Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=4&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=5&sort=funder", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=3&sort=funder" }, "data": [ { "type": "Grant", "id": "2518", "attributes": { "award_id": "2014626", "title": "Models for Complex Functional and Object Data", "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": 7186, "first_name": "Pena", "last_name": "Edsel", "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": 300000, "principal_investigator": { "id": 7187, "first_name": "Hans-Georg", "last_name": "Mueller", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 276, "ror": "", "name": "University of California-Davis", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 276, "ror": "", "name": "University of California-Davis", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "Big data are increasingly encountered across society and all of the sciences and pose novel challenges for statistical analysis, due to their complexity and size. Challenging data analysis tasks that motivate this research originate in brain imaging, genomics, the social sciences and many other areas of current interest. To make sense of such data and extract relevant information requires principled statistical methodology that is suitable for the analysis of large samples of complex data. Examples include networks or age-at-death distributions for which common algebraic operations such as sums or differences are not defined. In many instances such data objects may also be repeatedly observed over time, and the quantification of their time dynamics is then of great interest. For example, one might be interested to determine whether sudden changes occur and where these are located in time. Statistical methodology will be developed that addresses these data analytic needs, along with theory and efficient computational implementations. This new methodology is expected to lead to substantial new insights. For example, it will be possible to quantify phenomena such as changes in temperature, mortality or income distributions over calendar years, or changes in brain connectivity networks as a function of age, which will aid in distinguishing normal and pathological brain aging. The new methodology will also make it possible to detect differences between groups of complex data, for example between the mortality distribution of countries, including the identification of clusters. The project also provides research training opportunities for undergraduate and graduate students. \n\nThe focus of this research is the development of statistical methods and theory for random objects, i.e., metric space valued random variables, including object-valued functional and longitudinal data. Due to the lack of Euclidean structure, existing methods from high-dimensional and functional data analysis are generally not applicable for metric-space valued random objects. This motivates the development of novel approaches that address the challenge of a lack of Euclidean structure. Major lines of inquiry will be regression and change-point models for random objects on one hand and methods for trajectories of random objects including complex functional data on the other. New regression and change-point models to be studied include distributions as predictors; regression models for point processes; inference and single index modeling for Frechet regression; and change-point analysis for sequences of object data under various scenarios. For object-valued functional data, an emphasis will be the development of time warping models for random objects and of models for longitudinal random objects in various spaces, including the case where the data are only sparsely and irregularly observed in time. Tools and theory for principled statistical analysis of random objects to be developed will rely on empirical process theory for M estimators in metric spaces, U statistics and related approaches. These developments will lead to the creation of a toolbox suitable for data analysis of object data and associated freely available software.\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": "2741", "attributes": { "award_id": "1902691", "title": "Global Dynamics of Nonlinear Dispersive Evolution Equations and Spectral Theory", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Mathematical and Physical Sciences (MPS)", "ANALYSIS PROGRAM" ], "program_reference_codes": [], "program_officials": [ { "id": 8102, "first_name": "Marian", "last_name": "Bocea", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2018-07-01", "end_date": "2021-09-30", "award_amount": 270000, "principal_investigator": { "id": 8103, "first_name": "Wilhelm", "last_name": "Schlag", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "This project aims at understanding the propagation of waves in a wide sense. On the one hand, the PI will investigate the behavior of waves in space, as they interact nonlinearly with themselves and matter over large space-time scales. The ultimate goal is to explain how the energy, which is stored in a wave undergoing a nonlinear dynamical evolution, ultimately splits into quantized pieces and a wave \"at the horizon\". The latter refers to energy, possibly of large size, which is infinitely spread out and does not interact with anything in a noticeable fashion. In contrast with this macroscopic behavior, the project also aims at understanding the behavior of waves on the microscopic scale, such as in crystals or quasi-crystals. The goal is to explain transitions from an insulating state to that of a conductor, which these materials may exhibit as they undergo changes on the molecular level. Such changes may occur through the insertion of impurities, or changes in the environment. Both the macroscopic as well as the microscopic behavior of waves is of crucial importance to science and engineering, and profoundly affects our daily modern lives. Modern communication relies on waves transmitted over large distances both in space but also along glass fiber cables. For the latter the properties of the material are crucial and both nonlinear effects as well as aforementioned microscopic phenomena decide the suitability of the underlying medium. \n\nMore technically speaking, the PI intends to further investigate the rigorous mathematical theory of focusing dispersive semilinear evolution equations. A major open problem is to analyze the resolution of any solution into moving solitons and radiation. Some success has been achieved in recent years on this important problem, but for nonintegrable equations we are far from a satisfactory understanding. The PI is currently involved in the study of this problem in the dissipative setting in which some damping is added to the equation. The Hamiltonian setting appears to be very difficult at the moment, especially in the subcritical regime. The methods involved derive from dynamical systems, invariant manifold theory, and dispersive PDEs. The quantum mechanical problems alluded in the previous paragraph belong to the area of Anderson localization. Together with his long-standing collaborator Michael Goldstein at Toronto, but also with young collaborators which are joining the field, the PI intends to bring the body of techniques which were developed over the past 20 years based on large deviation estimates, the avalanche principle, semi-algebraic sets, and harmonic analysis such as (pluri)subharmonic functions and the Cartan estimate, to bear on both linear and nonlinear problems in dynamical systems and spectral theory. Ultimately, the goal here is also to better describe the behavior of wave propagation in disordered media.\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": "2818", "attributes": { "award_id": "1907223", "title": "NSF Postdoctoral Fellowship in Biology FY 2019: Holistic Restoration: Integrating Community Ecology into Coastal Mangrove Conservation", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Broadening Participation of Gr" ], "program_reference_codes": [], "program_officials": [ { "id": 8392, "first_name": "Daniel", "last_name": "Marenda", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-08-01", "end_date": "2021-07-31", "award_amount": 138000, "principal_investigator": { "id": 8393, "first_name": "Alexandria", "last_name": "Moore", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 973, "ror": "", "name": "Moore, Alexandria Chanel", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 973, "ror": "", "name": "Moore, Alexandria Chanel", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2019, Broadening Participation of Groups Under-represented in Biology. The fellowship supports a research and training plan for the Fellow that will increase the participation of groups underrepresented in biology. Coastal wetlands are among the most valuable and threatened ecosystems across the globe. Given their declining status, significant effort has been devoted to conservation and restoration. However, most efforts fail to meet stated goals because of an emphasis on practices rooted in an incomplete understanding of these ecosystems. Due to traditional restoration approaches, a knowledge gap exists in our current understanding of the factors that maintain the health and functioning of coastal wetlands. Further, conservation practices that aim to protect ecosystems often fail to consider local values, knowledge systems, and needs (altogether known as 'biocultural values'), an oversight which can cause conflict and impact conservation outcomes. This project therefore aims to link the ecological values of coastal wetlands with the associated biocultural values anchored to the surrounding communities. This interdisciplinary approach endeavors to guide conservation practices towards just and sustainable solutions. The restoration and management recommendations that result from this work will thus have implications for conservation and restoration approaches in the various global locales where the need for environmental conservation and cultural preservation overlap.\n\nThe objectives of this study are to (1) address a biological knowledge gap in coastal wetland ecosystem ecology, (2) determine the social and biocultural values associated with coastal wetlands, and (3) incorporate ecological data and biocultural knowledge and values into coastal wetland restoration practice and land management decisions. These objectives will be addressed by (1) conducting a consumer presence-absence field experiment to determine impacts on various essential coastal wetland processes, (2) conducting focus groups and open-ended key informant interviews along with a systematic literature review, and (3) engaging with local environmental management officials to inform best-practices for restoration utilizing the results of the field experiment and interviews. This project also aims to increase diversity, equity, and inclusion in conservation by engaging high school and undergraduate students from traditionally underrepresented backgrounds through various means, including the AMNH-sponsored Inclusive Conservation Community Initiative, the Science Research Mentoring Program, and Fellowship-sponsored research assistants. Additionally, specific training objectives include developing and piloting focus group interview procedures, engaging local government and land management agencies in data-driven restoration decisions, and combining ecological and sociocultural perspectives to improve conservation outcomes.\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": "2695", "attributes": { "award_id": "1910283", "title": "I-Corps: Restoration of Ovarian Endocrine Function in Adolescent Girls with Premature Ovarian Insufficiency", "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": 7934, "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": "2019-02-01", "end_date": "2022-01-31", "award_amount": 50000, "principal_investigator": { "id": 7935, "first_name": "Ariella", "last_name": "Shikanov", "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": "The broader impact/commercial potential of this I-Corps project is to identify stakeholders and customers and to develop the most appropriate path forward to translate the company's technology to the clinic and bring it to the patients. Currently young girls suffering from premature ovarian insufficiency (POI) as a result of anticancer treatments have limited and inadequate options to undergo puberty and start their transition into adult life. The existing hormone replacement therapy (HRT) applied to induce puberty in girls with POI leads to long-term morbidities, such as decreased bone density, predisposition to obesity and diabetes. The company's technology allows the restoration of ovarian endocrine function in prepubescent girls and has the potential to become a central mainstream treatment for POI, which would result in significant improvement of the short and long-term health and eliminate long-term morbidities associated with premature ovarian failure. The commercial benefit of the proposed treatment would result from significant lower health costs associated with obesity, diabetes and osteoporosis. \n\nThis I-Corps project will further the company's understanding of the current state of the field and the value of the proposed technology, and help identify the next steps for preclinical and clinical studies. The company developed an immunoisolating capsule that supports the survival and function of ovarian allograft eliminating the need for immune suppression. The company's central hypothesis is that ovarian tissue secretes the gonadal hormones, estradiol, progesterone, androstenedione, activins and inhibins, in response to systemic hormone stimulation in a pulsatile and dynamic rate required for physiological progression through puberty, growth and associated metabolic changes. Experimental data from in vivo mouse and primate studies have demonstrated promising results of restoration of hormone function integrated in the endocrine system and neuroendocrine axis, with no evidence of immune rejection or local inflammatory adverse response. The next critical steps in the company's project is to perform customer discovery and identify partners for first-in-human trials.\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": "2941", "attributes": { "award_id": "1928614", "title": "FW-HTF-RL: Collaborative Research: Future expert work in the age of \"black box\", data-intensive, and algorithmically augmented healthcare", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "FW-HTF Futr Wrk Hum-Tech Frntr" ], "program_reference_codes": [], "program_officials": [ { "id": 8909, "first_name": "Ruyan", "last_name": "Guo", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-09-01", "end_date": "2023-08-31", "award_amount": 1500000, "principal_investigator": { "id": 8915, "first_name": "Oded", "last_name": "Nov", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 8910, "first_name": "Maurizio", "last_name": "Porfiri", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 8912, "first_name": "Batia M", "last_name": "Wiesenfeld", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 8913, "first_name": "Yindalon", "last_name": "Aphinyanaphongs", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 8914, "first_name": "Yvonne W", "last_name": "Lui", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 167, "ror": "https://ror.org/0190ak572", "name": "New York University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "The nature of expert work is changing. Technological advances such as artificial intelligence and data science increasingly enable new computerized tools and products that make predictions and recommendations which were previously made by human experts. However, many of these new tools are \"black boxes\" whose inner workings are often not understood by their users, place demands that create cognitive load, and de-emphasize abstract problem solving. As these technologies are being deployed, there is little understanding of how they affect experts' work practices, perceptions of the value of work, and the expert-client relationship. Foundational research is needed in order to understand and improve work in an age of data-intensive enhanced cognition, especially in healthcare where such new technologies are rapidly changing expert work. This project is expected to transform the future of expert work through a combined redesign of technology, workflow, and interactions. It will lead to: a healthier and better-informed population; efficient deployment of human capabilities in restructured healthcare occupations; healthcare providers reducing the proportion of time spent on repetitive tasks while increasing time devoted to value-adding, meaningful activities; guidelines on design and delivery of cognition-augmenting expert advice; and students who are well versed in cross-disciplinary research on cognition-augmenting technologies in the workplace.\n\nThe project's goals are: i) to study the relationships between experts, patients, and technologies in a multidisciplinary way; ii) to develop new ways for these technologies to serve experts and clients; and iii) to make expert work more responsive, value-adding, and meaningful. The project includes two strands. In the \"Understand\" strand, the interactions between experts, clients and cognition-augmenting technologies are examined. In the \"Shape\" strand, the project lays the foundations for technological and organizational interventions that will make the interactions between experts, clients, and technology more effective and empowering. With a multidisciplinary team including researchers in computer science, human-computer interaction, dynamical systems, and organization alongside with medical clinicians, the project will contribute: i) scalable approaches toward quantifying the benefits and drawbacks of cognition-augmented interactions, as well as measuring information flow in relationships between experts, clients, and cognition augmenting technologies; ii) insights into when, why, and how cognition-augmenting technologies are experienced as expertise enhancing, rather than degrading; iii) data-driven methodologies to predict the effects of technical and organizational interventions on experts' work and experts' interaction with patients; iv) novel tools and workflows for experts and clients to interact with black-box cognition-augmenting technologies; v) modeling how representation of problems can be embedded in expert; and vi) systematic exploration of explanation and dialogue interventions with regard to how they affect experts' work and expert-client relationship.\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": "10803", "attributes": { "award_id": "2239410", "title": "CAREER: Evolutionary Games in Dynamic and Networked Environments for Modeling and Controlling Large-Scale Multi-agent Systems", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "EPCN-Energy-Power-Ctrl-Netwrks" ], "program_reference_codes": [], "program_officials": [ { "id": 26885, "first_name": "Eyad", "last_name": "Abed", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-09-01", "end_date": "2028-08-31", "award_amount": 503462, "principal_investigator": { "id": 26886, "first_name": "Ceyhun", "last_name": "Eksin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 282, "ror": "", "name": "Texas A&M Engineering Experiment Station", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "Classical game theory addresses how individuals make decisions given suitable incentives, for example, whether to use resources rapaciously or with restraint. However, game theory does not typically address the consequences of the actions that reshape the resources over the long term. Indeed, individuals' actions often subsequently modify the commons (environment) and associated payoffs. In this project, we propose a unified mathematical framework to model and analyze the coupled evolution of individuals' incentives, opinions, and the environment using tools from game theory, network science, and nonlinear dynamic systems. Based on the mathematical framework, the proposed project is organized to study fundamental issues relating to (a) when and how desirable behavior, e.g., cooperative behavior, arise in the populations, and (b) whether tragedies of the commons can be averted in complex systems, e.g., during a pandemic. Scientific contributions of this project will have the potential to have a transformational impact on our understanding of the emergence of cooperation and environmental collapse in public health systems where individuals' actions affect the resources, and in engineered multi-agent systems, e.g., autonomous or energy systems, that involve self-interested entities. The overarching goals of the project are rooted in an educational agenda with initiatives, e.g., a summer residential research experience for educators, designed to expose the broader public to central concepts in game theory and nonlinear systems, and push for a systems-thinking perspective on societal problems.\n\nThe premise of this project is that individual behavior is dynamic, i.e., evolves according to selection or learning, and such learning behavior has subsequent effects on the environment, and thus on the future incentives for learning. The proposed research is a concerted effort to develop a mathematical framework for studying population behavior when the population’s well-being depends on the environment that the behavior is affecting. The proposed research aims to achieve the following scientific contributions: 1) novel models of strategic learning dynamics in feedback-evolving games with relevance to socio-biological and -technological systems including epidemics and autonomous systems; 2) decentralized algorithms for tracking rational behavior in dynamic network games; 3) a framework for dynamic intervention mechanisms to induce desirable system-level behavior in such settings; 4) design and analysis of experiments to uncover the role of peer effects and ambiguity on perceived risks on cooperation. This effort will lead to novel analysis, and scalable decentralized algorithms applicable to addressing real-world problems in social and technological multi-agent systems.\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": "2759", "attributes": { "award_id": "1847287", "title": "Doctoral Dissertation Research: Identifying Positively-Selected Introgressed Genetic Variants with Regulatory Effects in Humans", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Social, Behavioral, and Economic Sciences (SBE)", "Bio Anthro DDRI" ], "program_reference_codes": [], "program_officials": [ { "id": 8165, "first_name": "Rebecca", "last_name": "Ferrell", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-05-15", "end_date": "2021-04-30", "award_amount": 33433, "principal_investigator": { "id": 8167, "first_name": "Terence", "last_name": "Capellini", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 455, "ror": "https://ror.org/03vek6s52", "name": "Harvard University", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 8166, "first_name": "Evelyn", "last_name": "Jagoda", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 455, "ror": "https://ror.org/03vek6s52", "name": "Harvard University", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "Fifty thousand years ago, modern humans dispersing out of Africa to Europe and Asia met now-extinct human relatives, such as Neanderthals, and interbred with them. As a result, genetic variation from Neanderthals exists in the human gene pool, but the effects of this variation on human biology are not well understood. In this doctoral dissertation project, the researcher will conduct a large-scale laboratory-based genetic experiment to test whether Neanderthal variants can affect the degree to which a gene is active in human immune cells. By identifying these variants and making publicly available the raw data from this experiment, the researchers will advance knowledge about the effects of evolutionary history and genetic variation on the immune system of living humans. Given that science news often features stories about Neanderthals, the researchers will utilize popular interest in this area to demonstrate the biological and medical relevance of studying human evolutionary history. They will also work with two museums to develop an exhibit that will additionally highlight the practical importance of this field of research. Furthermore, this project will help promote women in science given that the research will largely be undertaken by a female graduate student who is committed to training other women in science and has been active in the organization for Graduate Women in Science Engineering at her university. \n\nAlthough the last two decades have seen great strides in genetic research, because the specific function of most of the human genome is still unknown, researchers face difficulty when trying to connect most specific genetic mutations to their effect on biology. To aid in this discovery, datasets have been produced that allow correlations between the presence of genetic variation and biological phenotypes. However, because genetic variants near each other are often inherited together, it can be difficult to determine which genetic variant is responsible for the biological effect, limiting the ability to truly understand the mechanism. This is especially true in the case of Neanderthal genetic sequences present in living humans, which mostly lay in poorly understood parts of the genome that are thought generally to regulate the expression of genes. Nonetheless, correlational evidence suggests that this Neanderthal genetic variation may be affecting human immune system function. The researchers will conduct an experiment in which they simultaneously test thousands of Neanderthal genetic variants and their human counterparts for their ability to regulate the expression of genes in the immune system, in order to isolate the specific Neanderthal genetic variants that affect the biology of the human immune system. This will allow researchers to focus future work on specific functional testing of these important genetic variants. Furthermore, by directly comparing correlational findings to the results in a laboratory experiment, this research will deepen the understanding of these commonly used genetic datasets.\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": "2840", "attributes": { "award_id": "1916914", "title": "RoL: Collaborative Research: When a pathogen becomes a mutualist: discovery, evolution and rules that govern function and acquisition in wasp-viral symbiosis", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Systematics & Biodiversity Sci" ], "program_reference_codes": [], "program_officials": [ { "id": 8488, "first_name": "Christopher", "last_name": "Balakrishnan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-09-01", "end_date": "2023-08-31", "award_amount": 481235, "principal_investigator": { "id": 8489, "first_name": "Barbara", "last_name": "Sharanowski", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 173, "ror": "", "name": "The University of Central Florida Board of Trustees", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 173, "ror": "", "name": "The University of Central Florida Board of Trustees", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "Recent discoveries have shown that symbiotic relationships of viruses with their hosts are pervasive, confer major benefits to their hosts, and have played a major role in the evolution of life on earth. Understanding how these viral associations evolve is thus essential for a holistic view on the evolution of a broad diversity of organisms. Parasitoid wasps (wasps that grow within and kill other insects) are a natural laboratory for understanding the evolution of viral symbiosis because they are highly diverse and have evolved repeated associations with viruses. These viruses are able to suppress the immune defense mechanisms of the insect hosts that are parasitized by the wasps, enabling the wasps to survive and reproduce. Parasitoid wasps also provide substantial economic benefits to society because they are natural enemies of insect pests that cause damage to forests and agricultural crops. This project investigates the evolution and interactions between one of the most astonishing radiations on Earth (braconid parasitoid wasps, with 19,000 species) and the massive untapped diversity of their symbiotic viruses. The long-term goal is to understand the rules that govern the associations of the viruses, the wasps, and the hosts of the wasps. This research project advances knowledge in several ways: (1) discovery of new biodiversity in two poorly studied areas of the tree of life--viruses and wasps; (2) resolution of the evolutionary history and age of wasp-viral symbioses; (3) discovery of predictive genomic traits for viral symbiosis to understand the rules that govern these interactions; (4) characterization of the function of viruses; and (5) generate publicly available genome data. The proposed work will substantially transform understanding of symbiotic viral evolution, which will provide general information about virus evolution. The researchers will integrate wasp and viral research with education and public outreach by working closely with teachers in local schools and developing new educational resources. Furthermore, the program will improve STEM education and educator development and increase public literacy and engagement in STEM.\n\nThis project integrates phylogenetic, functional, and genomics approaches to discover the rules that govern mutualistic associations between viruses and wasps and, in turn, the interactions between these parasitoid wasps and their hosts. The overall objectives are to resolve and date the evolutionary relationships of the wasp family Braconidae using new methods of DNA analysis, discover which wasp lineages are associated with mutualistic viruses and the timing of their domestication, determine how viruses affect the antagonistic interactions between the wasps and their hosts, and examine genome features related to viral mutualism. The researchers aim to: (1) Resolve and date deep and shallow nodes for one of the most diverse lineages (19,000 species) on Earth; (2) Discover and characterize the multiple origins of viral symbiosis in Braconidae; and (3) decipher the roles of viral symbionts in the biology of the parasitoid wasps and their hosts. The outreach plan has two main components: 1) Providing research internships in the lab for local K-12 teachers so that they may learn new research techniques that will improve their teaching; and 2) using immersive virtual reality and animation experiences to engage the public and enhance learning in undergraduate education. The researchers will also provide integrated research and training opportunities to underrepresented mentees (2 postdoctoral researchers, 7 undergraduate and 2 graduate students) across the disciplines of phylogenetics, functional and comparative genomics, and revisionary systematics.\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": "2534", "attributes": { "award_id": "2038439", "title": "CAREER: Biochar Systems for Sustainable Applications in the Food-Energy-Water Nexus", "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": 7250, "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": "2020-07-01", "end_date": "2024-06-30", "award_amount": 519401, "principal_investigator": { "id": 7251, "first_name": "Yuan", "last_name": "Yao", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 452, "ror": "https://ror.org/03v76x132", "name": "Yale University", "address": "", "city": "", "state": "CT", "zip": "", "country": "United States", "approved": true }, "abstract": "Biochar is a carbon-rich solid byproduct of thermochemical biomass conversions. It has potential applications in food, energy, and water systems. This project aims to advance potential biochar applications by (1) using artificial intelligence (machine learning) approaches to predict process data and life cycle assessment (LCA) of various combinations of biomass feedstocks, conversion pathways, and applications of biochar; (2) building an integrated framework for modeling and analysis of biochar systems in the food-energy-water (FEW) nexus; and (3) demonstrating the framework through real-world case studies in different geographic, temporal, and socioeconomic contexts. The educational and outreach objectives include (1) attracting underrepresented students to STEM fields by developing a multimedia package for FEW and biochar sustainability; (2) developing both in-class and online courses and providing training and professional development opportunities to integrate research and education activities for undergraduate and graduate students; (3) developing an international network of scholars for FEW, biochar sustainability, and interdisciplinary research communities with a long-term goal of forming an international research and education program.\n\nThis project targets bridging knowledge gaps for biochar production and effective applications in enhancing FEW sustainability by integrating LCA, technico-economic analysis (TEA), Geographic Information System (GIS), machine learning, and dynamic modeling. Understanding the impacts of using various biomass substrates for different biochar applications on the environment, economics, and communities will lay a foundation for the further design and implementation of large-scale biochar systems under different socioeconomic, climate change, and resource limiting conditions. Integration of advanced modeling tools including LCA, GIS, and machine learning that are commonly used in different disciplines is an important feature of the approach. Through integration of advanced modeling methods from engineering, environmental science, natural science, and data science, this project seeks to demonstrate how transdisciplinary research can create improved societal outcomes.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "10463", "attributes": { "award_id": "2119299", "title": "Collaborative Research: PPoSS: LARGE: Principles and Infrastructure of Extreme Scale Edge Learning for Computational Screening and Surveillance for Health Care", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "PPoSS-PP of Scalable Systems" ], "program_reference_codes": [], "program_officials": [ { "id": 637, "first_name": "Wei", "last_name": "Ding", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-10-01", "end_date": "2026-09-30", "award_amount": 2127227, "principal_investigator": { "id": 26470, "first_name": "Fan", "last_name": "Ye", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 26469, "first_name": "Elinor R", "last_name": "Schoenfeld", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 578, "ror": "", "name": "SUNY at Stony Brook", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "This project investigates a completely new cross-disciplinary concept of “Computational Screening and Surveillance (CSS)” that utilizes edge learning to detect early indicators of diseases, and monitor health changes in both individuals and populations. CSS analyzes and interprets continuous and heterogeneous physical and physiologic sensing-data streams of human subjects to produce real-time information, knowledge, and insights about their health status. The project’s novelty is a data-driven paradigm that revolutionizes the understanding, prediction, intervention, treatment, and management of acute/infectious, chronic physical and psychological diseases. The project’s impacts are enormous social and economic benefits to individuals, organizations, and the healthcare system: early detection, preemptive intervention and management can lead to greatly improved quality of care, and huge savings for multiple diseases each costing hundreds of billions of dollars every year.\n\nThe investigators design, develop and evaluate principles and solutions for CSS enabled by extreme-scale edge learning spanning four dimensions: data modalities, health conditions and data patterns, Artificial Intelligence/Machine Learning (AI/ML) algorithms and models, and individuals/populations. The design is guided by four principles: exploit scale and heterogeneity, design for uncertainty, privacy as a first-class citizen, and faults and attacks as a norm. The investigators will 1) design AI/ML algorithms for learning data patterns and correlations for diverse health conditions in both individuals and populations at extreme scales; 2) quantify theoretical bounds on the tradeoffs between security, privacy protection, and learning accuracy in order to protect against various attacks on data and models at both the edge and cloud; 3) develop programming abstractions for automated exploration of competing AI/ML methods under uncertainty, and system mechanisms to protect stream processing integrity against sensitive data disclosure and faulty/malicious analytics; and 4) devise neural architectures and accelerators for computation efficiency at the constrained edge, data efficiency using limited training sets, and human efficiency utilizing AutoML.\n\nThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 4, "pages": 1424, "count": 14236 } } }