Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1392&sort=approved
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=approved", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=approved", "next": null, "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1391&sort=approved" }, "data": [ { "type": "Grant", "id": "12667", "attributes": { "award_id": "2219587", "title": "Collaborative Research: CISE-MSI: DP: SCH: Privacy Preserving Tutoring System for Health Education of Low Literacy Hispanic Populations", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "CISE MSI Research Expansion" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28583, "first_name": "Renu", "last_name": "Balyan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1249, "ror": "https://ror.org/02rrhsz92", "name": "SUNY College at Old Westbury", "address": "", "city": "", "state": "NY", "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).This project will implement a computer tutor for low literacy Hispanic breast cancer survivors. Breast cancer is the leading cause of cancer-related deaths in Hispanics, and although research has shown that education can greatly mitigate stress and improve quality of life, few educational interventions for this population exist. The computer tutor resulting from this project will mimic a human tutor that teaches about breast cancer survivorship skills and about breast cancer in general. Because tutoring involves conversation with the survivor, it is possible that they reveal sensitive personal information; therefore, it is important to encrypt the information in the tutoring session to prevent any privacy breaches. And for the tutoring component to be effective, special attention must be paid to the utilization of natural language processing models as well as models of behavior that are observed in the target population when tutoring and/or interacting with technology. For the privacy component to be effective, techniques that can encrypt and decrypt data at high speeds will be explored to make the interaction fluid. To date, computer tutors that converse with their students have been tried mainly with a highly literate population in college settings, so their impact on low literacy Hispanics is unknown. Therefore, this project will advance our understanding of the impact of designing artificial intelligence powered tutors to address diversity and disparities in the access to information by a subset of low literacy individuals, as well as our understanding of privacy preserving algorithms that work in real-time with complex natural language processing models. More broadly, project outcomes will facilitate access to information for minority populations and will serve to build research capacity and train minority students in the participating teaching-oriented institutions.The project will be carried out with two objectives in mind. First, development of a novel intelligent computer tutoring system that is customized so that it can effectively query and interact with Hispanic breast cancer survivors by adapting existing content that was created for this population in prior research. Because it has been shown that both the language of many adult Hispanics, and target population interactions with technology, are more nuanced than previously thought, our first objective also involves training natural language algorithms and designing interactions that model those of Hispanic breast cancer survivors. The second objective is to develop privacy-preserving algorithms that utilize robust end-to-end encrypted communication and can encrypt and decrypt distributed data in real time at a speed that does not hinder the interactions with the computer tutor. The contributions of this development process will be threefold: (1) to understand the role of culture and education in the interaction between low literacy Hispanic breast cancer survivors and intelligent tutoring systems; (2) to develop a framework that facilitates the implementation of intelligent tutoring systems for minority populations; and (3) to develop accurate and low latency privacy preserving mechanisms for NLP model training and dialogue interfaces.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": "12668", "attributes": { "award_id": "2219212", "title": "Collaborative Research: A Partnership in Central Missouri in the Era of Multi-messenger Astrophysics", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "PAARE" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28584, "first_name": "Marco", "last_name": "Cavaglia", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 504, "ror": "https://ror.org/00scwqd12", "name": "Missouri University of Science and Technology", "address": "", "city": "", "state": "MO", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole under the American Rescue Plan Act of 2021 (Public Law 117-2). A new research and education partnership will be developed in central Missouri as a pilot program between Lincoln University of Missouri and the Missouri University of Science and Technology (S&T). The core mission of this new partnership is to provide training and increase research opportunities in astronomy and astrophysics among underrepresented and underserved students in central Missouri, building on a nascent astrophysics program. This two-year project is a pilot program toward the creation of a longer-term partnership which leads eventually to a formal S&T PhD bridge program for students at Lincoln University and other surrounding minority-serving institutions, contributing to increasing Missouri’s diversity in astronomy. The team members will regularly participate in public lectures at the local library and high schools to promote the importance of fundamental science among the public.This program will offer student exchange visits, winter and summer workshops, and summer research internships to train underrepresented and underserved students, which will allow them to consider a STEM career or PhD program in astronomy. These activities will train young researchers at S&T to improve their presentation, mentoring, and management skills. The proposal team conducts complementary research covering cosmology and galaxy evolution, gravitational-wave physics, and the physics of the interstellar medium. Within the project duration, the Hobby-Eberly Telescope Dark Energy Experiment is expected to release the measurement of dark energy properties at high redshift. The Laser Interferometer Gravitational-wave Observatory will detect more gravitational wave sources in the O4 Observing run and advance the knowledge of black holes and neutron stars. Machine learning applications will play significant roles in advancing these data analyses, which will be leveraged to train students as educational 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": "12669", "attributes": { "award_id": "2219090", "title": "AstroCom NYC: A Partnership between New York City Astronomers", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "PAARE" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28585, "first_name": "Mordecai-Mark", "last_name": "Mac Low", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2128, "ror": "", "name": "CUNY York College", "address": "", "city": "", "state": "NY", "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). AstroCom NYC is a program designed to improve the access of urban minority students to opportunities in astrophysical research by enhancing and solidifying partnerships between research astronomers in New York City. The partners are minority-serving institutions of the City University of New York (CUNY), and the astrophysics research departments of the American Museum of Natural History (AMNH) and the Center for Computational Astrophysics (CCA) at the Flatiron Institute. A renewed program, which builds on the success of the original AstroCom NYC, will cement a lasting and sustainable partnership spanning all five boroughs of New York City to provide centralized, personalized mentoring as well as financial and academic support to CUNY undergraduates throughout their studies, plus the resources and opportunities to further CUNY faculty research with students.The partners have created a formal conduit for CUNY students (the majority of whom are poor, urban students from groups underrepresented in STEM) to participate in research in astronomy. The partners in AstroCom NYC have many years of experience mentoring undergraduates in research on galaxy properties and evolution, black hole physics, nearby and low-mass stars, numerical simulations and modeling, and observational astronomy from the radio to gamma rays. They are also well-qualified for the task of improving minority access to astrophysics research because of their strong working relationships, expertise and enthusiasm for mentoring students with diverse backgrounds, and the ready pool of participant candidates from within CUNY. AstroCom NYC serves as a model to urban areas with large and diverse minority populations, and the participants publish widely, present progress reports nationally, conduct faculty professional development, and serve on review panels based on their expertise in engaging diverse populations.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": "12670", "attributes": { "award_id": "2221912", "title": "The Alliance for Identity-Inclusive Computing Education-Postdoctoral Research Fellowship (AIICE-PRF)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Directorate for STEM Education (EDU)", "Postdoctoral Fellowships" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28586, "first_name": "Eduardo", "last_name": "Bonilla-Silva", "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 is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). While computer science has transformed society, there are striking examples of how the groundbreaking technologies underlying this transformation have proven extremely harmful for people from groups who are historically underrepresented in computing. One notable instance is facial recognition software trained on a set of images with limited racial diversity. The resulting bias in such software can be attributed to the lack of diversity in academic and professional computing environments. Successfully broadening participation in computing requires computing faculty and researchers who can create/implement identity-inclusive computing curricula, policies, and practices, as well as perform innovative research in computing education. The Alliance for Identity-Inclusive Computing Education-Postdoctoral Researcher Fellowship (AiiCE-PRF) is based on evidence that the lack of diversity in university computer science departments is replicated in the computer science and computing education research community in terms of researcher identities, research topics, and available postdoctoral researcher positions. This marginalization impacts postdocs’ sense of belonging, publication and citation counts, and thus future hiring and career advancement. The AiiCE-PRF program will combine research and professional development activities related to computing education as well as provide best practices for identity-inclusive postdoc experiences that can be leveraged across STEM disciplines.The goal of the AiiCE-PRF is to increase the number of postdocs from groups who are historically underrepresented in computing and the number of postdocs performing identity-inclusive computing education research. The three-year project includes a research initiative where Fellows perform mixed-methods research related to training, curricula and pedagogy, policy, and student/faculty perceptions of race in computing. Fellows also participate in a professional development program that focuses on the three key components of a faculty portfolio: research, teaching, and service. Throughout this experience, fellows will work with the project team, members of the greater AiiCE alliance (who span disciplines, sectors, and identities), and each other to also develop independent research projects that will serve as the foundation for their future programs of research. Ultimately, the AiiCE-PRF will 1) increase fellows’ understanding of and preparation for academic careers; 2) increase fellows’ sense of belonging in the discipline (both as a postdocs and members of groups that are historically underrepresented in computing); and 3) contribute to best practices for supporting computing postdocs across the discipline.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": "12671", "attributes": { "award_id": "2213401", "title": "LEAPS-MPS: Taming the Radicals-Manipulating Lattice-Confined Metalloradicals for C-H Activation", "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": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28587, "first_name": "Wenyang", "last_name": "Gao", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 923, "ror": "https://ror.org/005p9kw61", "name": "New Mexico Institute of Mining and Technology", "address": "", "city": "", "state": "NM", "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). In this project, funded by the Mathematical and Physical Sciences Directorate and housed in the Chemistry Division, Professor Wenyang Gao and his students at New Mexico Institute of Mining and Technology will take advantage of the high reactivities of chemicals known as radicals (i.e. molecules that have odd numbers of electrons) and apply them to promote reactions of light hydrocarbons. Advances in hydraulic fracturing technologies provide vast available reserves of domestic light hydrocarbons, e.g., natural gas. Insufficient processing infrastructure coupled with the challenge of long-range transportation of gaseous hydrocarbons has prevented efficient utilization of these resources. A significant amount of natural gas has to be burned in on-site flares to avoid its direct atmospheric release. Chemical upgrading of light hydrocarbons, for instance, transforming gaseous methane into liquid methanol, is expected to turn these resources into chemical fuels or industrial feedstocks that have increased ease of handling, transport, and storage. Prof. Gao’s work will address the lack of chemical approaches for transforming methane efficiently and selectively by trapping highly reactive metal-containing radicals in rigid porous materials known as metal-organic frameworks, which will facilitate the desired reactions of light hydrocarbons. Meanwhile, the project will engage underrepresented minority students working on addressing sustainability and energy-related issues and prepare them as role models for the future scientific workforce.The project will take advantage of the high reactivities of radicals and apply them for the activation of light hydrocarbons. Prof. Gao and his students will utilize metal-organic frameworks, and their lattice confinement effect, to tame the highly reactive metalloradicals and utilize these species for hydrocarbon conversion. This project expects to provide synthetic access to solid-state radicals, examine their structures and reactivities, and obtain understanding on how tamed radicals to impact the chemical valorization of light hydrocarbons. This project will not only develop novel synthetic chemistry to access lattice-confined metalloradicals in the solid state, but also examine these highly reactive metalloradicals towards activating strong C(sp3)–H bonds in simple hydrocarbons.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": "12672", "attributes": { "award_id": "2144209", "title": "CAREER: Toward A Knowledge-Guided Framework for Personalized Decision Making", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Info Integration & Informatics" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28588, "first_name": "Jundong", "last_name": "Li", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 517, "ror": "", "name": "University of Virginia Main Campus", "address": "", "city": "", "state": "VA", "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).Learning causality from data is a vital stepping stone toward building human-level intelligent systems that can make appropriate decisions. In seeking to make an optimal decision for each individual (i.e., personalized decision making), we need to understand the causal relationship between a decision and its consequent outcome. Causal inference provides a principled way to achieve personalized decision making by learning individual-level causal effects from observational data. Its impacts are seen in a broad spectrum of application domains. However, existing causal inference frameworks are mostly data-driven and face multifaceted challenges (at the assumption-, data-, and application-level) when applied in real-world observational studies. Despite that, a vast amount of prior human knowledge manifests itself in different ways and could be leveraged to tackle these challenges. Although abundant human knowledge provides great opportunities, its complex nature coupled with observational data also imposes tremendous hurdles. This project aims to bridge the gap between what can be accessed (i.e., a large amount of observational data across different domains and human knowledge in different formats) and what is desired (i.e., more effective causal inference to advance personalized decision making).This project develops a suite of novel causal inference models and algorithms to analyze observational data by harnessing the power of human knowledge and gaining deeper insights to advance personalized decision making. First, it leverages relational knowledge that describes the relations among data instances in observational data, investigates its role in relaxing overly optimistic assumptions for causal inference. Second, it explores meta knowledge that depicts distinct properties of observational data and develops principled causal inference models and algorithms to incorporate such knowledge. Third, it aims to improve the utility of existing data-driven causal inference frameworks by harnessing application knowledge, which characterizes the unique needs of real-world applications. The outcomes of this project will enable researchers and practitioners to assimilate massive amounts of observational data, across numerous application domains, and leverage abundant human knowledge, to benefit scientific discovery and informed decision making. Outcomes of this project will be integrated into the existing curricula and new courses. This project will also provide research opportunities to undergraduate and graduate students, especially female and underrepresented minorities. Customized research and teaching components will be designed and implemented to attract K-12 students in STEM education and engage them in causal inference and data science research. Last but not least, this project will improve student success and retention via a unique educational decision making component. This approach will optimize current education systems, for the benefit of generations of students to come.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": "12673", "attributes": { "award_id": "2119883", "title": "GP-IN: CUSP: Connecting Underserved Students to Polar STEM", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "Polar Special Initiatives" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28589, "first_name": "Deborah", "last_name": "Shulman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 665, "ror": "https://ror.org/01adr0w49", "name": "University of Maine", "address": "", "city": "", "state": "ME", "zip": "", "country": "United States", "approved": true }, "abstract": "Recent changes in the Polar regions such as atmospheric warming, permafrost thaw, sea ice decline, and glacier retreat, are having global impacts. Understanding these Polar changes and predicting their future global impacts require a wide range of future science, technology, engineering, and mathematics (STEM) professionals. Unfortunately, less than 25% of high school students in the United States receive Earth systems science training and Polar studies represents a very small component of what is taught. Additionally, the majority of Earth systems societal challenges disproportionately impact low income and underrepresented populations, yet there is a significant deficiency in the number of underrepresented students receiving training within these fields. In fact, most Earth systems science programs lack gender, ethnic, and economic diversity. Effective environmental solutions require communication between scientists, policy-makers, and the public, and must also support all communities, in particular, those most at risk. The project aims to help remedy gaps in Polar STEM education by developing new opportunities for underrepresented high school students to engage in real Polar STEM education in the classroom and via field experiences. Additionally, the project aims to train teachers in high schools to integrate Polar STEM experiences in their classrooms to increase Polar STEM literacy within the United States. The researchers specifically propose to help fill the gaps in Polar Earth systems science education within the United States by developing a collaborative consortium of education programs including the University of Maine, Juneau Icefield Research Program (JIRP), and several Department of Education funded Upward Bound Programs across the United States to offer 1) new project-based field opportunities in Polar STEM for high school students from low income or first generation college families, 2) teacher training in Polar Earth systems sciences 3) help to teachers developing high school lessons using authentic Polar STEM data, and 4) research focused on determining if our field and classroom education program improves teaching and high-school student learning about Polar environments. This project will specifically support justice, equity, diversity, and inclusion, of underrepresented students within the Polar geosciences and help develop a more diverse and representative next generation of science leaders in more communities across the United States.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": "12674", "attributes": { "award_id": "2219183", "title": "Collaborative Research: A Partnership in Central Missouri in the Era of Multi-messenger Astrophysics", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "PAARE" ], "program_reference_codes": [], "program_officials": [], "start_date": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28590, "first_name": "Ajay", "last_name": "Mishra", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 881, "ror": "", "name": "Lincoln University", "address": "", "city": "", "state": "MO", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole under the American Rescue Plan Act of 2021 (Public Law 117-2). A new research and education partnership will be developed in central Missouri as a pilot program between Lincoln University of Missouri and the Missouri University of Science and Technology (S&T). The core mission of this new partnership is to provide training and increase research opportunities in astronomy and astrophysics among underrepresented and underserved students in central Missouri, building on a nascent astrophysics program. This two-year project is a pilot program toward the creation of a longer-term partnership which leads eventually to a formal S&T PhD bridge program for students at Lincoln University and other surrounding minority-serving institutions, contributing to increasing Missouri’s diversity in astronomy. The team members will regularly participate in public lectures at the local library and high schools to promote the importance of fundamental science among the public.This program will offer student exchange visits, winter and summer workshops, and summer research internships to train underrepresented and underserved students, which will allow them to consider a STEM career or PhD program in astronomy. These activities will train young researchers at S&T to improve their presentation, mentoring, and management skills. The proposal team conducts complementary research covering cosmology and galaxy evolution, gravitational-wave physics, and the physics of the interstellar medium. Within the project duration, the Hobby-Eberly Telescope Dark Energy Experiment is expected to release the measurement of dark energy properties at high redshift. The Laser Interferometer Gravitational-wave Observatory will detect more gravitational wave sources in the O4 Observing run and advance the knowledge of black holes and neutron stars. Machine learning applications will play significant roles in advancing these data analyses, which will be leveraged to train students as educational 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": "12675", "attributes": { "award_id": "2213408", "title": "LEAPS-MPS: Rational design of macromolecular assemblies controlled via plasmonic activation", "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": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28591, "first_name": "Julianne", "last_name": "Griepenburg", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 230, "ror": "", "name": "Rutgers University Camden", "address": "", "city": "", "state": "NJ", "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). LEAPS-MPS: Rational design of macromolecular assemblies controlled via plasmonic activationPART 1: NON-TECHNICAL SUMMARYIn nature, light controls a large number of physical and biological processes. In synthetic systems, using light as a trigger to initiate processes is beneficial because it is often biocompatible, and can be well controlled in both time and space, especially through the use of ultrafast lasers. This proposal seeks to use light to trigger structural changes in macromolecules, such as in DNA assemblies and molecular storage compartments known as vesicles. Vesicles are of interest because they provide the ability to compartmentalize contents, preventing interaction with the surrounding environment; light-induced structural disruption could allow for their contents to be released on-demand. In order for this to happen, light must be converted into heat or mechanical energy which can disrupt surrounding structures. This can be achieved with the unique light-sensitive properties of small gold particles known as nanoparticles, sometimes only consisting of a few hundred atoms. DNA assemblies can assist in this process by providing a scaffold for nanoparticle placement. The thorough investigation of these interactions has the potential to be transformative for applications in biotechnology and nanotechnology, for example, drug-delivery, allowing for therapeutics to be released in a specific location within the body to reduce side effects in healthy tissues or cells. In addition to important scientific applications, a significant goal of this proposal is to provide experiential learning opportunities for students at Rutgers University-Camden. Such opportunities are essential on this campus, to increase engagement in the large population of first-generation college students as well as students who identify with groups commonly underrepresented in STEM fields. Recruitment, training, and mentoring will ensure that students become highly competitive for future endeavors in industry and academia. The campus location in the heart of Camden, NJ provides unmatched opportunities for outreach in the surrounding community. Towards this goal, an outreach program called MEDIA (Meeting Exceptional Diverse Inclusive Academics) will be launched, where a diverse group of scientists from Rutgers-Camden will interact with grade school students; the goal of this program is early intervention to dissuade common scientist gender and race stereotypes frequently portrayed by the media that can limit interest in and later pursuit of scientific study.TECHNICAL SUMMARYPlasmonic nanoparticles, such as those comprised of gold, hold great potential as photosensitizers due to their unique optical properties which allow them to strongly absorb light and convert that energy into a localized response; the localized surface plasmon resonance absorption wavelength can be readily tuned through size, shape, organization, and composition. This plasmonic response can result in thermal and/or mechanical disruptions to the surrounding environment. This proposal hypothesizes that plasmonic effects can disrupt both the local organization of both diblock copolymer bilayer membranes which make up polymersome carrier vesicles, as well as DNA origami assemblies, both together and individually. The first aim of this work proposes to address the level of disruptions (i.e., poration vs. thermal dissociation). In Aim 2, the fundamental knowledge acquired in Aim 1 will be used to rationally design polymersome-DNA heterovesicles. The ability to control and detect the macromolecular organization of each component will be developed, to gain high spatiotemporal control over dissociation, poration, and cargo release in response to pulsed irradiation. Synergistically, this work will open doors to many training opportunities for undergraduate, M.S., and Ph.D. students at Rutgers-Camden, creating a hierarchy of opportunity, mentorship, and productivity. A large emphasis will be on the recruitment and retention of first generation college students and students from groups underrepresented in STEM, by providing paid research training and creating a sense of belonging in the scientific community through opportunities such as conference presentations. Proposed outreach programs in grade schools in the local Camden, NJ community will ensure the future diversity of STEM scholars by working towards offsetting the commonly media portrayed racial and gender stereotypes of scientists, through a program entitled MEDIA (Meeting Exceptional Diverse Inclusive Academics).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": "12676", "attributes": { "award_id": "2212922", "title": "LEAPS-MPS: Topological Symmetries of Non-Compact Riemann Surfaces", "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": "2022-09-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28592, "first_name": "Nicholas", "last_name": "Vlamis", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 722, "ror": "", "name": "CUNY Queens College", "address": "", "city": "", "state": "NY", "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). This project concerns research within the field of topology, a branch of mathematics with a focus on understanding the global large-scale structure of spaces, in contrast to geometry’s focus on local fine structure. The abstract nature of topology has made it a useful tool throughout the sciences, from asking questions regarding the shape of the universe to understanding the large-scale properties of complex networks. This project focuses on understanding topological symmetries of Riemann surfaces, which are two-dimensional objects, including the complex plane, the two-dimensional sphere, and objects that look like the surface of a doughnut. Riemann surfaces appear in almost every branch of mathematics and naturally arise in science, especially via string theory and via the solutions of differential equations. In addition, the project has several outreach components aimed at supporting students in pursuing a career in the mathematical sciences. The PI will create an organization dedicated to building a network of alumni to foster relationships in the community and create internship opportunities. Additionally, the PI will host several career panels featuring former students working in a diverse range of fields and will provide research experiences for undergraduates. The research is focused on understanding the algebraic structure of the (topological) mapping class group of a Riemann surface. In the finite-area case, the structure of mapping class groups is well understood, and the theory has deep connections to geometric group theory and Teichmüller theory. This project investigates the infinite-area case, where relatively little is known. The main goal is to characterize the countable-index normal subgroups of mapping class groups of infinite-area Riemann surfaces. The investigation will forge new connections between low-dimensional topology and recent developments in topological group theory.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": 1392, "pages": 1392, "count": 13920 } } }