Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=5&sort=program_reference_codes
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=program_reference_codes", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=program_reference_codes", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=6&sort=program_reference_codes", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=4&sort=program_reference_codes" }, "data": [ { "type": "Grant", "id": "2816", "attributes": { "award_id": "1925596", "title": "CC* Compute: Accelerating Computational Research for Engineering and Science (ACRES) at Clarkson University, A Campus Cluster Proposal", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Campus Cyberinfrastructure" ], "program_reference_codes": [], "program_officials": [ { "id": 8385, "first_name": "Kevin", "last_name": "Thompson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2019-07-01", "end_date": "2021-06-30", "award_amount": 396950, "principal_investigator": { "id": 8387, "first_name": "Joshua", "last_name": "Fiske", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 597, "ror": "https://ror.org/03rwgpn18", "name": "Clarkson University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 8386, "first_name": "Brian", "last_name": "Helenbrook", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 597, "ror": "https://ror.org/03rwgpn18", "name": "Clarkson University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Clarkson University is building a computational cluster (ACRES: Accelerating Computation Research for Engineering and Science) to support data and computationally intensive projects aligned with Clarkson's four interdisciplinary research themes: Data Analytics, Healthy World Solutions, Advanced Materials Development, and Next Generation Healthcare. ACRES facilitates the conduct of high-impact, collaborative research that requires access to high-performance computing (HPC) resources, enables research currently not practical/feasible, and also supports student-learning opportunities through credit-bearing courses, undergraduate research, and an existing NSF REU site focusing on HPC. As a campus resource, ACRES is made available to any faculty member or student at the University according to queueing policies implemented to ensure fair-access. And, ACRES supports Clarkson's increased focus on computational research and a cluster hire of computationally active faculty. \n\nThe ACRES compute cluster replaces an existing, five-year-old high-performance compute cluster whose computational capacity provided 1.05M core-h/yr. Research need for computational capacity has grown to an identified total of 8.5M core-h/yr. ACRES is sized to meet current demands and modest near-term growth with unused computational capacity being shared via the Open Science Grid (OSG) to benefit the broader scientific community. This new computational resource provides 9.8M core-h/year through 1120 cores, high-speed Infiniband interconnect, four NVIDIA Tesla V100 GPUs, and 40 TB of scratch storage.\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": "11776", "attributes": { "award_id": "1R21AI174080-01A1", "title": "Leveraging Pathogen-Host Networks to Identify Virus-specific and Estradiol-regulated Mechanisms during Respiratory Infection", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 6243, "first_name": "BROOKE ALLISON", "last_name": "Bozick", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-06-09", "end_date": "2025-05-31", "award_amount": 253510, "principal_investigator": { "id": 27652, "first_name": "Jason Edward", "last_name": "Shoemaker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 848, "ror": "", "name": "UNIVERSITY OF PITTSBURGH AT PITTSBURGH", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Respiratory viruses, such as influenza and SARS-CoV-2, interact with distinct molecular pathways in human cells to promote virus replication and alter immune activity. When considering patient cohort variability, morbidity and mortality are often higher for women than men for select influenza virus infections, exemplified in the 2009 H1N1 pandemic. Estradiol, a major sex hormone, has been shown to impact virus replication in a sex-specific manner. Yet much remains unknown as to the pathways different viruses engage to promote infection and alter immune activity or what pathways link estradiol activity to virus replication. This research program uses recently developed bioinformatics algorithms and NIAID-supported, published datasets in order to reveal new pathways and molecules involved in infection with influenza viruses and SAR-CoV-2 (Aim 1) and in infection in respiratory cells derived from women and treated with estradiol (Aim 2). More specifically, we will use two dynamic network perturbation algorithms, ProTINA and DeltaNeTS+, to create dynamic mathematical models of intracellular signaling in order to predict important disease modulators. Dynamic network perturbation analysis will be applied to virus-specific, virus-host interaction networks and host gene expression data induced by each virus. For Aim 2, we have identified gene expression data from influenza-infected nasal cells from female donors that are pretreated with estradiol. We will validate ProTINA’s and DeltaNeTS+ ability to identify host factors of virus replication using results from published siRNA- and CRISPR-based screens. After the validation, we will perform an in-depth characterization of the most significant proteins identified in order to generate new hypothesis on the host pathways that are involved in infection with different respiratory viruses or that interact with estradiol during infection.", "keywords": [ "2019-nCoV", "Address", "Adoption", "Affect", "Age Years", "Algorithms", "Automobile Driving", "Binding", "Bioinformatics", "COVID-19", "CRISPR screen", "Cells", "Cessation of life", "Code", "Communicable Diseases", "Communities", "Computer Analysis", "Data", "Data Set", "Development", "Disease", "Drug resistance", "Epidemiology", "Epithelial Cells", "Estradiol", "Female", "Future", "Gene Expression", "Genomics", "Goals", "Gonadal Steroid Hormones", "Hormones", "Hospitalization", "Human", "Immune", "Immune response", "Infection", "Infectious Diseases Research", "Inflammatory", "Inflammatory Response", "Influenza", "Influenza A Virus H1N1 Subtype", "Influenza A Virus H3N2 Subtype", "Integration Host Factors", "Knowledge", "Link", "Mediating", "Molecular", "Morbidity - disease rate", "Nasal Epithelium", "National Institute of Allergy and Infectious Disease", "Natural regeneration", "Nose", "Pathway interactions", "Patients", "Policies", "Process", "Proteins", "Publishing", "Research", "Respiratory Tract Infections", "Signal Transduction", "Small Interfering RNA", "Time", "Validation", "Viral Load result", "Virus", "Virus Replication", "Woman", "Work", "cohort", "drug candidate", "effectiveness evaluation", "experience", "human data", "in silico", "influenza infection", "influenzavirus", "mathematical model", "men", "molecular drug target", "mortality", "novel", "pandemic disease", "pathogen", "patient variability", "pressure", "programs", "respiratory", "respiratory infection virus", "respiratory virus", "response", "seasonal influenza", "secondary analysis", "sex", "therapeutic candidate", "therapeutic target", "therapy development", "virus host interaction", "whole genome", "young adult" ], "approved": true } }, { "type": "Grant", "id": "2304", "attributes": { "award_id": "2025954", "title": "LTER: Coastal Oligotrophic Ecosystem Research", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "LONG TERM ECOLOGICAL RESEARCH" ], "program_reference_codes": [], "program_officials": [ { "id": 6330, "first_name": "Paco", "last_name": "Moore", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-03-01", "end_date": "2025-02-28", "award_amount": 4750800, "principal_investigator": { "id": 6335, "first_name": "John", "last_name": "Kominoski", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 207, "ror": "https://ror.org/02gz6gg07", "name": "Florida International University", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 6331, "first_name": "James", "last_name": "Fourqurean", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 6332, "first_name": "Evelyn E", "last_name": "Gaiser", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 6333, "first_name": "Jennifer S", "last_name": "Rehage", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 6334, "first_name": "Kevin", "last_name": "Grove", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 207, "ror": "https://ror.org/02gz6gg07", "name": "Florida International University", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "Coastal ecosystems like the Florida Everglades provide many benefits and services to society including protection from storms, habitat and food for important fisheries, support of tourism and local economies, filtration of fresh water, and burial and storage of carbon that offsets greenhouse gas emissions. The Florida Coastal Everglades Long Term Ecological Research (FCE LTER) program addresses how and why coastal ecosystems and their services are changing. Like many coastal ecosystems, the Florida Everglades has been threatened by diversion of fresh water to support urban and agricultural expansion. At the same time, sea-level rise has caused saltwater intrusion of coastal ecosystems which stresses freshwater species, causes elevation loss, and contaminates municipal water resources. However, restoration of seasonal pulses of fresh water may counteract these threats. Researchers in the FCE LTER are continuing long-term studies and experiments to understand how changes in freshwater supply, sea-level rise, and disturbances like tropical storms interact to influence ecosystems and their services. The science team is guided by a diversity and inclusion plan to attract diverse scientists at all career stages. The team includes resource managers – who use discoveries and knowledge from the FCE LTER to guide effective freshwater restoration – and an active community of academic and agency scientists, teachers and other educators, graduate, undergraduate, and high school students. The project has a robust education and outreach program that engages the research team with the general public to advance science discoveries and protection of coastal ecosystems.\n\nThe FCE LTER research program addresses how increased pulses of fresh and marine water will influence coastal ecosystem dynamics through: (i) continued long-term assessment of changes in biogeochemistry, primary production, organic matter, and trophic dynamics in ecosystems along freshwater-to-marine gradients with a focus on how these affect accumulation of carbon and related elevation change, (ii) meteorological studies that evaluate how the climate drivers of hydrologic presses and pulses are changing, (iii) social-ecological studies of how governance of freshwater restoration reflects the changing values of ecosystem services, and (iv) use of high-resolution remote sensing, coupled with models to forecast landscape-scale changes. A new experimental manipulation will determine drivers and mechanisms of resilience to saltwater intrusion. Data syntheses integrate month-to-annual and inter-annual data into models of water, nutrients, carbon, and species patterns and interactions throughout the Everglades landscape to compare how ecosystems with different productivities and carbon stores respond (maintain, increase, or decline) to short- (pulses) and long-term changes (presses) in hydrologic connectivity. Synthesis efforts will use data from national and international research networks aimed at understanding how chronic presses and increasing pulses determine ecosystem trajectories, addressing one of the most pressing challenges in contemporary ecology.\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": "10240", "attributes": { "award_id": "1R44AI170392-01", "title": "SARS-CoV-2 vaccines based on RBDs with engineered glycosylation sites", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Allergy and Infectious Diseases (NIAID)" ], "program_reference_codes": [], "program_officials": [ { "id": 6908, "first_name": "JENNIFER L.", "last_name": "Gordon", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-08-08", "end_date": "2023-01-31", "award_amount": 300000, "principal_investigator": { "id": 26186, "first_name": "MICHAEL DAVID", "last_name": "ALPERT", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 21748, "first_name": "Michael R.", "last_name": "Farzan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1472, "ror": "", "name": "SCRIPPS FLORIDA", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] } ], "awardee_organization": { "id": 1900, "ror": "", "name": "EMMUNE, INC", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true }, "abstract": "We are developing vaccine antigens for SARS-CoV-2 that focus the antibody response onto neutralizing epitopes in the receptor binding domain (RBD) of the viral Spike (S) protein. Efficient expression of the RBD in technically-demanding formats, e.g., on a self-assembling multimer scaffold, was achieved by engineering N-linked glycosylation sites into the RBD. The engineered N-linked glycosylation sites occlude hydrophobic patches that form inter-subunit interfaces in the native S protein, but that interfere with expression of the RBD in other contexts. The glycans also help to focus the immune response away from off-target faces of the RBD, and onto the targets for potent neutralizing antibody responses. We will extend the potential for this strategy to focus the neutralizing antibody response further, onto conserved epitopes in the RBD. This overall strategy maximizes the focusing of neutralizing antibody responses onto epitopes that are conserved among variants of SARS-CoV-2. In addition, we will compare, and possibly combine, immunofocusing with approaches designed to elicit variant-specific neutralizing antibodies. We will develop and utilize two distinct platforms for expressing these RBD antigens: mRNA delivered by lipid nanoparticles (LNPs), and a novel scaffold for efficiently displaying multimers of RBD antigens as recombinant protein. LNP-mRNA vaccines have the advantage of being a validated approach for vaccinating against SARS-CoV-2, whereas the novel multimer scaffold has the advantage of being heat stable after lyophilization. The antigens generated by this project exploit three layers of immunofocusing to elicit or boost antibody responses that neutralize diverse variants of SARS-CoV-2.", "keywords": [ "2019-nCoV", "Amino Acids", "Antibody Response", "Antibody titer measurement", "Antigens", "Baculovirus Expression System", "Baculoviruses", "COVID-19 vaccination", "COVID-19 vaccine", "Cytoplasmic Protein", "Cytoplasmic Tail", "Data", "Development", "Dose", "Engineering", "Epitopes", "Face", "Family", "Ferritin", "Freeze Drying", "Grant", "Helicobacter pylori", "Human", "Hydrophobicity", "Immune response", "Infection", "Length", "Link", "Mass Spectrum Analysis", "Mesocricetus auratus", "Messenger RNA", "Mosaicism", "Mus", "Pathway interactions", "Phase", "Polysaccharides", "Population", "Production", "Property", "Prophylactic treatment", "Proteins", "Protocols documentation", "Protomer", "RNA vaccine", "Recombinant Proteins", "SARS-CoV-2 antigen", "SARS-CoV-2 spike protein", "SARS-CoV-2 variant", "Saline", "Site", "Subunit Vaccines", "System", "Testing", "Transmembrane Domain", "Vaccine Antigen", "Vaccines", "Variant", "Viral", "base", "cost", "design", "experimental study", "glycosylation", "head-to-head comparison", "immunogenic", "immunogenicity", "improved", "lipid nanoparticle", "neutralizing antibody", "novel", "receptor binding", "receptor expression", "reconstitution", "scaffold", "thermophilic organism", "thermostability", "vaccine development", "vaccine efficacy", "variants of concern" ], "approved": true } }, { "type": "Grant", "id": "7168", "attributes": { "award_id": "3R01DK115728-03S1", "title": "Structure-based Bioengineering of Wnt Surrogates for Intestinal Stem Cell Biology and Therapy", "funder": { "id": 4, "ror": "https://ror.org/01cwqze88", "name": "National Institutes of Health", "approved": true }, "funder_divisions": [ "National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)" ], "program_reference_codes": [], "program_officials": [ { "id": 11708, "first_name": "Patricia", "last_name": "Greenwel", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2018-08-15", "end_date": "2023-06-30", "award_amount": 553964, "principal_investigator": { "id": 22963, "first_name": "Kenan Christopher", "last_name": "GARCIA", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 266, "ror": "https://ror.org/00f54p054", "name": "Stanford University", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 6819, "first_name": "CALVIN J", "last_name": "KUO", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 266, "ror": "https://ror.org/00f54p054", "name": "Stanford University", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] } ], "awardee_organization": { "id": 266, "ror": "https://ror.org/00f54p054", "name": "Stanford University", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has threatened global health. The severity of disease and rising number of deaths from SARS-CoV-2 have raised an urgent need for effective therapies. Besides respiratory symptoms, 20-50% of patients exhibit gastrointestinal symptoms such as diarrhea and emesis. In addition, clinical evidence shows that viral RNA can be found in rectal swabs, indicating that the intestine may be a critical target of SARS-CoV-2 infection. In this proposal, we engineer novel high-affinity blocking agents for known entry receptors of SARS-CoV-2 to prevent infection of human intestinal cells and pursue a longer-term goal of structure-based discovery of novel receptor targets. Aim 1 designs blocking agents that target the known interaction of SARS-CoV-2 S protein with its primary entry receptor ACE2 (angiotensin-converting enzyme 2), as well as with a novel co-receptor, CD147 (accessory protein for monocarboxylate transporters), both of which are expressed in human small intestinal and colon epithelial cells. In Aim 1 we will engineer an ACE2/CD147 bi-specific agent that can simultaneously target both SARS-CoV-2 S protein receptors to improve the efficiency and specificity of viral blockade. We utilize in vitro protein evolution by yeast cell surface display to generate high-affinity ACE2 and CD147 ECDs with improved affinity for SARS-CoV-2 S protein versus the wild- type ECDs These will be combined into a single bispecific agent containing both ACE2 and CD147 affinity-matured ECDs and assayed in human intestinal organoids. In particular, we deploy intestinal organoids with a “flipped polarity” where the apical ACE2-expressing aspect faces outwards towards the surrounding ECM/media instead of towards the interior lumen to better model physiologic viral infection. In Aim 2, we will screen a CRISPRa activating library for additional human SARS-CoV-2 secretome targets. The SARS-CoV-2 secretome, i.e. virus-encoded secreted or surface-exposed transmembrane proteins, also facilitates infection of host cells and provides novel targets for SARS- CoV-2 therapeutics. This proposal leverages expertise of Chris Garcia (Multi-PI of the parental R01) in protein engineering, immunotherapeutics, and structural biology with Calvin Kuo (Multi-PI of the parental R01) expertise in organoid generation and disease modelling to design targeted therapeutics for SARS-CoV-2. We also utilize collaboration from the Manuel Amieva and Catherine Blish groups in organoid apical-basal polarity inversion and BSL3 SARS-CoV-2 infection, respectively.", "keywords": [ "2019-nCoV", "Affinity", "Apical", "Biological Assay", "Biomedical Engineering", "COVID-19", "COVID-19 pandemic", "Cell Therapy", "Cell surface", "Cells", "Cessation of life", "Clinical", "Collaborations", "Colon", "Diarrhea", "Disease", "Disease model", "Engineering", "Epithelial Cells", "Evolution", "Exhibits", "Extracellular Matrix", "Face", "Generations", "Goals", "Human", "Immunotherapeutic agent", "In Vitro", "Infection", "Infection prevention", "Integral Membrane Protein", "Intestines", "Libraries", "Organoids", "Patients", "Peptidyl-Dipeptidase A", "Protein Engineering", "Proteins", "Respiratory Signs and Symptoms", "SARS coronavirus", "Severity of illness", "Small Intestines", "Specificity", "Structure", "Surface", "Swab", "Therapeutic", "Viral", "Virus", "Virus Diseases", "Vomiting", "Yeasts", "base", "cellular engineering", "design", "effective therapy", "gastrointestinal symptom", "global health", "improved", "novel", "pandemic disease", "physiologic model", "prevent", "receptor", "rectal", "respiratory", "stem cell biology", "structural biology", "targeted agent", "targeted treatment", "viral RNA" ], "approved": true } }, { "type": "Grant", "id": "12800", "attributes": { "award_id": "2302813", "title": "Collaborative Research: Adaptable Game-based, Interactive Learning Environments for STEM Education (AGILE STEM)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Cyberlearn & Future Learn Tech" ], "program_reference_codes": [], "program_officials": [ { "id": 1414, "first_name": "Soo-Siang", "last_name": "Lim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-09-15", "end_date": null, "award_amount": 350000, "principal_investigator": { "id": 28719, "first_name": "Daniell", "last_name": "DiFrancesca", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 28719, "first_name": "Daniell", "last_name": "DiFrancesca", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 219, "ror": "", "name": "Pennsylvania State Univ University Park", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Learners of all ages are expected to be prepared to interact with emerging and technology-driven work environments. In addition, the growing reliance on online learning and its unprecedented and unexpected acceleration due to the COVID-19 pandemic are expected to change the education landscape forever. Thus, there is a need to grow the development of digital platforms for teaching and learning. Emerging technologies such as machine learning and high fidelity simulated environments have the potential to create customized and adaptable learning environments to support STEM learning outcomes. This project serves the national interest by advancing the knowledge about designing and creating adaptable game-based, interactive learning environments for STEM. The inclusion of underrepresented minority and female learners in the design stages of these learning environments, their portability, as well as the capability of these environments to be customized and adaptive have the potential to enhance education equality, engagement, and learning outcomes, and broaden their usability to several STEM domains. Moreover, the narratives and simulation models are inspired by real-world systems. Therefore, the learning environments are expected to enhance the learner’s understanding of complex system concepts that are challenging to understand using traditional teaching approaches and will help build the much-needed skills for the U.S. future STEM workforce. The proposed emerging technologies do not necessarily need access to specialized equipment, which eliminates barriers to scalability and border implementation and use. <br/><br/>The primary goals of this project are to automatically customize and adapt three-dimensional (3D) simulated game-based learning environments to improve engagement, and provide a deeper understanding of their design, development, and deployment, impact on learning and self-regulated learning (SRL) skills, and knowledge transferability from the learning environments to real-life applications. The project addresses the lack of scientific evidence and/or work in the following thrust areas: 1) the potential of reducing the barriers to content generation of 3D simulated game-based learning environments using emerging and advanced machine-learning methods; 2) creating customized content and adaptive 3D simulated game-based learning environments that improve and maintain learners motivation and engagement, enhance learning via instructional assistive content scaffolding, and increase knowledge transferability from game to real-life applications; 3) assessing the effectiveness of the learning environments for all learner groups in online and residential settings; and 4) exploring how learner decision-making and behavior data in the simulated game-based learning environments, and eye-tracking, facial expressions, bio-signals, and usage data, enhance knowledge about the relationships between decision-making/usage and SRL skills development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "3328", "attributes": { "award_id": "1811163", "title": "Advancing the Design of Visualizations for Informal Science Engagement", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Education and Human Resources (EHR)", "AISL" ], "program_reference_codes": [], "program_officials": [ { "id": 10551, "first_name": "Chia", "last_name": "Shen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2018-10-01", "end_date": "2019-12-31", "award_amount": 249677, "principal_investigator": { "id": 10553, "first_name": "Jennifer", "last_name": "Frazier", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1082, "ror": "https://ror.org/0037yf233", "name": "Exploratorium", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 10552, "first_name": "Joyce", "last_name": "Ma", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 1082, "ror": "https://ror.org/0037yf233", "name": "Exploratorium", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants. This project is a two-day conference, along with pre- and post-conference activities, with the goal of furthering the informal science learning field's review of the research and development that has been conducted on data visualizations that have been used to help the public better understand and become more engaged in science. The project will address an urgent need in informal science education, providing a critical first step towards a synthesis of research and technology development in visualization and, thus, to inform and accelerate work in the field in this significant and rapidly changing domain.\n\nThe project will start with a Delphi study by the project evaluator prior to the conference to provide an Emerging Field Assessment on data visualization work to date. Then, a two-day conference at the Exploratorium in San Francisco and related activities will bring together AISL-funded PIs, computer scientists, cognitive scientists, designers, and technology developers to (a) synthesize work to date, (b) bring in relevant research from fields outside of informal learning, and (c) identify remaining knowledge gaps for further research and development. The project team will also develop a website with videos of all presentations, conference documentation, resources, and links to social media communities; and a post-conference publication mapping the state of the field, key findings, and promising technologies. \n\nThe initiative also has a goal to broaden participation, as the attendees will include a diverse cadre of professionals in the field who contribute to data visualization work.\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": "4096", "attributes": { "award_id": "1607069", "title": "2016 Cellular & Molecular Fungal Biology GRC, Plymouth, New Hampshire, June 19-24, 2016", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Symbiosis Infection & Immunity" ], "program_reference_codes": [], "program_officials": [ { "id": 13758, "first_name": "Michael", "last_name": "Mishkind", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2016-07-01", "end_date": "2017-06-30", "award_amount": 15000, "principal_investigator": { "id": 13759, "first_name": "Amy", "last_name": "Gladfelter", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 226, "ror": "https://ror.org/05rad4t93", "name": "Gordon Research Conferences", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 226, "ror": "https://ror.org/05rad4t93", "name": "Gordon Research Conferences", "address": "", "city": "", "state": "RI", "zip": "", "country": "United States", "approved": true }, "abstract": "This project will facilitate the attendance and participation of early career scientists in the Gordon Research Conference on Cellular and Molecular Fungal Biology to be held at the Holderness School, June 19-24, 2016. The goal of the conference is to disseminate information about fungal biology among an interdisciplinary group of researchers, and to increase our collective understanding of basic fungal biology and its application to socially important problems. Fungi are essential parts of the terrestrial nutrient cycle, play a central role in the development of biofuels, and produce many critically important chemicals. These diverse applications of fungi require the interdisciplinary acquisition and application of fundamental fungal biology. This project will support the convergence and exchange of new findings amongst an interdisciplinary group of scientists dedicated to the study of fungi. \n\nThe intellectual merit of the project is rooted in the meeting's highly interdisciplinary and interactive format. The meeting will feature topics that integrate multiple time and space scales for different questions in fungal biology to promote interactions amongst researchers with diverse perspectives within the community. There is a specific emphasis on integrating mathematical modeling and biophysics as a new addition to this meeting and an entire session is dedicated to the interface of fungal biology with the physical sciences. The meeting enables cross-fertilization of ideas, from cell biology to evolution, that occurs in and outside of the sessions and especially between junior and senior scientists. Young investigators emphasize from previous meetings how interactive the conference is and how responsive it is to the presentation of their work.\n\nThis conference has broad impacts on training and is dedicated to extending the research community by emphasizing women and members of underrepresented groups in inviting speakers. The current invited speakers are approximately 50% women, including several Latinas. The small size of the meeting and the emphasis on discussion (40% of meeting time is dedicated to discussions) encourages active participation. Poster sessions are featured without competing events to focus attention on the most junior scientists, who often have the newest data. The GRC on Cell and Molecular Fungal Biology also is dedicated to research that applies basic knowledge to socially important questions involving filamentous fungi, particularly mutualisms with plants (mycorrhizae), parasitism with plants (plant pathology) and animals (animal pathology), and industrial mycology (enzyme production). The interactions among researchers focused on both basic and socially important research speeds research aimed at solving societal problems caused by or that can be improved by fungi.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "5120", "attributes": { "award_id": "1010204", "title": "CNH/EID: The Vector Mosquito Aedes aegypti at the Margins: Sensitivity of a Coupled Natural and Human System to Climate Change", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "DYN COUPLED NATURAL-HUMAN" ], "program_reference_codes": [], "program_officials": [ { "id": 18242, "first_name": "Sarah", "last_name": "Ruth", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2010-10-01", "end_date": "2014-09-30", "award_amount": 1235153, "principal_investigator": { "id": 18246, "first_name": "Andrew", "last_name": "Monaghan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 275, "ror": "", "name": "University Corporation For Atmospheric Res", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [ { "id": 18243, "first_name": "Mary H", "last_name": "Hayden", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 18244, "first_name": "Lars M", "last_name": "Eisen", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 18245, "first_name": "Luca Delle", "last_name": "Monache", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 275, "ror": "", "name": "University Corporation For Atmospheric Res", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "This project will explore the ecology of Aedes (Ae.) aegypti, the mosquito that transmits dengue, yellow fever and chikungunya. We hypothesize that the combined effects of climate variability and changes made by humans to their local environment can influence key aspects of both mosquito ecology and human behavior. Studying this system as a whole will improve our ability to predict risks of mosquito vector and dengue virus exposure and the possible impacts of future climate change. \n\nDengue viruses circulate between mosquitoes and humans, causing an estimated 100 million human dengue infections annually. In the last decade, the Americas have experienced a dramatic increase in severe cases (dengue hemorrhagic fever), with devastating public health consequences. As neither vaccines nor therapeutics are yet available, mosquito control is the main option for preventing and controlling dengue outbreaks. Efforts in this area have been hindered by a poor understanding of the dengue virus transmission system at the interface between its natural and human components. Of particular concern is the potential for dengue fever to expand into areas that are presently outside transmission zones but may become vulnerable under scenarios of future climate change. For example, this potential expansion poses a risk to the ~19 million people in and near Mexico City, a high altitude \"island\" currently free of dengue but surrounded by dengue virus transmission at lower altitudes. \n\nSpecific aims of the project are to: (1) determine how weather/climate factors are related to the presence and abundance of disease-carrying mosquitoes, especially by serving as barriers to mosquitoes becoming established in an area; (2) use these results in high-resolution atmospheric models to develop a predictive model for future mosquito range expansion; (3) determine which aspects of human behavior and attributes of man-made environments are most closely related to Ae. aegypti presence and abundance; (4) employ state-of-the-science data assimilation procedures to validate, refine, and define uncertainty in this modeling framework. Key aspects of this coupled natural and human system will be studied along an altitudinal transect in Mexico, ranging from coastal, low-elevation environments with well established vector mosquito populations and intense dengue virus transmission to high-elevation, mountainous areas which currently are free of the mosquito vector and local virus transmission. The team of experts from Mexico and the United States includes climatologists, vector ecologists, modelers and medical anthropologists.\n\nThe project will contribute essential insights into the ongoing debate about climate change and infectious disease relationships, extending beyond the explicit vector ecology and geographic boundaries of this study. The work will provide quantitative knowledge that can be used to develop novel strategies to control Ae. aegypti in the face of future threats to system resilience. Further, it will provide training for a postdoctoral fellow in climate modeling and spatial risk modeling at both Colorado State University and the National Center for Atmospheric Research and involvement and in situ training of university and secondary school students in data collection. Through \"participatory epidemiology\", local community members will learn how to use environmental observation and data collection as a means of community empowerment.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "11264", "attributes": { "award_id": "2328095", "title": "CDS&E: Simulation- and Data-driven Peptide Antibody Design Targeting RBD and non-RBD Epitopes of SARS-CoV-2 Spike Protein", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Engineering (ENG)", "Cellular & Biochem Engineering" ], "program_reference_codes": [], "program_officials": [ { "id": 4079, "first_name": "Steven", "last_name": "Peretti", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-10-01", "end_date": "2025-09-30", "award_amount": 549351, "principal_investigator": { "id": 25373, "first_name": "Baofu", "last_name": "Qiao", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 630, "ror": "", "name": "CUNY Baruch College", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Drugs interact with proteins to disrupt bacterial and viral infections. Effective drugs are usually discovered rather than designed. Antibodies are protein complexes generated by the immune system to bind to and inactivate viruses. Peptides are short strings of amino acids that are being designed to mimic the protein binding activity of antibodies. Many aspects of protein-protein and protein-peptide interactions are not clearly understood. This project will apply an artificial intelligence approach to understand those interactions. The SARS-CoV-2 spike protein will be the model system for study. The resulting model for therapeutic peptide design will be provided to the research community on a variety of software platforms. The project will also support outreach to K-12 students regarding the SARS-CoV-2 virus and viral infections. \n\nThe overall objective is to develop a hybrid machine learning-simulation (MLSim) platform that allows us to better understand the molecular interaction between peptide drugs and viral proteins. The model viral protein system will be the SARS-CoV-2 spike proteins at both the receptor-binding domain (RBD) and the non-RBD. Transfer learning techniques for existing data models for protein-peptide interactions will be implemented. Online learning techniques will allow for the timely update of the predictive models with newly available data. The multiscale simulation component aids the machine learning part by supplying high-fidelity input data and cross-validating the predictions These efforts should result in molecular-level insight into viral protein-antibody interactions. There are two key outcomes anticipated from this project. First, a simulation- and data-enabled platform that integrates a high-throughput, customizable machine learning pipeline for fast screening and filtering peptide candidates, with high-fidelity all-atom explicit-solvent molecular dynamics simulation and free energy calculations. The second is fundamental insight into viral protein-peptide interactions and how those influence the design of neutralizing peptides.\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": 5, "pages": 1424, "count": 14236 } } }