space-based and ground-based observatories, including the NSF-funded Expanded Owens Valley Solar Array. They will determine which types of jets are associated with impulsive solar energetic particle events, where the high-energy electrons are located both within and beyond the solar sources, and how these events evolve. Their magnetic topologies will be estimated by nonlinear force-free field extrapolations from magnetograms. Based on the data analysis results, they will perform simulations with initial conditions consistent with typical properties of the observed events. Postprocessing the simulation output with the particle-tracking code will reveal where electrons are energized, how their spectra evolve, and how these energetic particle escape.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": "12536", "attributes": { "award_id": "2238340", "title": "CAREER: An Integrated Geophysical Approach to Research and Education to Solve the Tectonic Puzzle of the Northern Atlantic", "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": [], "start_date": "2023-03-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28466, "first_name": "Irina", "last_name": "Filina", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 298, "ror": "", "name": "University of Nebraska-Lincoln", "address": "", "city": "", "state": "NE", "zip": "", "country": "United States", "approved": true }, "abstract": "The Northern Atlantic has diverse geologic features including a hotspot under Iceland, volcanic-rich passive continental margins of Norway and Eastern Greenland, and active and abandoned spreading centers in the Atlantic Ocean with the Jan Mayen microcontinent in between. However, the tectonic history of the region has generally been oversimplified. This research will reveal the crustal type (continental or oceanic) of different tectonic blocks, reconstruct their fit prior to the opening of the northern Atlantic Ocean, and provide a tectonic “snapshot” for each geologic time period. The results can help pinpoint the timing and extent of critical geological processes that affect paleoclimate, biodiversity, and initiation of oceanic water circulation. The research will be integrated with education efforts, including mini research projects in advanced geophysical classes at the University of Nebraska-Lincoln; a summer camp for high school students and underserved students from Girls Inc. of Lincoln and Omaha, NE; and five education modules that will be disseminated to educators across the nation via the Science Education Resource Center at Carleton College. Such efforts will broaden participation in STEM and cultivate a diverse and well-equipped geophysics workforce. With uncertainties in the extent of the Jan Mayen microcontinent and tectonic domains of the Norwegian margin, as well as the disputed crustal affinity of the Greenland-Iceland-Faroe Ridge, tectonic reconstruction of the Northern Atlantic region remains poorly constrained. This project will examine crustal architecture and tectonic structures of individual regions via the integration of geophysical methods with geological constraints from scientific drilling. A set of robust and comprehensive geophysical models in three individual regions of the Northern Atlantic – the Norwegian-Greenland conjugate margins, the Jan Mayen microcontinent, and the Greenland-Iceland-Faroe Ridge region – will be developed to define subsurface structures that are in agreement with multiple geophysical methods. The identified tectonic features will be traced in-between the modeled lines in all three regions using spatial analysis of potential fields, building a framework for a consequent tectonic restoration, which will provide new fundamental knowledge of the pre-Atlantic continent. Integrated with these efforts, the education goal is to promote geophysics as a career of choice by engaging diverse undergraduate, graduate, and high school students in interactive learning experiences centered around an integrated geophysical approach. These activities will promote a comprehensive multi-physics analysis that integrates publicly available datasets and enables robust and rigorous interpretations. Ultimately, a comprehensive geophysical research program will be established at a public land-grant institution that will yield graduates who are well-equipped to meet the needs of the geophysical workforce and nation.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": "12537", "attributes": { "award_id": "2239105", "title": "CAREER: Impacts of the Chemical and Physical Properties of Surfactants on the Hygroscopic Growth of Atmospheric Aerosol Particles", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "Atmospheric Chemistry" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-03-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 7300, "first_name": "Amanda", "last_name": "Frossard", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 160, "ror": "", "name": "University of Georgia Research Foundation Inc", "address": "", "city": "", "state": "GA", "zip": "", "country": "United States", "approved": true }, "abstract": "This CAREER project focuses on the study of surfactant compounds in atmospheric aerosol and their effects on particle hygroscopic growth. Field collections and laboratory experiments using high resolution chemical and physical analyses will be used to assess the influence of surfactant molecular composition and associated properties on the hygroscopic growth of atmospheric particles. Hygroscopic growth can alter particle size and composition, both of which are important determinants in the influence of aerosol particles on visibility and human health.The effect of surfactants on particle hygroscopic growth is expected to be nonlinear and dependent on the surfactant molecular composition, structure, and critical micelle concentration. The experimental plan will address the following questions: (1) What are the compositions, structures, and interfacial properties of surfactants in atmospheric aerosol particles? How do these surfactant characteristics vary as a function of particle size and air mass source region (e.g., natural, anthropogenic, marine, aged influences)? (2) What effects do surfactant structure, composition, and interfacial properties have on the hygroscopic growth of submicron and supermicron aerosol particles? Chemical and physical measurements of aerosol particles collected as part of two field campaigns at the Skidaway Institute of Oceanography, on the coast of Georgia, will be made during two seasons to capture seasonal variability. Laboratory experiments will also be conducted to measure the hygroscopic growth of model laboratory-generated aerosol particles to determine the influence of the surfactant fraction directly. Multivariate statistics will be used to determine the surfactant properties in different particle types.The education and outreach plan includes working with high school students to collect local air quality measurements, developing a new laboratory course to explore the principles of analytical chemistry through measurements of aerosol chemistry, and conducting a first-year research seminar course and a summer research experience for undergraduate students.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": "12538", "attributes": { "award_id": "2149553", "title": "REU Site: Studying Race and Policing in the Complex Social Interaction Lab", "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": "2023-03-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28467, "first_name": "Dale", "last_name": "Willits", "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": "This project is funded by the Research Experiences for Undergraduates (REU) Sites program in the Directorate for Social, Behavioral and Economic Sciences. This REU provides both scientific and societal benefits. In terms of science, this project engages the scientific method examining the role of race in how interactions between police officers and community members unfold. In terms of societal benefits, this research will help generate understanding of police interactions, with a specific focus of understanding why police interactions vary and how they can be improved. This program imparts the knowledge, skills, and abilities to engage in scientific research to REU participants, while demonstrating how such research can improve community prosperity and welfare by affecting positive change in police-community interactions. In addition, this project generates research that will increase the safety of community members and officers involved in police-community interactions. Lastly, this program supports education and diversity by recruiting students from diverse backgrounds who will be embedded into a collaborative and interdisciplinary research environment where they will develop research skills which improve their ability to make meaningful contributions to society.The Complex Social Interaction Lab REU trains undergraduate researchers, especially, but not limited to, those from underrepresented populations, on data-oriented social science approaches to the study of race and policing. The site emphasizes the recruitment, training, and participation in research of promising students to address three interrelated projects: race and police use of force, 2) race and de-police escalation tactics, and 3) race and procedurally just policing. The methodological approaches focus on coding video and audio data, basic to intermediate quantitative methods, and advanced applications in GIS, time-series analysis, data analytics, and data visualizations. Additionally, this project reinforces the importance of methodological rigor and analytical creativity in generating valid and reliable measures and interpreting those data by way of the objective coding of body worn camera footage, making use of such footage as a novel source of data for the study of policing. Students will have the opportunity to use these methods to generate innovative data and the opportunity to publish peer-reviewed research. The goals of this project are to 1) recruit promising students, 2) provide real world research opportunities that integrate theory, methods, and application, 3) increase knowledge regarding policing and the race, 4) develop professional skills, and 5) prepare students for graduate school and for other career opportunities. This site is supported by the Department of Defense ASSURE program in partnership with the NSF REU 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": "12539", "attributes": { "award_id": "2313262", "title": "LEAPS-MPS: Applications of Algebraic and Topological Methods in Graph Theory Throughout the Sciences", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "OFFICE OF MULTIDISCIPLINARY AC" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-03-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28468, "first_name": "Lindsey-Kay", "last_name": "Lauderdale", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 537, "ror": "", "name": "Southern Illinois University at Carbondale", "address": "", "city": "", "state": "IL", "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). Graphs are used to represent complex networks throughout the sciences; for example, biology, chemistry, computer science, and engineering all use graphical networks to model real-life phenomena. The use of graphs allows for a concise way to model the relationships among a large number of entities in a network, and these relationships can be understood through the structural properties of graphs. Such structural properties of graphs are often quantitative, and the research goal of this project is to study numerous quantitative graph measures. The research results will be applied to complex networks, which arise outside of the mathematical sciences, in order to improve network models. The educational goal of this project is to increase the persistence in the undergraduate mathematics major by creating opportunities that increase both the academic integration and social integration of mathematics majors. Mathematics majors from underrepresented groups will be encouraged to participate with the goal of increasing the number of such individuals who could serve as role models for the scientific workforce of the future. A major goal of this project is to study distance-based graph invariants using various algebraic and topological methods in order to improve models which the graph describes. Some current viewpoints do not account for the symmetries of a graph, which are known to affect certain applications; the first area of focus in this project is to further develop graph invariants to account for such symmetries of graphs. The PI will create generating functions that represent q-analogs of these invariants. The second area of focus in this project is to use embedding techniques to obtain new properties and bounds on graph invariants.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": "12540", "attributes": { "award_id": "2322322", "title": "PFI-TT: Ultrafast Thermal Simulation of Metal Additive Manufacturing", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "PFI-Partnrships for Innovation" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-03-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28469, "first_name": "Prahalada", "last_name": "Rao", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 244, "ror": "", "name": "Virginia Polytechnic Institute and State University", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is fast and accurate computer simulation software to predict when and why flaws are formed in metal parts made using additive manufacturing (3D printing). Given its singular design and material flexibility, metal additive manufacturing (metal AM) has the potential to revolutionize U.S. manufacturing by improving part performance and reducing waste and processing costs. However, safety-conscious industries, such as aerospace and biomedical, are hesitant to adopt AM processes due to the frequent occurrence of parts with hidden flaws. Traditional approaches for detecting and correcting flaws involve determining and adjusting the process parameters that lead to defects using a trial-and-error approach, which is expensive and time-consuming. This innovative project utilizes a computational simulation software to identify and correct design and processing problems before a part is printed. Importantly, this approach will provide scientific insights into why certain process parameters and part design features result in defect formation. This efficient and cost-effective method for detecting and correcting flaws in AM parts will enable their wide-spread commercialization and adoption. Ultimately, using AM processes rather than traditional manufacturing may save businesses time and resources while increasing part efficiency and reducing negative environmental impacts. This project will verify, validate, and commercialize a computational heat transfer modeling approach to simulate the temperature distribution in parts made using metal AM. This technology, which is based on the novel concept of heat diffusion on graphs (graph theory), aims to predict and correct design and processing problems before a part is printed. This capability would ultimately lead to improved AM part quality and increased use of AM processes in precision-critical industries. Existing simulation packages are expensive and incorporate proprietary assumptions. Non-proprietary approaches, in turn, take hours, if not days, to simulate the thermal history for a simple part. Prior work by the research team has demonstrated that the graph theory approach is approximately twenty times faster than non-proprietary methods and so computationally lightweight that it could be deployed on a laptop or smartphone. In moving toward commercializing the technology, the project team will employ practical use case samples produced by their industrial partners. The work will address two fundamental research questions: (1) What process conditions and part design features are linked to specific temperature patterns and why? (2) What is the influence of thermal history on flaw formation? The technical results from this project may include a rigorous, experimentally validated, computationally efficient, user-friendly, and industrially corroborated thermal simulation approach that can be used for rapid physics-based optimization of part design and process settings in metal AM.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": "12541", "attributes": { "award_id": "2333154", "title": "Collaborative Research: Scales and drivers of variability in dissolved organic carbon across diverse urban watersheds", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Evolutionary Processes" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-03-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28470, "first_name": "Rebecca", "last_name": "Hale", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 711, "ror": "https://ror.org/01pp8nd67", "name": "Smithsonian Institution", "address": "", "city": "", "state": "DC", "zip": "", "country": "United States", "approved": true }, "abstract": "Most ecosystems are impacted by human activities to some degree, but this can vary considerably beteween locations. For example, cities differ in their impacts on streams and rivers depending on age, storm water infrastructure, amount of green space, and other factors of the built environment. Natural factors such as climate (temperature and precipitation) and geology also affect how different cities influence water quality and quantity at different times of the year. In this project, differences in urban impacts on carbon inputs and outputs in streams will be evaluated across cities in the U.S. that have different urban and climate contexts. This research is critical for understanding ecological patterns and processes in urban streams. Broader impacts of the work will include training opportunities for undergraduate and graduate students and postdoctoral scholars, workshops, and an innovative training and internship program for high school students.This study will take a novel approach to jointly consider how the human and ecological dimensions of ecosystem ecology interact to control the quality, quantity, and timing of dissolved organic carbon (DOC) – the largest flux of carbon in streams – entering watersheds across the continent. This project will assess how urbanization affects DOC, focusing on how urbanization affects stream ecosystems in regionally-specific ways. Researchers will test the hypothesis that human activities introduce novel sources of DOC and affect the spatial and temporal scales and variability of ecological processes in different geographies and urban contexts. The hypothesis will be tested using a comparative approach to understand urban effects on DOC in five urban study areas – Miami, FL, Boston, MA, Atlanta, GA, Salt Lake City, UT, and Portland, OR. Extensive synoptic sampling of DOC concentrations and quality will be combined with intensive sensor networks to develop a multi-scale understanding of the quantity and quality of DOC in urban systems. Spatial statistics and time-series analyses will identify key spatio-temporal characteristics of human development (e.g., wastewater infrastructure, housing density) and biophysical factors (e.g., discharge, precipitation, canopy cover) that control the concentration, characteristics, and bioavailability of DOC.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": "12542", "attributes": { "award_id": "2236229", "title": "Exploring the Impact of Community Engagement on STEM Undergraduates via Math Circles for Urban Elementary School Students", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "IUSE" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-02-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28471, "first_name": "Emily", "last_name": "Atieh", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1113, "ror": "https://ror.org/02z43xh36", "name": "Stevens Institute of Technology", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true }, "abstract": "This project aims to serve the national interest by fostering partnerships between higher education and local communities to improve K-12 math education while developing the teaching, leadership, and communication skills of undergraduates majoring in STEM fields. The project will develop and assess an innovative year-long community engagement program that prepares undergraduates to lead math circles with urban elementary school students in multiple community settings. Through exploration, collaboration, and problem solving, math circles promote positive perceptions of mathematics, children's ability to do math, and the relevance of math to everyday life. This project will advance understanding of the potential impact of math circles as a vehicle to enhance undergraduate STEM learning experiences. Undergraduate facilitators will be empowered to apply mathematics to effect positive change in their community. The project will also serve to broaden participation in math education, strengthen pathways to the STEM workforce, foster deeper understanding of important mathematical concepts, and build knowledge of best practices in teaching and learning.The project’s overarching goal is to develop an innovative community engagement program to harness the knowledge, skills, and enthusiasm of well-prepared STEM undergraduates to facilitate collaborative mathematics problem solving among elementary school students in their local community. Over three years, the project will design, implement, and iteratively improve a credit-bearing course that will prepare STEM undergraduates to lead math circles with elementary school children in various community settings: a school-based after school program, a public library, and the Boys and Girls Club. Four key tasks each year guide the project. First is to offer an elective community engagement course for all STEM majors. Second is to collaborate with partner sites to recruit elementary school students to participate in a math circle program. Third is to collect and analyze data to ascertain the impact on undergraduate math circle facilitators. The fourth and final task is to undertake formative and summative evaluation to strengthen outcomes for undergraduate facilitators and improve both the project-developed course and the overall community engagement program. The data gathered will provide a rich picture of who chooses to be a math circle facilitator and why, and the impact on students’ knowledge, skills, and perceptions of mathematics within and across community sites. Results will be disseminated via research publications, presentations at major conferences, webinars, a public-facing website, and a blueprint for replicating the project model at other institutions of higher learning. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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": "12543", "attributes": { "award_id": "2222220", "title": "MCA: Environmental Drivers of Snow Algae Bloom Dynamics, Physiology, and Life-Cycles", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Ecosystem Science" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-02-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28472, "first_name": "Robin", "last_name": "Kodner", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 481, "ror": "https://ror.org/05wn7r715", "name": "Western Washington University", "address": "", "city": "", "state": "WA", "zip": "", "country": "United States", "approved": true }, "abstract": "Snow algae, a group of photosynthetic microorganisms that are adapted to live in frozen habitats, are the major group of primary producers in alpine and polar snow ecosystems. These organisms have complex life cycles intimately connected to environmental conditions and seasonal habitat transformations. When snow algae bloom on the top of snow, their high biomass darkens snowfields due to red-colored protective pigments produced inside the algal cells. Snow algae blooms increase melting of snow and glaciers, promoting more growth due to the availability of liquid water, and resulting in a positive feedback loop. Despite their ecological importance, we still do not know how blooms form. This project is studying the dynamics of snow algae blooms by addressing the relationships between snow algae physiology, growth and reproduction, and their environment using field and laboratory-based experiments. This research is also providing a primarily undergraduate institution with a new, powerful instrument for simultaneously measuring photosynthesis and carbon fixation in algae that can be used in the field and facilitate field-based experiments. The results of this study build capacity for further studies that will help predict snow algal environment-biology interactions into the future.The connection between snow algal bloom dynamics, life cycle, and environmental conditions represents an opportunity to study ecosystem responses to climate warming in a tractable system. This project lays the foundation for characterizing the fundamentals of carbon fixation and primary productivity in snow algal blooms. It also increases our understanding of the fundamental role that snow algae physiology plays in the growth and reproduction of snow algae across life stages adapted to different habitats. The proposed field and laboratory methods will allow the development of an experimental design to simultaneously measure habitat conditions, primary productivity, and carbon fixation in natural populations and serves as a launch point for future studies and continued collaboration. The snow algal system presents an opportunity to study the evolution of climate-ecosystem feedbacks in environments threatened by significant habitat loss over the next century.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 } } ], "meta": { "pagination": { "page": 1383, "pages": 1397, "count": 13961 } } }