Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1419&sort=-id
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=-id", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=-id", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1420&sort=-id", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1418&sort=-id" }, "data": [ { "type": "Grant", "id": "383", "attributes": { "award_id": "2145277", "title": "CAREER: Re-Thinking the Perception-Action Paradigm for Agile Autonomous Robots", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 718, "first_name": "Donald", "last_name": "Wunsch", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-04-15", "end_date": "2027-03-31", "award_amount": 500000, "principal_investigator": { "id": 719, "first_name": "Giuseppe", "last_name": "Loianno", "orcid": null, "emails": "[email protected]", "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": [], "awardee_organization": { "id": 167, "ror": "https://ror.org/0190ak572", "name": "New York University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Autonomous robots will become pervasive in our society and will solve complex tasks, actively collaborating with each other and with humans. As the recent COVID-19 outbreak has highlighted, autonomous robots can solve a range of time-sensitive problems including logistics, reconnaissance, and disinfection of critical areas. Beyond pandemic, small-scale robots can help humans in complex or dangerous tasks such as search and rescue, security, and surveillance, and, thanks to their lighter weight, they pose only a modest risk to human safety. These time-sensitive tasks require robots to make fast decisions and agile maneuvers in complex and dynamic environments. State-of-the-art autonomous navigation approaches, while mature, are slow and brittle and prevent robust and resilient agile navigation. This Faculty Early Career Development (CAREER) Program studies the fundamental perception-action problem for agile navigation of autonomous robots in complex environments by planning a novel, low-latency, robust, adaptive, safe, and resilient paradigm. This project aims also to educate students on the technical aspects, societal benefits, and ethical use of autonomous systems by establishing a unique multi-disciplinary, and inclusive research and educational platform which includes a core curriculum on robot localization and navigation, and a series of online racing hackathons for a post-pandemic customized and inclusive research and educational experience. These will contribute to lowering the barrier to participation in research and education for students, particularly underrepresented minorities.This project will generate a new foundational theory, which includes models and algorithms resulting from a principled combination of perception, learning, and control to holistically design visual perception and action to create small-scale agile autonomous robots. The goal is to capture the strict cross–coupling effects between perception and action to jointly and concurrently resolve the perception-action problem to speed up the robots’ decision making process and increase their agility. The project is organized in three thrusts according to a series of objectives, culminating in innovations in robotics autonomy research and education. A compressed and unified representation of the perception and action spaces guarantees to reduce the robot's inference latency and naturally reveals the cross-coupling effects among them. Next, the robot will exploit using this representation its action-predictive information to enhance its inference capabilities and will employ an optimal control/planning approach to maximize its perception accuracy and quality.This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).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": "382", "attributes": { "award_id": "2136709", "title": "SBIR Phase I: A Portable Oxygen Concentrator with High Flow Rates for In-home Therapy (COVID-19)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)" ], "program_reference_codes": [], "program_officials": [ { "id": 716, "first_name": "Edward", "last_name": "Chinchoy", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-04-15", "end_date": "2023-03-31", "award_amount": 256000, "principal_investigator": { "id": 717, "first_name": "Jun", "last_name": "Kamata", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 193, "ror": "", "name": "AIROMATIX INC.", "address": "", "city": "", "state": "OR", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 193, "ror": "", "name": "AIROMATIX INC.", "address": "", "city": "", "state": "OR", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable easy oxygen delivery to patients with respiratory conditions. Currently, patients requiring high flow-rates of oxygen above 4 L/min require oxygen tanks that are large, heavy and can be hazardous, limiting mobility and transportation options. The proposed system produces breathable oxygen at higher flow rates and lower energy compared to current portable oxygen concentrators, enabling sustained patient use. This enables sustained oxygen production in a portable manner to manage medical conditions causing oxygen deprivation, including Chronic Obstructive Pulmonary Disease (COPD) and Coronavirus Disease (COVID-19). This Small Business Innovation Research (SBIR) Phase I project will develop a portable system that utilizes a novel photocatalytic (light activated) reaction to separate oxygen from ambient air, trapped in a chemical solution, then released as needed through a temperature-controlled reaction. This project will monitor the capture and release reactions using absorption spectroscopy to determine the ideal conditions of oxygen production. Several photosensitizer chemical compounds (fullerene C70 and C60, rubrene, and methylene blue with urea) will be evaluated on system longevity by continuously cycling the systems under higher temperatures and light exposure, and monitoring their effects on oxygen production. A prototype will then be developed that generates targeted oxygen flow rates at the desired rate of energy consumption, and the oxygen produced validated as safe for inhalation using bench tests.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": "381", "attributes": { "award_id": "2224644", "title": "Conference: Student and Junior Faculty Support for the International Symposium on Sustainable Systems and Technology (ISSST) 2022", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)" ], "program_reference_codes": [], "program_officials": [ { "id": 714, "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": "2022-06-01", "end_date": "2023-05-31", "award_amount": 18000, "principal_investigator": { "id": 715, "first_name": "Lu", "last_name": "Liu", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 192, "ror": "https://ror.org/04rswrd78", "name": "Iowa State University", "address": "", "city": "", "state": "IA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 192, "ror": "https://ror.org/04rswrd78", "name": "Iowa State University", "address": "", "city": "", "state": "IA", "zip": "", "country": "United States", "approved": true }, "abstract": "2224644 (Lu). The International Symposium on Sustainable Systems and Technology (ISSST) conference will engage participants from multiple disciplines to focus on sustainability and engineering challenges. This conference, to be held June 21-23, 2022 in Pittsburgh, PA, will address a spectrum of issues for assessing and managing products and services across their life cycle, as well as the design, management, and policy implications of sustainably engineered systems and technologies. ISSST 2022 will highlight five themes: (1) Integrated human-physical systems – how to integrate human dimensions into sustainability design and implementations; (2) Infrastructure sustainability and resiliency – quantitative assessment of the sustainability and resiliency of the built environment; (3) Advances in sustainability assessment methods – the development of new sustainability assessment methods, including data science and analytics, machine learning, multi-objective analyses, and other methods for emerging systems and technologies; (4) Sustainability education – pedagogical approaches to teaching sustainability at different levels and lessons learned in designing sustainability curriculum; and (5) Other creative sustainability-related topics – new methods and ideas that demonstrate unique partnerships, big ideas, perspectives from non-STEM (science, technology, engineering, math) disciplines. The conference will also host special sessions to bring participants together in educational sessions, workshops, communications, and professional skills development. The conference is designed for significant participation from students and young faculty members, as this is critical for developing the next generation of sustainable solutions. This grant will help to expand the participation of students, underrepresented groups, and junior faculty from across the United States in ISSST 2022. Social equity, differential access and impacts, and environmental justice will be prominent across all of the five themes of the 2022 conference. Several sessions are also expected to address the implications of the COVID-19 pandemic on production and consumption, pollution, and critical infrastructure systems. A diverse group of members will share their work in sustainability science and engineering through paper and poster presentations, as well as formal and informal discussions. The conference will also feature a variety of plenary/keynote speakers, including Dr. Aurora Sharrad, Director of Sustainability, from University of Pittsburgh and Dr. Ranran Wang from Leiden University, Netherlands. All of this will provide participants a venue for discussing visions, educational approaches, challenges, as well as provide educators and students opportunities to gain insight on research on sustainability in a holistic manner.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": "380", "attributes": { "award_id": "2148271", "title": "RINGS: Resilient mmWave Networks via Distributed In-Surface Computing (mmRISC)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 710, "first_name": "Murat", "last_name": "Torlak", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-05-01", "end_date": "2025-04-30", "award_amount": 365202, "principal_investigator": { "id": 713, "first_name": "Kaushik", "last_name": "Sengupta", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 191, "ror": "https://ror.org/00hx57361", "name": "Princeton University", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 711, "first_name": "Kyle A", "last_name": "Jamieson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 191, "ror": "https://ror.org/00hx57361", "name": "Princeton University", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true } ] }, { "id": 712, "first_name": "Yasaman", "last_name": "Ghasempour", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 191, "ror": "https://ror.org/00hx57361", "name": "Princeton University", "address": "", "city": "", "state": "NJ", "zip": "", "country": "United States", "approved": true }, "abstract": "Wireless networks are undergoing a radical transformation with the aim to provide the critical information infrastructure for the 21st century and foster new economic opportunities, innovation and many emerging applications. To facilitate this, there is a focus on new spectrum in the millimeter-wave frequency range that has the ability to support ultra-high data rates with low latency needed for applications in automation, robotics and cyber-physical systems, smart health, and autonomous vehicles and systems. The spectrum can also support wireless backhaul links to bridge the last mile connectivity, and provide broadband wireless access---the importance of which is clearly highlighted during the Covid-19 pandemic. However, these connectivity links are prone to physical channel disruptions including blockages and channel propagation variations, and therefore not resilient. The proposal involves a multi-disciplinary approach across three different research groups towards addressing these problems and ensuring resilience and scalability in such networks. The proposed concept of smart reflecting surfaces aims to enable dynamic and on-demand control of wireless channels to create favorable transmission allowing robust wireless connectivity in mobile mmWave WLANs. The success of this project can enable the next-generation, ubiquitous, and low-cost mmWave wireless access, including flexible deployment of wireless backhauls addressing the last-mile connectivity, satellite communication, and intelligent wireless sensing systems for smart cities and cyber-physical systems. The project will address the need for developing US-centric capabilities in semiconductors and wireless technology, through training of students across the undergraduate and the PhD program in a rigorous multi-disciplinary research effort. This project, mmRISC, builds Resilient mmWave Networks via Distributed In-Surface Computing. We investigate mmWave, multi-band hybrid surfaces with embedded custom-silicon ICs that provide on-surface signal amplification and computing abilities for multi-user localization, tracking and ambient sensing. Our proposed surfaces enable resilient and reconfigurable distributed networks that maintain low latency, energy and spectral efficiency. We pursue a holistic, cross-system research approach focusing on scalable, spectrally-agile, low-power, and low-cost hybrid surfaces operable across multiple mmWave bands with controlled amplification. We will also focus on embedded computing for on-surface sensing, and resilient network architectures supporting such smart surfaces allowing capacity optimization. Through cross-layer design approaches, our proposed work will inform the architecture of NextG surface-assisted wireless networks for the future.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": "379", "attributes": { "award_id": "2151871", "title": "Collaborative Research: A New Multiscale Framework for Integrating Socio-Economic Processes, Vector-Borne Disease Control, and the Impact of Transient Events", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [], "program_officials": [ { "id": 708, "first_name": "Henry", "last_name": "Warchall", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-07-01", "end_date": "2025-06-30", "award_amount": 99407, "principal_investigator": { "id": 709, "first_name": "Olivia", "last_name": "Prosper", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 190, "ror": "", "name": "University of Tennessee Knoxville", "address": "", "city": "", "state": "TN", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 190, "ror": "", "name": "University of Tennessee Knoxville", "address": "", "city": "", "state": "TN", "zip": "", "country": "United States", "approved": true }, "abstract": "Mathematical models for infectious diseases are critical tools for informing effective disease interventions. The disease management strategies informed by models of vector-borne diseases (such as diseases spread by mosquitoes) led to the elimination of malaria from the United States and other countries. However, malaria continues to have an enormous impact on resource-challenged regions of the world, while other existing and emerging vector-borne diseases such as West Nile Virus, Dengue Virus, and Zika Virus continue to impact both advanced and resource-challenged economies. A shortcoming of many existing modeling approaches is the absence of an explicit connection between economic factors and disease transmission – two factors that influence each other. In an increasingly connected and complex world, accounting for the synergistic effects of these factors is essential for effective disease control. For example, the COVID-19 pandemic caused sudden economic shifts that affected the progress of malaria control programs, resulting in increases in malaria-related deaths. In collaboration with an ecologist/economist and with an entomologist and a biostatistician from Africa, the investigators will build mathematical tools to bridge this gap, which will be used to inform public health and economic growth policies. The project will train graduate students through involvement in the research. Workshops on feedback between economic and disease systems will train a new generation of undergraduate students from diverse backgrounds on this important topic. This work will also involve students from Africa, a continent that is highly affected by vector-borne diseases. Incorporating socio-economic factors into vector-borne disease (VBD) systems is key to identifying new interventions, by unraveling the intertwined relationship between VBD, socio-economic conditions, and transient events. The investigators aim to develop a new mechanistic framework for transient disease dynamics that accounts for feedback between VBDs and economic systems, the impact of fast-slow time scales, and sudden endogenous and exogenous events that shift the economic landscape. Factors including heterogeneous mosquito-biting and insecticide-treated-net (ITN) replacement times, demographic structure, and human behavior in relation to ITN use will be included. For even the simplest economic-VBD model, standard methods for computing basic epidemiological metrics and performing structural identifiability analysis break down. Hence, the investigators also plan to build the mathematical toolbox required to analyze and simulate these coupled systems. Although the framework will be applied to malaria as a prototype VBD using socio-economic and epidemiological data from Kenya, Madagascar, and West Africa to calibrate the parameters and validate the outcomes of the models, it is intended to be robust enough to be applicable to other VBDs. Furthermore, the framework will allow the investigators to realistically answer important public health and economic growth questions, including how to distribute ITNs across connected populations, and how to respond to spontaneous events affecting the economic landscape.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": "378", "attributes": { "award_id": "2210137", "title": "EAGER: DCL: SaTC: Enabling Interdisciplinary Collaboration: Combatting Disinformation and Racial Bias: A Deep-Learning-Assisted Investigation of Temporal Dynamics of Disinformation", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)" ], "program_reference_codes": [], "program_officials": [ { "id": 704, "first_name": "Daniela", "last_name": "Oliveira", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-06-01", "end_date": "2024-05-31", "award_amount": 300000, "principal_investigator": { "id": 707, "first_name": "Kookjin", "last_name": "Lee", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 705, "first_name": "Kyounghee", "last_name": "Kwon", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, { "id": 706, "first_name": "Doowon", "last_name": "Kim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "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 project explores the diffusion of racial disinformation online and its social impacts, particularly focusing on Asian Americans. While the hatred and bias against Asian Americans have become notable amid the COVID-19 pandemic, Asian-targeting disinformation has yet been fully explored. The project's novelties are in unique multidisciplinary approaches to (1) detect Asian-targeting disinformation and its countermeasure messages, and understand how they are spread on the web, (2) examine how the spread of disinformation and countermeasure messages on the web is associated with the intensity of the bias and hate crimes against Asian Americans, and (3) develop various data-driven computational models to help understanding the disinformation dynamics. The project's broader significance and importance are to inform civil society, including advocacy organizations and the general public, about how to strategize communication efforts in battling racial disinformation, and to make the developed tools and outcomes publicly available for broader uses.The project takes three-staged approaches. The main objective of the first phase is to develop computational tools for the detection and analysis of the temporal dynamics between Asian-targeted disinformation and countermeasures on the Web. A specific focus is on developing automated identification tools and deep-learning classification models by feature-engineering unique characteristics of disinformation. The objective of the second phase is to understand to what extent the spread of disinformation and countermeasures online is associated with the societal trend of implicit bias and hate crime occurrences against Asian Americans in the real-world, which can be achieved via developing deep-learning causality models. The objective of the third phase is to design scalable data-driven deep-learning models of disinformation dynamics in macro and micro levels, identifying unknown dynamics from the real-world measurements, which also enables simulations of the learned dynamics.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": "377", "attributes": { "award_id": "2146969", "title": "Disability Culture and Technology", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)" ], "program_reference_codes": [], "program_officials": [ { "id": 702, "first_name": "Wenda K.", "last_name": "Bauchspies", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-05-01", "end_date": "2023-04-30", "award_amount": 274144, "principal_investigator": { "id": 703, "first_name": "Mozhdeh A", "last_name": "Hamraie", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 189, "ror": "https://ror.org/02vm5rt34", "name": "Vanderbilt University", "address": "", "city": "", "state": "TN", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 189, "ror": "https://ror.org/02vm5rt34", "name": "Vanderbilt University", "address": "", "city": "", "state": "TN", "zip": "", "country": "United States", "approved": true }, "abstract": "Many disability communities have developed remote techniques for participating in work and social life. These innovative techniques are part of disability culture and community. Many people believe that technologies merely help disabled people do the things that nondisabled people do. However, disabled people also design their own technologies in order to challenge what is considered normal. “Disability Culture and Technology” aims to address the social inequalities that disabled people face by documenting the role of technology in disability communities. The data resulting from this study will be made free and available to the public. Publications resulting from this data will also enable policymakers, employers, and decision-makers to make more informed choices regarding remote participation. This will make employment and education opportunities more equitable and diverse. Society will also benefit from a better understanding of disabled peoples’ contributions and knowledge.“Disability Culture and Technology” will ask how disabled people use and transform remote access technologies to shape society, both during and before the COVID-19 pandemic. This NSF Scholars Award gathers oral histories, images, videos, and other forms of documentation to build an archive of the ways that disabled people use remote access to form community. This archive will enable researchers to study how disabled people shape technology in order to survive the pandemic, and more broadly, to change society. It will inform how science and technology studies scholars understand issues such as who designs, uses, and transforms technology. The research and resulting publications will also inform how disability studies scholars understand the role of technology in connecting disabled people across long distances and forming communities.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": "376", "attributes": { "award_id": "2151872", "title": "Collaborative Research: A New Multiscale Framework for Integrating Socio-Economic Processes, Vector-Borne Disease Control, and the Impact of Transient Events", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)" ], "program_reference_codes": [], "program_officials": [ { "id": 700, "first_name": "Henry", "last_name": "Warchall", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-07-01", "end_date": "2025-06-30", "award_amount": 99986, "principal_investigator": { "id": 701, "first_name": "Ruijun", "last_name": "Zhao", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 188, "ror": "https://ror.org/04att9732", "name": "Minnesota State University, Mankato", "address": "", "city": "", "state": "MN", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 188, "ror": "https://ror.org/04att9732", "name": "Minnesota State University, Mankato", "address": "", "city": "", "state": "MN", "zip": "", "country": "United States", "approved": true }, "abstract": "Mathematical models for infectious diseases are critical tools for informing effective disease interventions. The disease management strategies informed by models of vector-borne diseases (such as diseases spread by mosquitoes) led to the elimination of malaria from the United States and other countries. However, malaria continues to have an enormous impact on resource-challenged regions of the world, while other existing and emerging vector-borne diseases such as West Nile Virus, Dengue Virus, and Zika Virus continue to impact both advanced and resource-challenged economies. A shortcoming of many existing modeling approaches is the absence of an explicit connection between economic factors and disease transmission – two factors that influence each other. In an increasingly connected and complex world, accounting for the synergistic effects of these factors is essential for effective disease control. For example, the COVID-19 pandemic caused sudden economic shifts that affected the progress of malaria control programs, resulting in increases in malaria-related deaths. In collaboration with an ecologist/economist and with an entomologist and a biostatistician from Africa, the investigators will build mathematical tools to bridge this gap, which will be used to inform public health and economic growth policies. The project will train graduate students through involvement in the research. Workshops on feedback between economic and disease systems will train a new generation of undergraduate students from diverse backgrounds on this important topic. This work will also involve students from Africa, a continent that is highly affected by vector-borne diseases. Incorporating socio-economic factors into vector-borne disease (VBD) systems is key to identifying new interventions, by unraveling the intertwined relationship between VBD, socio-economic conditions, and transient events. The investigators aim to develop a new mechanistic framework for transient disease dynamics that accounts for feedback between VBDs and economic systems, the impact of fast-slow time scales, and sudden endogenous and exogenous events that shift the economic landscape. Factors including heterogeneous mosquito-biting and insecticide-treated-net (ITN) replacement times, demographic structure, and human behavior in relation to ITN use will be included. For even the simplest economic-VBD model, standard methods for computing basic epidemiological metrics and performing structural identifiability analysis break down. Hence, the investigators also plan to build the mathematical toolbox required to analyze and simulate these coupled systems. Although the framework will be applied to malaria as a prototype VBD using socio-economic and epidemiological data from Kenya, Madagascar, and West Africa to calibrate the parameters and validate the outcomes of the models, it is intended to be robust enough to be applicable to other VBDs. Furthermore, the framework will allow the investigators to realistically answer important public health and economic growth questions, including how to distribute ITNs across connected populations, and how to respond to spontaneous events affecting the economic landscape.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": "375", "attributes": { "award_id": "2200883", "title": "A Systematic Review and Meta-Analysis on the Effectiveness of Remote Education in Math and Science", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)" ], "program_reference_codes": [], "program_officials": [ { "id": 697, "first_name": "Joan", "last_name": "Walker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-10-01", "end_date": "2025-09-30", "award_amount": 599996, "principal_investigator": { "id": 699, "first_name": "Sarah", "last_name": "Sahni", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 187, "ror": "", "name": "American Institutes for Research in the Behavioral Sciences", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 698, "first_name": "Laura", "last_name": "Michaelson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 187, "ror": "", "name": "American Institutes for Research in the Behavioral Sciences", "address": "", "city": "", "state": "VA", "zip": "", "country": "United States", "approved": true }, "abstract": "Web-based and digital tools to support math and science learning have emerged as a major trend over the past several decades. As of 2013, all 50 states and the District of Columbia offer online learning experiences to K–12 students, ranging from supplemental courses that accompany traditional in-person instruction to full-time online schools. Understanding the promise and limitations of remote learning is an urgent line of research now because of increased reliance on remote instruction during the COVID-19 pandemic. The pandemic and continued disruptions to schooling have been associated with substantial setbacks in learning. Studies examining academic progress between March 2020 and March 2021 reported significant lack of progress, which was particularly pronounced in math and science relative to reading. Furthermore, lack of progress was greatest among subgroups that already experience achievement disparities in math and science, such as students of color, rural students, and those eligible for free or reduced-price lunch.This comprehensive systematic review and meta-analysis synthesizes evidence surrounding math and science remote education programs from the past 15 years. The goal is to understand the effectiveness of math and science remote education programs; how their effectiveness varies by program characteristics (e.g., fully online vs. hybrid, synchronous vs. asynchronous, and student-instructor ratio); and whether their effects vary with student sample characteristics. To prioritize future research needs, the researchers will create evidence gap maps to illuminate patterns in the existing evidence base and identify areas in which evidence is lacking. This analysis will build foundational knowledge and inform educators about which programs and strategies in math and science remote education have been most effective. In addition, the review will provide targeted guidance on which programs and strategies have been most appropriate for vulnerable groups of students.The Discovery Research K-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools (RMTs). Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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": "374", "attributes": { "award_id": "2202180", "title": "Building Efficiency for a sustainable Tomorrow (BEST) Center", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)" ], "program_reference_codes": [], "program_officials": [ { "id": 692, "first_name": "Virginia", "last_name": "Carter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-10-01", "end_date": "2025-09-30", "award_amount": 1650000, "principal_investigator": { "id": 696, "first_name": "Peter L", "last_name": "Crabtree", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 176, "ror": "", "name": "University of California-Berkeley", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 693, "first_name": "Mary Ann", "last_name": "Piette", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 694, "first_name": "Theodore", "last_name": "Wilinski", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 695, "first_name": "Robert", "last_name": "Nirenberg", "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": "Commercial buildings are a predominant feature of U.S. cities. Such buildings form the physical infra-structure for people working in many economic sectors. The technicians who operate these buildings are largely invisible to building occupants, occasionally seen responding to a complaint about room temperature or repairing equipment. Climate change, the COVID-19 pandemic, and new digital technologies are creating a new dynamic for the work of building technicians, increasing the importance of their role, expanding the knowledge and skills required of them, and raising expectations about the quality of their work. Today’s building technicians must be prepared to manage the complex building automation, data analytics, and energy management systems of the high-performance “sustainable” buildings of the future. This project will support the BEST Center transitioning to a Resource Center to continue to serve the community for the collection, dissemination, and adoption of programs, courses, lab applications, and innovative instructional methods for the advanced technological education of building systems technicians. The BEST Resource Center will support the development of building technician education programs at community and technical colleges nationwide, engage industry to support this effort, and strengthen the national STEM pipeline. The Center will have 3 goals: 1) Transform the instructional capacity of community colleges in the field of building technician education, with an emphasis on High Performance Building Operations Technical-Professional (HPBOT-P) and Building Automation Specialist (BAS) curriculum alignment and certification; 2) Engage industry stakeholders and research partners in a national collaboration with community colleges to support high-quality building science instructional programs; and 3) Strengthen the national STEM pipeline for building technicians through outreach to high school students, women, and populations traditionally underrepresented in building science. This project is funded by the Advanced Technological Education program that focuses on the education of technicians for the advanced-technology fields that drive the Nation's economy.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": 1419, "pages": 1424, "count": 14236 } } }