Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1405&sort=-keywords
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Older people, especially those with a disability, often have difficulty maneuvering and need assistance even for minor chores such as handing over the TV remote, fetching water bottles, and other items such as medicines. This need for assistance has become even clearer from the COVID-19 outbreak, requiring collaborative robots with object handover skills to keep the affected person and their caretakers at a safe distance. Similarly, such robot abilities in factories can significantly improve work efficiency by handing over various tools to and from their collaborating workers. However, despite the significance of having robots with object handover skills, such a fundamental task remains unsolved. This proposal presents a framework to solve the human-robot handover tasks with arbitrary daily-life objects in uncontrolled environments and explicitly considers the most-used items by patients with motor impairments such as Amyotrophic Lateral Sclerosis.\n\nThe technical contributions of this proposal are divided into three research thrusts. First, a novel task-aware, 3D pose forecasting approach will be introduced to predict future poses of the full human body and their handheld objects from raw sensory information. During inference, various human body parts that are crucial for robot decision-making and control in solving human-robot object handover tasks will also be highlighted through learning-based attention models. Second, the proposal will formalize, represent, and learn the task-specific physical human-object and object-object interactions to predict socially feasible target object poses for handovers concerning the expected human behaviors and robot’s kinematic reachability during manipulation. Third, the predicted human behaviors and desired object handover poses will be used to determine human-friendly robot grasp and generate informed human-aware robot motion sequences. Finally, the proposed research thrusts will be integrated into a unified framework to solve human-to-robot and robot-to-human handover tasks with arbitrarily unknown objects from raw visual observations. The proposal’s outcomes will also exhibit new, proof-of-concept, human-robot handover demonstrations in the real-world using various most-used items by people with motor impairments.\n\nThis 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).\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": "10065", "attributes": { "award_id": "2226312", "title": "Cross-Cutting Improvements: The Development of a Geospatial Big-Data Infrastructure Supporting Socially and Environmentally Relevant Spatial Decision-Making and Analysis", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "NSF Public Access Initiative" ], "program_reference_codes": [], "program_officials": [ { "id": 874, "first_name": "Martin", "last_name": "Halbert", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-01-01", "end_date": "2025-12-31", "award_amount": 1135805, "principal_investigator": { "id": 11522, "first_name": "Timothy", "last_name": "Mulrooney", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 25943, "first_name": "Christopher", "last_name": "McGinn", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1074, "ror": "https://ror.org/051r3tx83", "name": "North Carolina Central University", "address": "", "city": "", "state": "NC", "zip": "", "country": "United States", "approved": true }, "abstract": "This research coordination network will foster GIS (geographic information systems) and open data science support for faculty and student researchers in a regional cluster of HBCU (Historically Black Colleges and Universities), MSI (minority serving institutions), and local communities. The project will be led by a team of researchers across multiple departments in the newly formed College of Health and Science (CHAS) at North Carolina Central University together with three other minority serving institutions in the region. This research coordination network will serve both the regional and larger scientific communities by advancing open science practices and principles in the development and deployment of data infrastructure and services needed to support the use of geospatial data in socially and environmentally relevant research activities.\n\nGeospatial data analysis has been proven to advance the understanding of social determinants of health affecting COVID-19 incidence rates, as well as a wide variety of other socially and environmentally relevant research issues. This project will coordinate the creation of a large number of new GIS data layers and make them available to the larger multidisciplinary research community in accordance with FAIR data sharing principles together with rich, standards-based and machine-readable metadata. Georeferenced data from disparate sources and disciplines will be enriched and normalized by standardized descriptive information based on a metadata schema, driven by the community of experts and intended end-users and compatible with international and federally mandated ISO 19115 standard and utilizing metadata profiles developed and used by state and local governments.\n\nThis award by the Office of Advanced Cyberinfrastructure is jointly supported by the Directorate for Education and Human Resources and the HBCU Excellence in Research Program.\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": "10066", "attributes": { "award_id": "2241057", "title": "Collaborative Research: CIF: Small: A New Paradigm for Distributed Information Processing, Simulation and Inference in Networks: The Promise of Law of Small Numbers", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Comm & Information Foundations" ], "program_reference_codes": [], "program_officials": [ { "id": 1867, "first_name": "Phillip", "last_name": "Regalia", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-01", "end_date": "2024-11-30", "award_amount": 249962, "principal_investigator": { "id": 25944, "first_name": "Farhad", "last_name": "Shirani Chaharsooghi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 207, "ror": "https://ror.org/02gz6gg07", "name": "Florida International University", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "The ability to access, process, and store distributed data in a reliable, efficient, and secure manner has become indispensable in everyday lives. A variety of emerging applications such as augmented reality, autonomous vehicles, and cloud computing heavily rely on handling large amounts of distributed information. The pandemic has further accentuated the global need for technologies that enable communication, collaboration, education and scientific discourse whilst maintaining physical distance, and this has increased awareness of the critical nature of the communication network infrastructure. The exponentially increasing demands for faster data processing and higher communication rates pose new challenges. This project addresses these challenges by developing novel approaches and techniques for distributed information processing, randomness generation, data storage and transmission, and inference. The project will tightly integrate research with a significant education and outreach program consisting of two focus areas: (i) Training students in interdisciplinary research, and (ii) Broadly disseminating research outcomes in the forms of new curricular development and student involvement. A concerted effort will be made to broaden the participation of women and under-represented minority students in the project. \n\nThe project is based on two research thrusts that are expected to provide a deeper understanding of the fundamental laws that govern the processing of information. In the first thrust, a new framework is developed based on two conceptual innovations: (i) A characterization of the fundamental memory structure of information processing functions using a novel notion of dependency spectrum, and (ii) Development of a new law of small numbers, which describes a fundamental interplay between the dependency spectrum and distributed cooperation. In particular, the project uncovers a trade-off between the correlation-preserving ability of distributed information-processing functions --- which is necessary for distributed cooperation --- and their ability to efficiently perform individual information-processing tasks. The second thrust addresses two application scenarios. (i) Building upon the concept of dependency spectrum, novel techniques are developed for distributed data compression, and transmission of information in interference and broadcast networks. (ii) The fundamental limits and practical design of distributed randomness generation algorithms are derived. These innovations lead to significant improvements over the state of the art both in terms of characterizations of asymptotic performance limits and constructive practical algorithms.\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": "10067", "attributes": { "award_id": "2155072", "title": "Using Computational Modeling to Transform Assessments of Creativity in Engineering Design", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)", "ECR-EHR Core Research" ], "program_reference_codes": [], "program_officials": [ { "id": 3698, "first_name": "Bonnie", "last_name": "Green", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-15", "end_date": "2025-08-31", "award_amount": 318879, "principal_investigator": { "id": 25945, "first_name": "Mark", "last_name": "Fuge", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "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 collaborative project from research teams at Pennsylvania State University, University of Maryland, and Washington and Lee University focuses on measuring creativity in undergraduate engineering education. The ability to think creatively is essential for success in STEM fields, particularly engineering, which requires designing solutions to complex problems that often have no single or \"correct\" solution. The Next Generation Science Standards identify creative thinking skills, such as problem solving and flexibility, as core competencies for modern STEM education. Yet educators are not currently equipped with adequate tools to assess creativity in their classrooms. To effectively prepare the STEM workforce, there is a critical need for assessment tools that educators and researchers can use to identify what works in STEM education to foster creativity. Current creativity tests present significant challenges for STEM educators, including (in-person) paper administration and, perhaps most problematically, manual scoring that requires teachers to count and code thousands of responses—a labor-intensive and often costly process, particularly for under-resourced schools. In light of the increasingly diverse student population, the availability of creativity tests that measure student ability fairly and consistently, regardless of race or ethnicity, is even more critical for equity of opportunity in STEM education. This project seeks to create an online platform for measuring creativity in engineering design that educators can use to cater to the needs of all their students. The tool will allow educators to administer a range of engineering creativity tasks and automatically calculate creativity scores. This project fits the intent of the ECR program to facilitate \"the development, refinement, and testing of new education research, measurement, and evaluation methodologies.\" It addresses the ECR research track, \"Research on STEM Learning and Learning Environments,\" and has additional impacts for \"Research on Broadening Participation in STEM Fields\" by designing inclusive and culturally and linguistically diverse assessment tools targeted to students who remain underrepresented in the pursuit of STEM courses of study and English as second language speakers.\n\nTwo aims guide this project. First is to build an online platform for large-scale engineering design assessment — validating all platform tasks with undergraduate engineering students — to allow teachers and researchers to easily assess creativity, automatically compute creativity metrics, and generate customizable student reports. Second is to apply the platform in an undergraduate design course at Penn State that includes a 3-week Creativity Module (with lessons and exercises on creativity in engineering design) to obtain valuable platform usability data from both instructors and students, while evaluating a promising undergraduate course intended to promote creativity in engineering design. The team will apply recent advances in computational modeling and machine learning — including active learning of design sketches and distributional semantic modeling of text-based responses to creative problem solving tasks. It is expected that this approach will streamline educational assessment of creativity, resulting in a user-friendly technology to assist STEM educators in the classroom. The novel computational tools developed in this project will advance knowledge and understanding for creativity psychometric assessment and across different fields (not only engineering). The PI team will also design assessment tools that are culturally responsive and minimally biased — especially for the growing number of students who speak English as a second language — and collaborate with STEM educators to maximize the usability of the platform in their classrooms. The online platform and course materials will be publicly available, facilitating the national transition to remote education and research (accelerated by the current pandemic) by providing online resources for STEM teachers and researchers across the country.\n\nThis project is supported by NSF's EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. The program supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent challenges in education.\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": "10068", "attributes": { "award_id": "2212352", "title": "Collaborative Research: HCC: MEDIUM: Body as Intervention: Toward Closed-Loop, Embodied Behavioral Health Interventions", "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": 2859, "first_name": "Balakrishnan", "last_name": "Prabhakaran", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-01", "end_date": "2026-07-31", "award_amount": 412423, "principal_investigator": { "id": 25946, "first_name": "Pedro", "last_name": "Lopes", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 289, "ror": "https://ror.org/024mw5h28", "name": "University of Chicago", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "There has been a drastic increase in stress and anxiety in the U.S., leading to a mental health pandemic. The need for effective mental health interventions is more urgent now than ever. By monitoring users' symptoms and their context (e.g., when someone is having an anxiety attack or experiencing cravings when passing by a bar) through wearables and IoT (Internet of Things) devices, mobile health (mHealth) technologies have the potential to transform mental health care. Despite the advanced monitoring capability, most existing mHealth interventions are digitization of traditional health interventions that do not deliver in-the-moment precision interventions in response to users' symptoms. As such, they inherit the limitations of their predecessors: the reliance on human motivation and the need for active engagement to be effective, resulting in limited adherence. To address this problem, the investigators will develop a class of novel solutions – sensory interventions – that can be effective without disrupting the users or requiring their active engagement. Sensory interventions are real-time closed-loop systems that directly act on the users’ bodies or immediate environment in response to users behavioral or physiological signals. Unlike existing solutions, sensory interventions combine applied engineering, signal processing, and machine learning to trigger interventions autonomously without user effort. The project will create three types of closed-loop wearable and IoT systems that use different modalities (vibration, airflow, and touch) to deliver sensory interventions in mental health contexts, such as cravings, workplace stress, and social stress. Ultimately, this project will enable mHealth interventions to be as rich, diverse, and personalized as mHealth monitoring solutions. This project will produce open-source software, hardware designs, and datasets. Collaborations with Cornell Tech Precision Health Initiative and with the University of Chicago Medicine and their clinical and industry partners will accelerate the dissemination of research through clinical evaluations and commercialization.\n \nMost existing mHealth behavioral health interventions, although coupled with advanced sensing systems to detect health needs, require conscious cognitive processing of information and active participation from users to be effective. This project will introduce and develop the concept of sensory interventions, a novel class of mHealth interventions that require little or no cognitive awareness to be effective. This project will investigate sensory interventions in four stages: (i) investigate and map modalities of external (electromechanical) stimuli to actuate neurological responses that produce a neurophysiological effect (ii) design and develop devices that enable these sensory interventions within the constraints of mHealth, (iii) determine physiological signals that are associated with target behaviors and integrate sensing systems, signal processing, and machine learning with sensory interventions to achieve closed-loop systems that automatically triggers intervention, and (iv) evaluate the efficacy, usability, and acceptability of the closed-loop systems (both in-lab and in situ). Throughout this process, the investigators will evaluate and characterize how sensory interventions impact three common stress-induced mental health challenges: substance cravings, workplace stress, and social stress. To intervene in substance cravings, the investigators will leverage heart rate biofeedback, develop a smartwatch-based system to deliver biofeedback using vibrotactors, and evaluate how such vibrotactile actuation mitigates alcohol and nicotine cravings. To intervene in workplace stress, the investigators will leverage breathing regulations, develop a fan-based system that alters the perception of airflow around the nose, and evaluate how such airflow entrains slow, guided breathing in the workplace. To intervene in social stress, the investigators will leverage affective touch, develop an arm-worn device that activates affective touch neurons, and evaluate how affective touch helps regulate social stress. Collectively, this research will enable a new class of mHealth interventions that are responsive to users’ health context in real-time and can be effective irrespective of users cognitive capacity or availability.\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": "10069", "attributes": { "award_id": "2212351", "title": "Collaborative Research: HCC: MEDIUM: Body as Intervention: Toward Closed-Loop, Embodied Behavioral Health Interventions", "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": 2859, "first_name": "Balakrishnan", "last_name": "Prabhakaran", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-01", "end_date": "2026-08-31", "award_amount": 686879, "principal_investigator": { "id": 5855, "first_name": "Tanzeem", "last_name": "Choudhury", "orcid": null, "emails": "[email protected]", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 279, "ror": "https://ror.org/05bnh6r87", "name": "Cornell University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 279, "ror": "https://ror.org/05bnh6r87", "name": "Cornell University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "There has been a drastic increase in stress and anxiety in the U.S., leading to a mental health pandemic. The need for effective mental health interventions is more urgent now than ever. By monitoring users' symptoms and their context (e.g., when someone is having an anxiety attack or experiencing cravings when passing by a bar) through wearables and IoT (Internet of Things) devices, mobile health (mHealth) technologies have the potential to transform mental health care. Despite the advanced monitoring capability, most existing mHealth interventions are digitization of traditional health interventions that do not deliver in-the-moment precision interventions in response to users' symptoms. As such, they inherit the limitations of their predecessors: the reliance on human motivation and the need for active engagement to be effective, resulting in limited adherence. To address this problem, the investigators will develop a class of novel solutions – sensory interventions – that can be effective without disrupting the users or requiring their active engagement. Sensory interventions are real-time closed-loop systems that directly act on the users’ bodies or immediate environment in response to users behavioral or physiological signals. Unlike existing solutions, sensory interventions combine applied engineering, signal processing, and machine learning to trigger interventions autonomously without user effort. The project will create three types of closed-loop wearable and IoT systems that use different modalities (vibration, airflow, and touch) to deliver sensory interventions in mental health contexts, such as cravings, workplace stress, and social stress. Ultimately, this project will enable mHealth interventions to be as rich, diverse, and personalized as mHealth monitoring solutions. This project will produce open-source software, hardware designs, and datasets. Collaborations with Cornell Tech Precision Health Initiative and with the University of Chicago Medicine and their clinical and industry partners will accelerate the dissemination of research through clinical evaluations and commercialization.\n \nMost existing mHealth behavioral health interventions, although coupled with advanced sensing systems to detect health needs, require conscious cognitive processing of information and active participation from users to be effective. This project will introduce and develop the concept of sensory interventions, a novel class of mHealth interventions that require little or no cognitive awareness to be effective. This project will investigate sensory interventions in four stages: (i) investigate and map modalities of external (electromechanical) stimuli to actuate neurological responses that produce a neurophysiological effect (ii) design and develop devices that enable these sensory interventions within the constraints of mHealth, (iii) determine physiological signals that are associated with target behaviors and integrate sensing systems, signal processing, and machine learning with sensory interventions to achieve closed-loop systems that automatically triggers intervention, and (iv) evaluate the efficacy, usability, and acceptability of the closed-loop systems (both in-lab and in situ). Throughout this process, the investigators will evaluate and characterize how sensory interventions impact three common stress-induced mental health challenges: substance cravings, workplace stress, and social stress. To intervene in substance cravings, the investigators will leverage heart rate biofeedback, develop a smartwatch-based system to deliver biofeedback using vibrotactors, and evaluate how such vibrotactile actuation mitigates alcohol and nicotine cravings. To intervene in workplace stress, the investigators will leverage breathing regulations, develop a fan-based system that alters the perception of airflow around the nose, and evaluate how such airflow entrains slow, guided breathing in the workplace. To intervene in social stress, the investigators will leverage affective touch, develop an arm-worn device that activates affective touch neurons, and evaluate how affective touch helps regulate social stress. Collectively, this research will enable a new class of mHealth interventions that are responsive to users’ health context in real-time and can be effective irrespective of users cognitive capacity or availability.\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": "10070", "attributes": { "award_id": "2151088", "title": "Learning to Lead (L2L): Building STEM Teacher Leaders that Broaden Participation in High-Need Schools", "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": 2088, "first_name": "Jennifer", "last_name": "Ellis", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-10-01", "end_date": "2027-09-30", "award_amount": 1479016, "principal_investigator": { "id": 25948, "first_name": "Jennifer", "last_name": "Albert", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 25947, "first_name": "Richard", "last_name": "Robinson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 626, "ror": "", "name": "Citadel Military College of South Carolina", "address": "", "city": "", "state": "SC", "zip": "", "country": "United States", "approved": true }, "abstract": "This Robert Noyce Teacher Scholarship Program Track 3: Master Teacher Fellows (MTF) project aims to broaden participation by connecting rural teachers to professional development and one another. Teachers will experience and reflect on effective pedagogies via graduate coursework culminating in two South Carolina Add-On Certification Endorsements (Problem Based Learning and Online Teaching and Teacher Leader), as well as 30 additional hours of graduate credit. While teacher education programs have prepared teachers for the content and pedagogies of the traditional school, few, if any, have prepared teachers for the unanticipated immersion into the online space that occurred during the first 18 months of the COIVD-19 pandemic. The Project Based Learning certificate will help MTFs explore ways to leverage their enhanced pedagogical content knowledge, including new and exciting forms of student engagement, student-to-student interaction, and assessment. Through the Teacher Leader certificate, the MTFs will learn research-based strategies that have been shown to promote quality teacher leader outcomes, including balancing teaching and leading, attending to equity-based norms of teaching, and knowledge of adult learning and career development. Teachers will connect with one another as they collaborate with project staff to create a statewide rural math teacher network, a teacher-driven professional community focused on addressing the unique challenges and opportunities faced by rural mathematics teachers.\n\nThe Citadel’s Learning to Lead (L2L): Building STEM Teacher Leaders that Broaden Participation in High-Needs Schools project is a collaboration between The Citadel’s Zucker Family School of Education and Swain Family School of Science and Mathematics (higher education), as well as Georgetown County School District (high-need local education agency) and the Lowcountry STEM Collaborative (non-profit). This project seeks to develop 18 teachers (with at least a Master’s degree) into Rural Teacher Leaders over five years. The L2L project strives to stimulate sustainable improvements in the quality of mathematics teaching and learning in rural high-needs schools through the following four goals: (1) building MTFs’ pedagogical content knowledge and skills, (2) building MTFs’ teacher leadership knowledge and skills, (3) collaborating with MTFs to create the SC Rural Math Teacher Network (SC-RMTN) with associated PD resources, and (4) supporting teachers to continue the SC-RMTN into the future. The L2L project incorporates an intentional form of gradual release in which MTFs take ownership of the knowledge, resources, and communities they have helped to create, greatly increasing the likelihood of project continuation long after its initial 5 year period. This Track 3: Master Teaching Fellowships 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 effectiveness and retention 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": "10071", "attributes": { "award_id": "2141283", "title": "The TIMES Model: Investigating the Importance of Social Support Timing", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)", "Social Psychology" ], "program_reference_codes": [], "program_officials": [ { "id": 2516, "first_name": "Steven", "last_name": "Breckler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-01", "end_date": "2025-08-31", "award_amount": 548750, "principal_investigator": { "id": 25950, "first_name": "Niall", "last_name": "Bolger", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 25949, "first_name": "Bert", "last_name": "Uchino", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 196, "ror": "https://ror.org/00hj8s172", "name": "Columbia University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Stress is a regular part of everyday life. It may arise from common experiences such as problems at work or arguments with friends, or it may have its origin in large-scale traumatic experiences such as a pandemic, political polarization, or economic depression. Such experiences permeate lives and are known to harm well-being. Research shows that the negative effects of such stressors can be reduced by supportive social relationships. Prior studies examining social support during times of stress have focused almost exclusively on the period leading up to or during a stressor. Yet, there is a growing recognition that recovery processes following a stressor may have important long-term implications for well-being, and in ways that differ from social support before or during a stressful event. This project focuses on how the psychological mechanisms of social support differ before versus after a stressful event. It is expected that social support received after a stressful event provides a particular benefit for recovery, and that it operates through distinct psychological mechanisms and has different outcomes compared to support enacted before a stressor. Making a distinction between pre-stressor and post-stressor social support is important because many stressful events are not anticipated, which means that pre-stressor support is not always available. This project will inform potential interventions by advancing understanding and improving how close others can help each other cope with stressors in the aftermath of stressful events.\n\nThis project focuses on the role of social support during a post-stressor period in facilitating emotional and physiological stressor recovery. The research considers the questions of whether post-stressor support involves distinct mediating processes and distinct outcomes when compared to support provided during the pre-stressor period. It is generally hypothesized that post-stressor support benefits physiological and emotional recovery. More specifically, it is expected that effective pre-stressor support reduces recipients’ distress and sympathetic arousal because of higher self-efficacy. In contrast, effective post-stressor support is expected to enhance recipients’ calmness, composure and parasympathetic control because of lower rumination, greater positive reframing, and rebuilding of the self. These hypotheses are tested in a daily diary study with a long-term follow-up and in an experiment introducing a social stressor. The project explores longer-term implications of post-stressor support and considers potential boundary conditions. Laying the foundation for potential future interventions is a priority. Students involved in the research learn about psychophysiological methods and participate in the conduct of studies on people in close relationships.\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": "10072", "attributes": { "award_id": "2011378", "title": "Theoretical Biophysics: Searching for Principles", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "PHYSICS OF LIVING SYSTEMS" ], "program_reference_codes": [], "program_officials": [ { "id": 780, "first_name": "Krastan", "last_name": "Blagoev", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-08-15", "end_date": "2023-07-31", "award_amount": 42000, "principal_investigator": { "id": 25952, "first_name": "David", "last_name": "Schwab", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 25951, "first_name": "Ilya M", "last_name": "Nemenman", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1879, "ror": "", "name": "CUNY Graduate School University Center", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "This project will provide partial support for the conference \"Theoretical Biophysics: Searching for principles\" (the Conference), to be held at the CUNY Graduate Center in New York City on Sep. 14 -16, 2022. The Conference will bring together world leaders in theoretical biophysics, and it will provide the opportunity for them to interact with education experts in the field, as well as with notable theorists in other fields of physics. The Conference is aimed at surveying achievements at the interface of theoretical physics and biology, to understand whether we expect theory at this interface to be different compared to the rest of theoretical physics, and if it will contribute differently, then how and why. Finally, the Conference will aim to understand challenges and opportunities involved in teaching the next generation of scientists at this interface.\n\nThe field of theoretical biophysics has grown in the recent decades from a boutique corner of physics to a substantial part of the international physics community. For example, over the course of the past ten years, the footprint of biophysics at the Annual March Meeting of the American Physical Society has more than doubled. Together with related fields of statistical physics (soft matter, polymer physics, statistical physics) biophysics now accounts for about a quarter of the talks at the meeting. Collectively, these groups are responsible for essentially all of the growth of the meeting in the last decade. Following such a rapid growth, it is now the time to take stock of the field and to understand where we are, and where we go from there. Are we still a single field, or have we fragmented into a collection of sub-disciplines roughly paralleling major divisions of life sciences? What have we contributed to understanding life that biologists would not be able to do on their own? Have we changed the discourse and the type of questions that are being asked? How do we educate the next generation of scientists to ensure that future progress remains equally dramatic? This Conference is needed precisely to answer these questions. The conference will be timely since conferences in this area have been mostly virtual during the pandemic and the National Academies of Sciences, Engineering and Medicine has just completed the first Decadal Review of Biological Physics\n\nThis event will provide an unparalleled opportunity to survey and summarize the current state of the field of theoretical biophysics. The perspectives presented at the Conference should help frame big questions for the next decade in the field. The presentations at the meeting will be recorded and made publicly available, increasing broader impact. Finally, by means of attracting a diverse group of participants, presenters, and discussants, including junior scientists, the meeting will contribute to the growth of diversity in physical 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": "10073", "attributes": { "award_id": "2224003", "title": "Conference: The Seventh Annual Meeting of SIAM Central States Section", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "COMPUTATIONAL MATHEMATICS" ], "program_reference_codes": [], "program_officials": [ { "id": 25953, "first_name": "Stacey", "last_name": "Levine", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-09-01", "end_date": "2023-08-31", "award_amount": 20000, "principal_investigator": { "id": 25955, "first_name": "Xu", "last_name": "Zhang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 25954, "first_name": "Xukai", "last_name": "Yan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 387, "ror": "https://ror.org/01g9vbr38", "name": "Oklahoma State University", "address": "", "city": "", "state": "OK", "zip": "", "country": "United States", "approved": true }, "abstract": "The 7th Annual Meeting of Society of Industrial and Applied Mathematicians Central States Section (SIAM-CCS) will be held at the Stillwater campus of Oklahoma State University during October 1-2, 2022. The conference website is https://siamcss2022.okstate.edu/. The SIAM Central States Section (SIAM-CSS) was founded in 2014, and it serves SIAM members in eight central states in the United States, including Arkansas, Colorado, Iowa, Kansas, Mississippi, Missouri, Nebraska, and Oklahoma. The SIAM-CSS Annual Meeting has been held annually since 2015, with the primary goal of improving the development of applied and computational mathematics throughout all central states, as well as facilitating knowledge transfer and promoting interdisciplinary collaborations among applied mathematics and other disciplines in science and engineering. \n\nThe SIAM-CSS annual conference series provides an important forum for applied and computational mathematicians from central states to present their latest achievements, communicate and exchange ideas, and enhance collaborations. It provides an excellent opportunity for researchers in all stages of their careers, especially early career mathematicians, to establish interactions with researchers from all over the U.S. and other countries. It is essential in stimulating research activities in relatively less developed states. As the first face-to-face meeting after the pandemic, the conference will bring vitality to the applied math community in the region and promote the development of the discipline. This NSF grant will solely support the participation of students, postdoctoral scholars, early career faculty, and underrepresented groups in STEM.\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": 1405, "pages": 1420, "count": 14196 } } }