Grant List
Represents Grant table in the DB
GET /v1/grants?sort=funder
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=funder", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=funder", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=funder", "prev": null }, "data": [ { "type": "Grant", "id": "9536", "attributes": { "award_id": "2030139", "title": "Compounding Crises: Facing Hurricane Season in the Era of COVID-19", "funder": null, "funder_divisions": [], "program_reference_codes": [ "CK090", "RND123" ], "program_officials": [], "start_date": null, "end_date": null, "award_amount": 199890, "principal_investigator": null, "other_investigators": [], "awardee_organization": null, "abstract": "Test", "keywords": [ "covid", "research" ], "approved": true } }, { "type": "Grant", "id": "2498", "attributes": { "award_id": "2031385", "title": "EAGER: Fundamental Study on Multistage Sustainability Assessment and Decision Making for Reshaping Technology Innovations", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "EnvS-Environmtl Sustainability" ], "program_reference_codes": [], "program_officials": [ { "id": 7110, "first_name": "Bruce", "last_name": "Hamilton", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-09-01", "end_date": "2023-08-31", "award_amount": 219998, "principal_investigator": { "id": 7111, "first_name": "Yinlun", "last_name": "Huang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 179, "ror": "https://ror.org/01070mq45", "name": "Wayne State University", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 179, "ror": "https://ror.org/01070mq45", "name": "Wayne State University", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "This exploratory research project will create a framework for systematically assessing the sustainability of emerging technologies. Sustainability assessment and decision-making for technology innovations is a key step towards achievement of industrial sustainability goals. This research will address how technology innovation can be reshaped to fully incorporate sustainability principles from the early development stage. The approach will use a unique methodology that incorporates sustainability science, large-scale system science, and engineering. The methodology and case studies are anticipated to be valuable for enhancing research and education on the sustainability of emerging technologies.\n\nThe project will employ a methodological framework for conducting systematic sustainability assessment of emerging technologies in their early development life cycle stages by recommending technology sets after performing sustainability impact evaluation. The framework will feature capability to effectively apply sustainability science and systems theory to methodically conduct multistage sustainability assessment, identify intertwined sustainability aspects, systematically process uncertain information, and provide system-level optimal decision support for technology innovations in different product development and manufacturing stages. This framework will be constructed using a hierarchical assessment and decision making scheme, and consist of a coherent set of concepts, propositions, principles, and methods that could improve the ability of researchers, decision makers, and organizations to reshape technology innovations. The proposed framework will be tested through investigating new technologies for nanopaint design and coating manufacturing, as compared to current coating material and application technologies.\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": "2571", "attributes": { "award_id": "2018427", "title": "MRI: Expansion of the Molecular Education and Research Consortium in Undergraduate Computational ChemistRY (MERCURY) via Addition of High Performance Computers", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Major Research Instrumentation" ], "program_reference_codes": [], "program_officials": [ { "id": 7415, "first_name": "Deepankar", "last_name": "Medhi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-10-01", "end_date": "2023-09-30", "award_amount": 400000, "principal_investigator": { "id": 7418, "first_name": "George", "last_name": "Shields", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 893, "ror": "https://ror.org/04ytb9n23", "name": "Furman University", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 7416, "first_name": "Carol A", "last_name": "Parish", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 7417, "first_name": "Maria A", "last_name": "Gomez", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 893, "ror": "https://ror.org/04ytb9n23", "name": "Furman University", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true }, "abstract": "This high-performance computer (HPC) adds to the HPC MERCURY resources, and enables 12 more research groups to benefit, expanding the consortium to 38 computational chemists and physicists at 33 different institutions. The consortium is the Molecular Education and Research Consortium in Undergraduate computational chemistRY (MERCURY). Its objective is to increase the number of undergraduate students participating and benefiting from this stimulating and highly productive environment. The enabled research projects described utilize the tools of computational chemistry to solve significant problems in chemistry and chemical physics. \n\nThe Instrument is expected to increase the number of undergraduate students participating and benefiting from this stimulating and highly productive environment. The enabled research projects utilize the tools of computational chemistry to solve significant problems in chemistry and chemical physics. This Instrument expansion builds on the progress and momentum of the 2001 MRI grant, which allowed the consortium to purchase a high-performance computer and assisted in formally establishing rigorous, accessible research programs at the member institutions. The instrument enables research in computational chemistry, spanning the fields of biochemistry, biological, bioinorganic, biophysical, environmental, inorganic, materials, machine learning, nanoparticles, physical, physical organic, photochemistry, polymers, and solvation effects.\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": "2595", "attributes": { "award_id": "2016363", "title": "Collaborative Research: Learning by Touch: Preparing Blind Students to Participate in the Data Science Revolution", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Cyberlearn & Future Learn Tech" ], "program_reference_codes": [], "program_officials": [ { "id": 7519, "first_name": "Dan", "last_name": "Cosley", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-10-01", "end_date": "2023-09-30", "award_amount": 328112, "principal_investigator": { "id": 7520, "first_name": "Sile", "last_name": "O'Modhrain", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "Over the past decade the data science revolution has transformed the way scientists, engineers, and businesses work. A key enabler is the rise of interactive data visualization tools, which allow users to filter, analyze, and understand large data sets. Beyond static charts and graphs, interactive data visualization allows users to view data in different ways and from different perspectives, to build deeper understanding of trends, and to test hypotheses. However, Blind and Visually Impaired People have not been able to fully participate in this data revolution. Common tools for data analysis and data exploration are based on interactive spatial graphics, displayed on 2D screens. These spatial diagrams, charts, and other representations are not easily conveyed through speech or text – the typical ways in which Blind and Visually impaired people consume information through computers. This lack of access to common tools has presented a barrier for Blind and Visually Impaired People to enter STEM fields. History teaches us that, with the right tools, Blind and Visually Impaired People can contribute fully to highly technical fields. For example, many blind people are engaged as programmers and network administrators across a range of industries. It is evident that, if Blind and Visually Impaired People are provided with accessible tools that are functionally equivalent to those used by others and are able to interact with and generate their own data, they will take their place in the world of work, alongside their sighted peers. To address these issues, this project will work to: (1) increase understanding of data literacy amongst Blind and Visually Impaired People; (2) develop new tools and techniques, using touch and audio, to help prepare Blind and Visually Impaired People’s to understand and explore data. This is expected to begin to increase access to STEM concepts and materials in the BVI community, where access has previously been limited. Spatial information is ubiquitous in STEM; finding effective ways to make it accessible to everyone is imperative. Increasing access to Interactive Data Visualization tools will help prepare the Blind and Visually Impaired to participate as data scientists, software engineers, and informed citizens.\n \nThis research will work to make fundamental contributions in the fields of information visualization, assistive technology, and haptic perception, advancing our understanding of techniques for effective encoding and exploration of spatial information in alternate forms to graphical representation. It will also expand on guidelines for multi-modal haptic interaction with spatial information and create new open source software to enable these interactions. Finally, it will contribute to the field of informal STEM learning, providing understanding about data literacy and personal data exploration as a pathway to engage the Blind and Visually Impaired community in data science and STEM activities. The research will use a mixed methods approach, using co-design, qualitative and longitudinal field studies, and quantitative lab studies. Through 4 synergistic research themes, this project will expand knowledge of broadening access to interactive data visualization for Blind and Visually Impaired People by investigating: (1) current practices, gaps and needs in data literacy for Blind and Visually Impaired People; (2) how task goals affect exploration strategies for tactile perception of data for BVI people; (3) data exploration and manipulation strategies through co-design using an interactive tactile display; and (4) the efficacy of interactive tactile data exploration to expand data literacy for BVI people.\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": "2554", "attributes": { "award_id": "2039317", "title": "WORKSHOP: Doctoral Consortium at the 2020 Conference on Computer Supported Cooperative Work and Social Computing", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "HCC-Human-Centered Computing" ], "program_reference_codes": [], "program_officials": [ { "id": 7344, "first_name": "Ephraim", "last_name": "Glinert", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-08-01", "end_date": "2021-07-31", "award_amount": 4500, "principal_investigator": { "id": 7345, "first_name": "Jessica", "last_name": "Vitak", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 297, "ror": "https://ror.org/047s2c258", "name": "University of Maryland, College Park", "address": "", "city": "", "state": "MD", "zip": "", "country": "United States", "approved": true }, "abstract": "This is funding to support a doctoral research consortium (workshop) to take place in conjunction with the Association for Computing Machinery's 2020 Conference on Computer Supported Cooperative Work and Social Computing (CSCW), to be held virtually due to the current situation from October 17-21, and which is sponsored by the Association for Computing Machinery's Special Interest Group on Human Computer Interaction (SIGCHI). The CSCW conferences are the premier venue for the presentation of research relating to the design and use of technologies that affect groups, organizations, communities and networks. The development and application of new technologies continues to enable new ways of working together and coordinating activities. While work is an important area of focus for the conference, technology is increasingly supporting a wide range of recreational and social activities. CSCW has also embraced an increasing range of devices, as we collaborate from different contexts and situations. Research published at CSCW is heavily refereed and widely cited; the conference annually attracts over 700 top researchers from academia and industry around the world. The CSCW doctoral consortia, which began in 1992, have been highly successful in providing a forum for the initial socialization into the field of young doctoral scholars, and many of today's leading CSCW researchers participated as students in earlier consortia. These doctoral consortia traditionally bring together the best of the next generation of CSCW researchers, allowing them both to sharpen the research skills and to create a social network among themselves and with senior researchers at a critical stage in their professional development. Maintaining and fostering research dialog among the diverse disciplines that are present in the CSCW community results in synergistic and transformative research collaborations. Because the students and faculty constitute a diverse group across a variety of dimensions, including nationality/cultural and scientific discipline, the students' horizons are broadened to the future benefit of the field.\n\nThe Doctoral Consortium at CSCW 2020 will be a full-day event taking place the day before the main conference on October 18. Goals of the doctoral consortium include building a cohort group of new researchers who will then have a network of colleagues spread out across the world, guiding the work of new researchers by having experts in the research field mentor them and provide constructive advice, and making it possible for promising new entrants to the field to attend their research conference. Students will make formal presentations about their research, followed by discussion and constructive feedback both from members of the faculty panel and other student participants. The feedback will be geared to helping students understand and articulate how their work is positioned relative to other CSCW research, whether their topics are adequately focused for thesis research projects, whether their methods are correctly chosen and applied, and whether their results are appropriately analyzed and presented. Additionally, the mentors will discuss different aspects of research life, including career paths, funding, work-life balance, etc.\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": "2522", "attributes": { "award_id": "1955798", "title": "Collaborative Research: SHF: Medium: NetSplicer: Scalable Decoupling-Based Algorithms for Multilayer Network Analysis", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Software & Hardware Foundation" ], "program_reference_codes": [], "program_officials": [ { "id": 7197, "first_name": "Almadena", "last_name": "Chtchelkanova", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-07-01", "end_date": "2023-06-30", "award_amount": 373868, "principal_investigator": { "id": 7198, "first_name": "Sharma", "last_name": "Chakravarthy", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 293, "ror": "", "name": "University of Texas at Arlington", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 293, "ror": "", "name": "University of Texas at Arlington", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "A multilayer network is a powerful and expressive mathematical tool for modeling and analyzing social, economic, biological, and technological systems. Informally, a multilayer network is a collection of related graphs. Applications of multilayer networks include understanding social networks, economic systems, online marketplaces, and detecting vulnerabilities in cyber-physical systems. While this research area is rapidly growing, there is a dearth of computational tools for analyzing large-scale networks from diverse applications. This project will develop the theoretical foundations and software infrastructure for analyzing very large multilayer networks on modern computing systems, thereby enabling their widespread use in diverse applications.\n\nThis project will develop NetSplicer, a collection of scalable high-performance algorithms for multilayer-network analysis. The approaches in NetSplicer will be based on a divide-and-conquer-like technique called network decoupling. Using decoupling, the multilayer network can be subdivided into multiple components, each of which could be potentially analyzed using known graph algorithms. Network decoupling seeks to address issues that are critical for multilayer analysis, such as reducing information loss and preserving structural and semantic information. The challenges in efficiently applying network decoupling include determining optimal decoupling strategies, preserving the structure and content of multilayer networks that have multiple vertex and edge types, and developing architecture-aware scalable algorithms that apply across different layers of a network. This project will provide a new capability for multiple research communities and will build a repository for multilayer networks. The planned collaborations with domain scientists from academia and industry, as well as curriculum development and outreach activities, will shape project development efforts to maximize impact.\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": "2538", "attributes": { "award_id": "2015561", "title": "Variational Inference for Complex Networks", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "STATISTICS" ], "program_reference_codes": [], "program_officials": [ { "id": 7265, "first_name": "Yulia", "last_name": "Gel", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-07-01", "end_date": "2023-06-30", "award_amount": 150000, "principal_investigator": { "id": 7266, "first_name": "Yuguo", "last_name": "Chen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 281, "ror": "", "name": "University of Illinois at Urbana-Champaign", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 281, "ror": "", "name": "University of Illinois at Urbana-Champaign", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "Large-scale complex networks are becoming increasingly common in a variety of scientific disciplines, including social sciences, biological sciences, and physical sciences. Such complex networks challenge the computational limit of classical methods, making it infeasible to carry out statistical network inference within a reasonable amount of time. This project will develop efficient algorithms that are computationally feasible for large-scale complex networks and have provable statistical guarantees on performance. The proposed methods will be applied to social and biological network data, including brain networks, and will be used for the study of disorders associated with hearing loss, such as tinnitus. The proposed research is highly interdisciplinary and provides an opportunity for involvement of graduate and undergraduate students with a broad range of backgrounds and interests. The proposed methods will be incorporated into relevant courses. Research results will be disseminated to the scientific communities and all software developed in this research will be freely distributed as open-source to the public.\n\nThe project will develop variational methods for complex networks, including dynamic, multi-layer, and heterogeneous networks, and investigate theoretical properties of the variational methods on these networks to provide provable statistical guarantees on performance. The network models the PI studies include latent space models for dynamic networks and dynamic multi-layer networks, stochastic block models for multi-layer networks, various models for heterogeneous networks, and other models for complex networks. The proposed variational inference procedure makes it possible to handle large scale complex network data. The theoretical properties the PI will investigate include consistency of parameter estimation and community detection for variational methods. The proposed methods will be applied to real network data from social and natural sciences.\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": "2507", "attributes": { "award_id": "1954336", "title": "New Directions for Redox-Active Ligands: Ratiometric Sensors for H2O2 with 19F and 1H MRI Outputs and Functional Mimics of Superoxide Dismutase with Non-Enzymatic Metals", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "Chem Struct,Dynmcs&Mechansms B" ], "program_reference_codes": [], "program_officials": [ { "id": 7147, "first_name": "Tong", "last_name": "Ren", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-08-01", "end_date": "2023-07-31", "award_amount": 420000, "principal_investigator": { "id": 7149, "first_name": "Christian", "last_name": "Goldsmith", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 273, "ror": "https://ror.org/02v80fc35", "name": "Auburn University", "address": "", "city": "", "state": "AL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 273, "ror": "https://ror.org/02v80fc35", "name": "Auburn University", "address": "", "city": "", "state": "AL", "zip": "", "country": "United States", "approved": true }, "abstract": "The overproduction of reactive oxygen species (ROS) has been linked to a wide array of health conditions, including many cardiovascular, neurological, and inflammatory disorders. Currently, it is difficult to assess the concentrations of ROS in vivo. The lack of reliable imaging techniques makes it difficult to understand the roles of ROS in the human body. A pattern of oxidative stress may be used to distinguish disorders that give rise to similar clinically observable symptoms, and the ability to detect ROS overproduction in vivo could potentially diagnose these conditions more quickly and accurately. In this project funded by the Chemical Structure, Dynamics, and Mechanisms-B Program of the Chemistry Division, Dr. Christian R. Goldsmith of Auburn University is developing small molecule sensors for the ROS hydrogen peroxide (H2O2) that gives rise to two distinct magnetic resonance imaging (MRI) signals before and after their reaction with H2O2. By comparing the signals, one may be able to directly assess the concentration of H2O2 in a particular region of the body. Dr. Goldsmith is also interested in observing how antioxidants interact with ROS. Dr. Goldsmith is also engaged in outreach activities that heighten the involvement of undergraduate students in science, technology, engineering, and mathematics (STEM). These activities include giving research talks at local colleges and providing summer research internships in Dr. Goldsmith’s laboratory. These activities are designed to improve both undergraduate science education in the East Alabama area and the diversity of the future STEM workforce.\n\nDr. Christian R. Goldsmith is developing new transition metal complexes that can detect and degrade reactive oxygen species (ROS). The research produces redox-responsive contrast agents for magnetic resonance imaging (MRI) and functional mimics of superoxide dismutase (SOD) enzymes. The new MRI contrast agents are iron complexes with fluorinated redox-active quinol-containing ligands. In their reduced Fe(II)-quinol forms, these give rise to weak H-1 and strong F-19 MRI signals. After oxidation by H2O2, the Fe(III)-para-quinone products display weak F-19 MRI but strong H-1 signals, with the enhancement in H-1 MRI deriving from the increased paramagnetism and higher aquation of the metal center. The contrast agents are therefore bimodal ratiometric sensors for H2O2. The superoxide dismutase (SOD) mimics consist of quinol-containing ligands coordinated to redox-inactive transition metal ions, specifically Zn(II) and Ga(III). These complexes use the quinol/para-quinone redox couple to alternatively reduce and oxidize superoxide and bypass the need for a potentially harmful redox-active transition metal ion. New quinol-containing ligands increase the catalytic activity by enabling superoxide to more readily access the metal center. Given the involvement of ROS in disease, these complexes may lead to improved diagnostic options for several health conditions. The project’s reliance on inorganic chemistry, organic chemistry, and biochemistry teach undergraduate and graduate students a broad array of skills. Dr. Goldsmith’s laboratory are also presenting research seminars at primarily undergraduate institutions in the East Alabama area and enable their students to participate in cutting-edge scientific research by providing two summer internships per year of the project.\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": "10483", "attributes": { "award_id": "2134789", "title": "2022 GRC / GRS on Colloidal, Macromolecular, and Polyelectrolyte Solutions: Sub-title: “Connecting theory and simulations to experiments and applications.”", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "PMP-Particul&MultiphaseProcess" ], "program_reference_codes": [], "program_officials": [ { "id": 1490, "first_name": "William", "last_name": "Olbricht", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-11-15", "end_date": "2022-10-31", "award_amount": 30000, "principal_investigator": { "id": 11768, "first_name": "Ronald", "last_name": "Larson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "This award will provide partial support for the 2022 Gordon Research Conference (GRC) on Colloidal, Macromolecular, and Polyelectrolyte Solutions: Connecting Theory and Simulations to Experiments and Applications, which will be held February 6-11, 2022 in Ventura, CA. The conference will be preceded by a Gordon Research Seminar (GRS) for graduate students. Together, the two events will provide opportunities for researchers, especially young investigators and students, to present results of their research, meet senior experts in the field, and discuss emerging research trends in colloidal and polymeric solutions. These materials are important in a variety of technology areas including coatings, paints, personal-care products and cosmetics, and food processing. The goal of the GRC and GRS is to bring promote discussions that will enable comparisons between experiments, numerical simulations, and theory for these important materials.\n\nColloidal and polymer science, including polyelectrolytes, is growing in importance in a wide range of applications, especially those involving biotechnology. The development of RNA vaccines was enabled in part by creating nanoparticle complexes of DNA, a polyelectrolyte, with oppositely charged surfactants. Synthetic structures that mimic cells, such as membraneless organelles, are formed by segregating charged proteins that exhibit polyelectrolyte phase behavior. Increasing computing power, new computational methods, and high resolution experiments now allow comparisons between experiment and simulation at length and time scales that are accessible to both. This is the theme of the GRC/GRS. Session topics will include polyelectrolytes and ionic liquids, confined colloids, directed assembly, propelled colloids, interfacial systems, polymers and biology, polymer glasses, and driven elastomers. The GRS for graduate students will include technical sessions as well as career development sessions for students and young investigators.\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": "2582", "attributes": { "award_id": "2037874", "title": "I-Corps: Cell Culture Platform Using Engineered Micropatterns to Control Differentiation", "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": 7458, "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": "2020-08-01", "end_date": "2023-01-31", "award_amount": 50000, "principal_investigator": { "id": 7459, "first_name": "Scott", "last_name": "Wood", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 580, "ror": "https://ror.org/00ch7yk27", "name": "South Dakota School of Mines and Technology", "address": "", "city": "", "state": "SD", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 580, "ror": "https://ror.org/00ch7yk27", "name": "South Dakota School of Mines and Technology", "address": "", "city": "", "state": "SD", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this I-Corps project is the development of an in vitro, articular cartilage model for osteoarthritis (OA). This model is designed to increase the likelihood of successful clinical translation of research on the causes of OA into potential treatments. OA often occurs with age or injury and affects over 32.5 million US adults. There are currently no known disease-modifying treatments to stop or reverse the progression of OA – all current treatments are limited to either various methods of pain management or surgical tissue replacement. The proposed technology will advance the translation of OA research by facilitating studies of chondrocytes, the primary cells that cause OA, using traditional and state-of-the-art genomic, proteomic, and imaging techniques. It is expected that the proposed technology will bridge the gap between the 2D and 3D cell culture markets, represented by an annual market of ~$1 billion in the US. Due to the prevalence and crippling nature of OA, joint replacements represent a $19 billion industry annually in the US. In addition to its role in OA treatments, the model may clinical implications in improving outcomes for autologous chondrocyte transplantation, increasing its commercial impact.\n\nThis I-Corps project is based on the development of a cell culture platform that improves control over the differentiation of chondrocytes. This control is enabled through the regulation of cell shape via a novel combination of nanotechnology, micropatterning, and mechanically-tunable, thin-film composite materials. Chondrocytes rapidly transform into non-physiological cell types in standard 2D culture systems. More advanced 3D culture systems prevent this problem but introduce difficulties in compatibility with analytical techniques. The proposed technology may act as an egg crate for individual cells, nesting each one in an environment that allows it to maintain its physiological nature without restricting their ability to be studied. The technology may maintain the physiological cell shape of chondrocytes for at least 28 days, four times as long as competing micropatterned technologies. The technology has potential applications in drug development, gene therapy, stem cell medicine, tissue engineering, the elucidation of molecular pathogeneses, and other biomedical applications.\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": 1, "pages": 1424, "count": 14236 } } }