COVID-19 Seed Grant Award Winners
Below are the winners of the OVPR and IEDM COVID-19 Seed Grant Program. The Office of the Vice President for Research and the Institute for Engineering-Driven Medicine joined together to provide funding for this special initiative seed grant program in the Spring 2020 semester. Faculty were asked to submit a brief proposal that included the specific aims, research methods, potential impact, and timeline of their projects as well as plans for developing highly competitive proposals for extramural funding. The call for applications, which was open for less than three weeks, received 63 submissions from Principal Investigators in the College of Arts and Sciences, College of Business, College of Engineering and Applied Sciences, School of Marine and Atmospheric Sciences, School of Medicine, and School of Social Welfare. The following projects were selected for funding with an award start date of May 22, 2020.
Nancy Reich, Janet Hearing, Patrick Hearing, and Hwan Kim, Department of Microbiology and Immunology: Interferon-lambda as a Broad-spectrum Antiviral Drug for COVID-19
Carlos Simmerling, Laufer Center for Physical and Quantitative Biology and Evangelos Coutsias, Department of Applied Mathematics and Statistics: Multiscale molecular simulations to develop inhibitors of the SARS-CoV-2 coronavirus membrane fusion protein
Matthew Lerner, Department of Psychology and Jennifer Keluskar, Department of Psychiatry and Behavorial Health: Psychosocial Impact of COVID-19-Induced Social Isolation (PICSI) on Youth with Autism Spectrum Disorder: A Longitudinal Study
Peter Tonge, Department of Chemistry, Dima Kozakov, Department of Applied Mathematics and Statistics, and David Thanassi, Department of Microbiology and Immunology: Targeted degradation of the SARS-CoV-2 Mpro protease as a novel therapy for treating COVID-19 infection
Shobana Shankar, Department of History: Adapting Social Behaviors during the Ebola and COVID-19 Emergencies: A Household-Level Analysis from the West African Region
Markus Seeliger, Department of Pharmacological Sciences, and David Liu, Department of Chemistry and Chemical Biology at Harvard University: Structure-based Development of Novel Cyclophilin Inhibitors for Studying and Blocking Viral Replication of Human Coronaviruses
Erich Mackow, Department of Microbiology and Immunology: Therapeutic Targeting SARS-CoV-2 Induced ACE2/Bradykinin Pulmonary Edema
Brady Nelson, Lauren Richmond, and Jessica Schleider, Department of Psychology: Effect of The Coronavirus (COVID-19) Pandemic on the Academic, Career, Mental, Psychosocial, and Physical Functioning of the SBU Community
Liliana Davalos, Department of Ecology and Evolution, and Jaymie Meliker, Department of Family, Population and Preventative Medicine: Inter-Species Modeling for Spillback/Spillover Avoidance
Heidi Preis and Marci Lobel, Department of Psychology, and Brittain Mahaffey, Department of Psychiatry and Behavorial Health: The COPE Study (COVID-19 Pregnancy Experiences)-- Experiences of Women Pregnant During the COVID-19 Pandemic and Associated Health Impacts
Nicholas Carpino and Erich Mackow, Department of Microbiology and Immunology: Investigating the role of the Sts enzymes in coronavirus-induced hyper-inflammation: establishing a foundation for immunomodulatory-based therapeutic intervention.
Chao Chen, Prateek Prasanna, and Janos Hajagos, Department of Biomedical Informatics: COVID-19 Prognosis with Interpretable Deep Learning Methods
Wadie Bahou and Dmitri Gnatenko, Department of Medicine, Cecilia Avila, Department of Obstetrics, Gynecology and Reproductive Medicine, and Wei Zhu, Department of Applied Mathematics and Statistics: Biomarker Identification for COVID-19 Risk Stratification in Maternal Fetal Heath
Prateek Prasanna, Department of Biomedical Informatics, Dimitris Samaras, Department of Computer Science, and Elaine Gould, Department of Radiology: The Virus is in the Details: Discovering Subtle COVID-19 Visual Features on Chest X-rays Using Machine Learning
Arie Kaufman, Department of Computer Science and Marlene Zawin, Department of Radiology: Use of Chest CT and Machine Learning for Diagnosis and Management of COVID-19 Patients
Miguel Garcia-Diaz, Department of Pharmacological Sciences and Robert Rizzo, Department of Applied Mathematics and Statistics: Pharmacological inhibition of SARS-CoV-2 replication
Peng Zhang and Yuefan Deng, Department of Applied Mathematics and Statistics, Miriam Rafailovich, Department of Materials Science and Chemical Engineering and Marcia Simon, Department of Oral Biology and Pathology: Multiscale Modeling of Binding SARS-CoV-2 to Various Substrates