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Academy of Data Science Discovery Fund

The Academy of Data Science Discovery Fund was established in 2021 to support pilot studies, data collection, or data analysis that will enable eventual application for external interdisciplinary research funding. The ADSDF provides up to $10,000 in funding to a single investigator and up to $20,000 for multiple investigators.

Originally earmarked for projects generated by the College of Science, the Academy of Data Science Discovery Fund is open to all Virginia Tech faculty members, including collegiate and research faculty.

2024-25 Awards

"Bayesian Approaches to Estimating Fluid Domains"
PI: Justin Krometis, Virginia Tech National Security Institute/Department of Mathematics
Co-PI: Jeff Borggaard, Department of Mathematics

"Data-Enabled Knowledge Discovery in Rechargeable Batteries"
PI: Hongxiao Zhu, Department of Statistics
Co-PI: Feng Lin, Department of Chemistry

"Enhancing Open Science Data Sharing through the Synthesis of Qualitative Datasets"
PI: Ivan Hernandez, Department of Psychology
Co-PI: Louis Hickman, Department of Psychology

"Instreyed: Advancing Fine-grained Data-limited Visual Recognition for Smart Surgical Tray Management"
PI: Chris Thomas, Department of Computer Science, College of Engineering
Co-PIs: Jacob Gillen, Virginia Tech Carilion School of Medicine; Chris Arena, Department of Biomedical Engineering and Mechanics, College of Engineering

"Rapid, In-Field Identification of Resistant Trees Using NIR Spectroscopy and Machine Learning"
PI: Carrie Fearer, Department of Forest Resources and Environmental Conservation, College of Natural Resources and Environment
Co-PIs: P. Corey Green, Department of Forest Resources and Environmental Conservation, College of Natural Resources and Environment; David Carter, Department of Forest Resources and Environmental Conservation, College of Natural Resources and Environment; W. Mark Ford, Department of Fish and Wildlife Conservation, College of Natural Resources and Environment

"Using Large Language Models and Generative AI to Scale Qualitative Data Analysis"
PI: Andrew Katz, Department of Engineering Education, College of Engineering

2023-24 Awards

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"A Data Science Approach to Data Protection"
PI: Jason LeGrow, Department of Mathematics
Co-PI: Gretchen Matthews, Department of Mathematics, and director of the Commonwealth Cyber Initiative in Southwest Virginia

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"Reverse Metabolomics to Map Host-Microbe Co-metabolism of Phytonutrients"
PI: Emily Gentry, Department of Chemistry

2022-23 Awards

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"Adapting Machine-Learning Algorithms to Develop ODE-based Systems Biology Models"
PI: Anand Banerjee, Academy of Integrated Science (systems biology)
Co-PI: Pavel Kraikivski, Academy of Integrated Science (systems biology)

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"BESI: Behavioral and Environmental Sensing and Intervention for Dementia Caregiver Empowerment"
PI: Alexandra Hanlon, Department of Statistics, and director of the Virginia Tech Center for Biostatistics and Health Data Science
Co-PI: Azziza Bankole, Virginia Tech Carilion School of Medicine

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"Inference and Uncertainty Quantification in Large-Scale Models of Earth's Mantle Convection and Plate Tectonics"
PI: Johan Rudi, Department of Mathematics

2021-22 Awards

"Data Science Enabled Polymer Modeling"
PI: Shenfeng Cheng, Department of Physics
Co-PIs: Greg Liu, Department of Chemistry; Xi Chen, Department of Industrial and Systems Engineering, College of Engineering

"Recovery from Opioid Use Disorder: Subgroup Identification Using Bayesian Dynamic Factor Models"
PI: Allison Tegge, Department of Statistics
Co-PIs: Marco Ferreira, Department of Statistics; Warren Bickel, Department of Psychology

"Transferrable Graph Encoding for Human Dynamic with Application in COVID-19 Prediction"
PI: Meimei Liu, Department of Statistics