Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1392&sort=-keywords
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-keywords", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=-keywords", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1393&sort=-keywords", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1391&sort=-keywords" }, "data": [ { "type": "Grant", "id": "10455", "attributes": { "award_id": "2050542", "title": "Building Capacity to Increase the Pool of Highly Qualified STEM Teachers in High-Need Texas School Districts with Predominantly Hispanic Student Populations", "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": 1859, "first_name": "Mike", "last_name": "Ferrara", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-01", "end_date": "2022-05-31", "award_amount": 74970, "principal_investigator": { "id": 26459, "first_name": "David", "last_name": "Turner", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26458, "first_name": "Angeli M", "last_name": "Willson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 404, "ror": "", "name": "St Mary's University San Antonio", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "This project aims to address the need for science, technology, engineering, and mathematics (STEM) K-12 teachers at both the national and regional level. Toward this aim, St. Mary’s University, a four-year Hispanic Serving Institution in San Antonio, Texas, will work with local education agency partners to evaluate and build capacity within its STEM Teacher Certification programs. The project will focus broadly on improving the pipeline for STEM majors seeking teacher licensure. In addition, it will encourage STEM pre-service teachers to teach in high-need schools and develop strategies and resources to support STEM pre-service teachers through their undergraduate studies and early stages of their professional K-12 teaching careers. This effort will include a careful investigation of available resources that might influence the development of an effective teacher preparation program and partnerships with local school districts. The project will also work to understand factors that impact Hispanic and other students as they make educational and career choices. \n\nThis project at St. Mary’s University includes partnerships with the Northside Independent School District (Northside ISD) and the San Antonio ISD. Project goals include: 1) analyzing baseline data to explore the need for highly qualified STEM teachers in the partner local education agencies; 2) understanding the motivations and obstacles faced by Hispanic and other students as they make educational and career choices, particularly whether to major in STEM fields and to pursue a career as a K-12 STEM educator; 3) evaluating the existing university infrastructure for a robust program for student recruitment and STEM teacher preparation; and 4) developing a comprehensive plan to enhance the University’s ability to (a) successfully recruit, retain, and graduate talented students as STEM teachers; and (b) to support them during their first year as teachers in high-needs school districts. The project will generate new knowledge about effective recruiting and support mechanisms for diverse pre-service teachers, in partnership with school districts that have predominantly Hispanic student populations. Project outcomes are expected to contribute to ongoing efforts to broaden participation in K-12 STEM teaching. This Capacity Building 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 persistence, retention, and effectiveness of K-12 STEM teachers in high-need school districts.\n\nThis 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": "10456", "attributes": { "award_id": "2105958", "title": "I-Corps: Aquatic debris cleanup using multi-agent unmanned surface vehicles and hotspot-based path optimization", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "I-Corps" ], "program_reference_codes": [], "program_officials": [ { "id": 602, "first_name": "Ruth", "last_name": "Shuman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-15", "end_date": "2022-08-31", "award_amount": 50000, "principal_investigator": { "id": 26460, "first_name": "Jan", "last_name": "Kleissl", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 258, "ror": "", "name": "University of California-San Diego", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this I-Corps project is to benefit US shorelines. The World Economic Forum predicts that by 2050 there will be more plastic than fish in the world's oceans. Waterfront maintenance workers face the brunt of the marine trash pollution issue as 80% of marine trash is sourced near-shore. As a result, waterfront governments alone spend a total of $10.2 billion to clean these waterways. The proposed technology benefits ecosystems by removing trash pollution from our shores, thereby preventing ecosystem degradation and allowing people to both benefit from marine services now and in the future. \n\nThis I-Corps project introduces the use of Unmanned Surface Vehicles (USV) to maximize debris cleanup performance and provide affordable solutions to cleaning these waterways. Solutions are being developed to address the oceanic plastic pollution problem once the debris is already in the ocean; however, insufficient effort is directed towards improving shoreline pickup, which contains 80% of plastic debris. Human-operated methods to collect the debris is inefficient and cost ineffective. This opens the door to expand USV technology to waterway maintenance. Similarly, USV environmental monitoring capabilities may provide data to the waterways and researchers such as oxygen monitoring for algae blooms and affordable data capture. The team currently has a working prototype and partnerships at the Jacobs School of Engineering and Scripps Institution of Oceanography. The I-Corps customer discovery activities will reveal the exact pain points experienced in these waterways to inform the proposed technology.\n\nThis 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": "10457", "attributes": { "award_id": "2050736", "title": "REU Site: Advancing Space Sciences through Undergraduate Research Experiences (ASSURE)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "EDUCATIONAL LINKAGES" ], "program_reference_codes": [], "program_officials": [ { "id": 7194, "first_name": "Manda S.", "last_name": "Adams", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-06-01", "end_date": "2022-05-31", "award_amount": 159728, "principal_investigator": { "id": 26462, "first_name": "Matthew", "last_name": "Fillingim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26461, "first_name": "Trevor A", "last_name": "Bowen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 176, "ror": "", "name": "University of California-Berkeley", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The Advancing Space Sciences through Undergraduate Research Experience (ASSURE) program at the University of California Space Sciences Laboratory provides undergraduate students with an immersive experience in space science research and engineering. Students are exposed to a multidisciplinary research laboratory setting, conducting cutting edge research alongside leaders in the field. The ASSURE program actively recruits participants from community colleges and other institutions serving populations historically underrepresented in the space and geosciences with the aim of providing research experience early in their careers. The interdisciplinary approach taken in the program is reflective of the range of skills that students may eventually face in the workforce.\n\nThe ASSURE program supports research projects relating to the development of spacecraft instrumentation and hardware, data analysis, and high performance computing at the forefront of federally funded geospace research. Students involved in the program acquire experience required for design and management of experimental research programs and support a range of on-going geospace missions. The research staff at SSL is composed of a diverse international community working on a range of space physics missions in radio astronomy, magnetospheric physics, heliophysics, planetary science, high energy astrophysics, and maintains robust engineering facilities. The range of work at SSL provides ASSURE students with the opportunity to gain a comprehensive exposure to a range of geospace research, including space weather and other phenomena of national importance. Students will receive a boot camps session in coding and professional development on communication skills including elevator pitches and presenting at a professional conference.\n\nThis 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": "10458", "attributes": { "award_id": "2116697", "title": "Conference: Waves of Change", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Symbiosis Infection & Immunity" ], "program_reference_codes": [], "program_officials": [ { "id": 2558, "first_name": "Joanna", "last_name": "Shisler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-06-01", "end_date": "2022-05-31", "award_amount": 197803, "principal_investigator": { "id": 26463, "first_name": "Nikki", "last_name": "Traylor-Knowles", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 647, "ror": "https://ror.org/02dgjyy92", "name": "University of Miami", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "To help fulfill the mission of NSF to support basic research and science education this proposal aims to provide training, mentorship and scientific collaboration for minorities in microbiology, immunology, ecology, evolution and marine science. The initiative called, ‘Waves of Change’, will be accomplished through a year-long set of virtual professional development events that include panels, workshops, science information sharing, structured mentoring opportunities, and networking to increase retention of minorities in science. The outcomes from this proposal will have broader impacts on society by training a new generation of scientists, assisting in creating a diverse workforce, and expanding opportunities for early career scientists through networking and mentorship. \n\nScience is driven by innovation and discovery. This innovation is accelerated when diverse voices are heard. When people from different backgrounds can work together on a common goal, science can achieve great things. However, to accomplish this goal, training is needed to bring together different perspectives and share information. This is particularly relevant in ecology, evolution, and marine science where collaborations are the foundation of success. This proposal called ‘Waves of Change’ will bring together diverse voices and create a forum for networking and professional development for early career scientists from underrepresented groups in ecology, evolution, and marine science. ‘Waves of Change’ will consist of monthly workshops, networking hours with scientific leaders, and panels that will address many including science policy, mentoring in academia and science, productivity in science, science communication, career paths in science, leadership in academia and beyond, self-care in science, scientific publishing, computational skills in science, challenges in science, networking, decolonization of science, and outreach-community based science. The goal of ‘Waves of Change’ will be to build community and networking opportunities with the scientific community at large while contributing to the retention and success of diverse scientists.\n\nThis 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": "10459", "attributes": { "award_id": "2129185", "title": "Student Travel Support to 3D Printing of Polymeric Composites & Hybrid Systems Symposium at American Chemical Society National Meeting; San Diego, California; March 20-24, 2022", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "AM-Advanced Manufacturing" ], "program_reference_codes": [], "program_officials": [ { "id": 2084, "first_name": "Khershed", "last_name": "Cooper", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-06-01", "end_date": "2022-05-31", "award_amount": 47984, "principal_investigator": { "id": 26464, "first_name": "Kenan", "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": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "This award provides travel support for students, post-docs and young faculty to attend and participate in the Symposium on \"3D Printing of Polymeric Composites and Hybrid Systems \" at the Spring American Chemical Society (ACS) national meeting in San Diego, CA, in March 20-24, 2022. The symposium focuses on new research in the field of polymer processing, composite and hybrid systems and additive manufacturing. The students present through oral and poster sessions their latest research results to the polymer processing, advanced manufacturing and broader engineering communities. Priority is given to student and young faculty participants who are women or who come from underrepresented minority groups. This approach promotes diverse participation at the conference, in the short term, and in STEM fields, in the long term. This award benefits the nation through the education of a skilled and diverse manufacturing workforce, which is better prepared to provide transformative solutions the challenges in their chosen fields.\n\nThis participant support is expected to benefit the students' professional, scientific and technical development. Attendance at the conference gives the students and young faculty a broader view of the polymer processing, composite and hybrid systems, additive manufacturing and engineering profession and of state-of-the-art research in their fields via access to several technical and professional development talks by leading domestic and international speakers. In particular, the symposium will discuss sustainability, recycling and remanufacturing. It will also discuss 3D printing strategies to mitigate polymer waste. Students enhance their communication skills through oral and poster presentations, in-depth discussions of their work with peers in their fields. This interactive experience significantly broadens student education, increases their enthusiasm for their research topic, acquaints them with expectations for scientific careers, and exposes them to new approaches for innovative research.\n\nThis 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": "10460", "attributes": { "award_id": "2107108", "title": "III: Small: Learning Multi-scale Sequence Features for Predicting Gene to Microbiome Function", "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": [ { "id": 864, "first_name": "Sylvia", "last_name": "Spengler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-09-01", "end_date": "2024-08-31", "award_amount": 492871, "principal_investigator": { "id": 7627, "first_name": "Gail", "last_name": "Rosen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 377, "ror": "https://ror.org/04bdffz58", "name": "Drexel University", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Microbial communities play vital roles in health and the environment. In human health, they are referred to as our microbiomes; for example, healthy gut microbiomes can help digest and efficiently convert food to nutrients to be taken up in our gut. However, what constitutes “unhealthy” (dysbiotic) microbiomes and how they can affect or be affected by the body (or environment) is unknown. If we can understand microbes’ interactions with each other and the body, then we can design better treatments, therapies, and medicines (e.g. pre- and pro-biotics) to manipulate microbiomes. To understand the ``rules'' for microbial ecosystems, we must first solve the genotype-to-phenotype problem, i.e. identify microbial genetic changes which correlate to changes in microbiome functioning/traits. Most researchers have simply focused on predicting environmental or disease phenotypes by solely using microbiome community structure (ie: a population census of species in a community) and do not consider detailed DNA/RNA differences. It is not surprising that most studies have yielded modest prediction accuracy and little understanding of how microbiomes function. Attributing which “configurations” of organisms and/or genes contribute to a particular “microbiome state” can help us predict disease, understand how the environment may change microbial ecosystems, and be able to predict future changes of these systems (e.g. perturbations due to a chemical, temperature, etc.). Methods that can learn pertinent features at multiple scales (genome-, organism-, and community-level) simultaneously, are needed to interpret both the “species census” and microbial genetic changes (mutations that may lead to speciation and/or functional evolution) that influence community structure. Our educational activities will bring cutting edge research and topics to undergraduate and graduate education in Bioinformatics-related courses, which are part of Machine Learning and Bioinformatics Masters programs and a Bachelor’s bioinformatics minor at Drexel University. In addition, we plan to organize a Drexel College of Engineering-wide high school extracurricular program for mentoring of science projects for underserved public schools. \n\nA unified algorithm is needed to learn microbiome features on multiple levels to be able to predict microbiome functioning, thereby identifying biological processes (a.k.a harnessing data to understand the rules of life, NSF Big10 goals) that result in important “states” (e.g. disease or healthy). Doing so will transform our understanding of how large- and small-scale changes influence microbiome phenotypes. Current approaches are highly limited. Phenotype prediction based on 16S rRNA surveys is usually conducted solely on microbial operational taxonomic units (OTUs), which rarely capture the mutations that signify overall phenotypic changes. Phenotype prediction using metagenomes may perform better than 16S surveys, but many downstream analyses (feature selection, statistical tests) are needed to interpret (e.g. infer subcommunities relevant to phenotype) this classification. Therefore, we propose to develop a recurrent neural network (RNN) that can learn both community-level changes in the microbiome and genetic changes that relate to microbiome phenotypes. While most neural networks can ``learn'' features, it is usually difficult to get this information back out of the network (i.e.: interpretation). We will also use the recent advances in attention-based RNNs that will help us interpret which multi-scale features are most important to phenotype prediction. We will make our algorithms and software available to the microbiome community, whose potential applications include improving agriculture, environmental monitoring, personalized medicine, among others.\n\nThis 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": "10461", "attributes": { "award_id": "2129076", "title": "Co-Development of Telehealth, Remote Patient Monitoring, and AI-based Tools for Inclusive Technology-Facilitated Healthcare Work of the Future", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Unknown", "FW-HTF Futr Wrk Hum-Tech Frntr" ], "program_reference_codes": [], "program_officials": [ { "id": 1223, "first_name": "Alexandra", "last_name": "Medina-Borja", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-10-15", "end_date": "2026-09-30", "award_amount": 2499999, "principal_investigator": { "id": 7243, "first_name": "Oded", "last_name": "Nov", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 167, "ror": "https://ror.org/0190ak572", "name": "New York University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 8912, "first_name": "Batia M", "last_name": "Wiesenfeld", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26465, "first_name": "Devin", "last_name": "Mann", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26466, "first_name": "Rumi", "last_name": "Chunara", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26467, "first_name": "Olugbenga", "last_name": "Ogedegbe", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 167, "ror": "https://ror.org/0190ak572", "name": "New York University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "As the use of digital health technologies grows, gaps between the potential of new technologies, existing healthcare practices, and workers’ preparedness for new technologies limit the potential of digital health to achieve acceptance and effective utilization at scale. This transition to scale research project views inclusion as a key driver of scale in future technology-facilitated healthcare work. Inclusive technology for healthcare work will enable workers in diverse roles and skills to leverage increasing access to data-driven technologies. The project focuses on the growth of Data-Intensive Technologies (DIT), which include telehealth and AI-based tools. The project’s approach to transition to scale centers on alleviating existing misalignment between current healthcare work and data-intensive technologies in three ways. First is through the co-development of tools and generalizable design principles with users that lower the barrier to technology integration for healthcare workers. Second is by empowering individuals within healthcare systems who have diverse roles to adopt and use the tools and improve their skills. Third is to enable patient-centered healthcare that promotes autonomy and strengthens clinician-patient concordance. The project represents a multi-institutional commitment to transitioning innovative healthcare to scale, through DIT facilitated inclusion of diverse workers in healthcare systems across the U.S., which together encompass over 1000 care sites in U.S. 24 states, multiple work roles, and different levels of training and hierarchy.\n\nThis project brings together several scientific fields, including human-computer interaction, health informatics, artificial intelligence (AI), sensing, medicine, organizational behavior, and research on diversity and inclusion. The investigator team is structured to achieve multiple convergent goals such as quantifying the impacts of scaling DIT on inclusive healthcare work and modelling prescription and adoption of DIT towards inclusive deployment at scale. Additionally, the investigators seek to identify generalizable DIT design principles for inclusive healthcare work at scale, and to develop theory and tools to facilitate at-scale inclusion through DIT-based patient-provider concordance. Finally, the project expects to develop tools and practices for lowering barriers to comprehension of and engagement with DIT by diverse healthcare workers; to create AI-based team-focused tools; and to analyze the opportunities and challenges in using AI for diverse healthcare teams’ work. This project has been funded by the NSF Future of Work at the Human-Technology Frontier cross-directorate program to promote deeper basic understanding of the interdependent human-technology partnership in work contexts by advancing design of intelligent work technologies that operate in harmony with human workers.\n\nThis 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": "10462", "attributes": { "award_id": "2134945", "title": "The Rising Stars in Cell Biology Symposium", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Cellular Dynamics and Function" ], "program_reference_codes": [], "program_officials": [ { "id": 3441, "first_name": "Richard", "last_name": "Cyr", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-15", "end_date": "2022-07-31", "award_amount": 10892, "principal_investigator": { "id": 26468, "first_name": "Jian", "last_name": "Liu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 344, "ror": "https://ror.org/00za53h95", "name": "Johns Hopkins University", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "This award provides support for a one-day meeting “The Rising Stars in Cell Biology Symposium” to be held on April 29, 2022 at Johns Hopkins University. The purpose of the meeting is to provide an opportunity to early career scientists (undergraduate, post baccalaureate, graduate students, and postdoctoral fellows) from diverse backgrounds within the greater Baltimore area to present their research and network with their peers. The format of the meeting will comprise of one keynote talk, selected oral presentations, poster sessions, and career development platforms. In the short-term, this meeting will provide an opportunity to trainees to highlight their exceptional research, boost their confidence, expose them to a wide array of leading-edge research within cell biology, which may lead to increased recruitment of under-represented minority (URM) students into graduate programs or postdoctoral positions across the participating institutions. In the long-term, this meeting will attract URM scholars to Science, Technology, Engineering and Mathematics (STEM), specifically to life sciences and to generate a vibrant and supportive environment that encourages retention of URM scientists in academia. \n\nThis meeting is motivated by the recognition of socio-economic disparity and the need for opportunities truly available to URM scholars. The award will defray the basic organizing expenses to reach a wide group of trainees as well as institutions that predominantly serve URM scholars in the greater Baltimore area. In particular, the award will provide support for the meeting participants in the form of travel vouchers, working meals, poster printing, and childcare assistance. Availability of opportunities provided by the meeting will showcase the trainees’ work and form a peer network, which will encourage URM scholars to continue their academic pursuit and help increase diversity at higher ranks within academia. Additionally, with the participants from diverse backgrounds but sharing the common interest in cell biology, this meeting is expected to foster scientific collaborations at the forefront topics and advance research forward.\n\nThis 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": "10463", "attributes": { "award_id": "2119299", "title": "Collaborative Research: PPoSS: LARGE: Principles and Infrastructure of Extreme Scale Edge Learning for Computational Screening and Surveillance for Health Care", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "PPoSS-PP of Scalable Systems" ], "program_reference_codes": [], "program_officials": [ { "id": 637, "first_name": "Wei", "last_name": "Ding", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-10-01", "end_date": "2026-09-30", "award_amount": 2127227, "principal_investigator": { "id": 26470, "first_name": "Fan", "last_name": "Ye", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26469, "first_name": "Elinor R", "last_name": "Schoenfeld", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 578, "ror": "", "name": "SUNY at Stony Brook", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "This project investigates a completely new cross-disciplinary concept of “Computational Screening and Surveillance (CSS)” that utilizes edge learning to detect early indicators of diseases, and monitor health changes in both individuals and populations. CSS analyzes and interprets continuous and heterogeneous physical and physiologic sensing-data streams of human subjects to produce real-time information, knowledge, and insights about their health status. The project’s novelty is a data-driven paradigm that revolutionizes the understanding, prediction, intervention, treatment, and management of acute/infectious, chronic physical and psychological diseases. The project’s impacts are enormous social and economic benefits to individuals, organizations, and the healthcare system: early detection, preemptive intervention and management can lead to greatly improved quality of care, and huge savings for multiple diseases each costing hundreds of billions of dollars every year.\n\nThe investigators design, develop and evaluate principles and solutions for CSS enabled by extreme-scale edge learning spanning four dimensions: data modalities, health conditions and data patterns, Artificial Intelligence/Machine Learning (AI/ML) algorithms and models, and individuals/populations. The design is guided by four principles: exploit scale and heterogeneity, design for uncertainty, privacy as a first-class citizen, and faults and attacks as a norm. The investigators will 1) design AI/ML algorithms for learning data patterns and correlations for diverse health conditions in both individuals and populations at extreme scales; 2) quantify theoretical bounds on the tradeoffs between security, privacy protection, and learning accuracy in order to protect against various attacks on data and models at both the edge and cloud; 3) develop programming abstractions for automated exploration of competing AI/ML methods under uncertainty, and system mechanisms to protect stream processing integrity against sensitive data disclosure and faulty/malicious analytics; and 4) devise neural architectures and accelerators for computation efficiency at the constrained edge, data efficiency using limited training sets, and human efficiency utilizing AutoML.\n\nThis 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": "10464", "attributes": { "award_id": "2140283", "title": "Workshop: Human-Technology Interface Series - Pathways to Products for Lifelong Learning", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Outreach & Tech. Assist" ], "program_reference_codes": [], "program_officials": [ { "id": 1782, "first_name": "Rajesh", "last_name": "Mehta", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-01", "end_date": "2022-07-31", "award_amount": 99998, "principal_investigator": { "id": 26474, "first_name": "Andrea", "last_name": "Burrows Borowczak", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 8772, "first_name": "Carolyn P", "last_name": "Rose", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26471, "first_name": "Gabrielle D", "last_name": "Allen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26472, "first_name": "Mike", "last_name": "Borowczak", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 26473, "first_name": "Laurie O", "last_name": "Campbell", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1046, "ror": "https://ror.org/01485tq96", "name": "University of Wyoming", "address": "", "city": "", "state": "WY", "zip": "", "country": "United States", "approved": true }, "abstract": "This award leverages new fundamental understanding of human cognition and the extraordinary capabilities of current technology to support our Nation's capacity to nurture lifelong learning, advance economic competitiveness, and provide meaningful paths for careers subject to industrial transformation. This workshop convenes experts in all elements of education at the human-technology interface (HTI) to address topics including: regional, socioeconomic, demographic, and other disparities in technology access and associated solutions; capabilities to address learning difficulties, variability in learning modalities, cognition development, and other needs driving customized education; opportunities for convergent research at the interface of neuroscience, education, and remote technology; industrial workforce development needs, transformations, and partnerships; and associated translational pathways for new solutions. This project advances our understanding of the landscape for next-generation leadership of the Nation's educational ecosystem.\n\nThis project advances understanding in several technical disciplines, including: cognition variation by learning modality and associated assessment; transferability and generalizability of processes with varying levels of technology engagement; adaptive testing (customized automated evaluation processes); and scalability. In addition to synthesizing current research in technologies and cognition, the workshop will explore promising practices in cohort formulation, implementation, and assessment; experiential education and integrated learning; inclusion, belonging, and other social processes driving educational outcomes; and other elements of holistic education to identify best practices toward translation at scale.\n\nThis 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": 1424, "count": 14236 } } }