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Faculty
Sarah Groves
Assistant Professor of Data Science
School of Data Science
Email: xpz5km@virginia.edu
Additional Contact Information
Website: smgroves.github.io/
Pronouns: She/her
Sarah Groves is a biomedical network scientist with a passion for project-based and analogy-driven learning. Her research focuses on building and interpreting data-driven network models that underlie cancer development, dynamics, and treatment response. After a B.S. in Physics and Mathematics from the College of William & Mary, she earned a Ph.D. at Vanderbilt University in Cancer Systems Biology in 2022, combining her quantitative background with an interest in solving biomedical problems.
As a systems thinker, Groves built computational tools to interrogate cell type switching in an extremely aggressive form of lung cancer. She then moved to Charlottesville for a postdoctoral position in the Department of Biomedical Engineering (2023-2026), where she built mathematical models to understand how proteins move and interact, or fail to do so, during mitosis in cancer.
Her interests include cancer genomics, gene regulatory network inference, civic tech, and developing innovative teaching methods.
Education
- Ph.D. in Cancer Systems Biology, Vanderbilt University
- B.S. in Physics and Mathematics, College of William & Mary
Data Science Domains
Analytics; Design
Areas of Practice
Artificial Intelligence and Machine Learning; Biomedical, Health, and Life Sciences
Selected Publications
- Groves, S.M., Clark, A, Wintruba, K., Saucerman, J.J. (2026) Integration of Social and Ethical AI Topics into a Computational Engineering Course Increases Engagement Without Loss of Learning. ASEE 2026 Conference. Accepted.
- Groves, S.M., Lu, M.J., Alvarez-Yela, A.C., Gerardo-Ramírez, M.G., Stukenberg, P.T., Lowengrub, J.S., Janes, K.A. (2025). Cahn-Hilliard dynamical models for condensed biomolecular systems. BioRxiv. doi: 10.1101/2025.07.13.664571. Accepted at PLOS Comp Bio.
- Groves, S.M., Quaranta, V. (2023). Review Article: Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics. Front. Netw. Physiol. doi: 10.3389/fnetp.2023.1225736
- Groves, S.M., Panchy, N., Tyson, D.R., Harris, L.A., Quaranta, V., and Hong, T. (2023). Involvement of Epithelial–Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity. Cancers 15, 1477.
- Groves, S.M., Ildefonso, G.V., McAtee, C.O., Ozawa, P.M.M., Ireland, A.S., Stauffer, P.E., Wasdin, P.T., Huang, X., Qiao, Y., Lim, J.S., Bader, J., Liu, Q., Simmons, A.J., Lau, K.S., Iams, W.T., Hardin, D.P., Saff, E.B., Holmes, W.R., Tyson, D.R., Lovly, C.M., Rathmell, J.C., Marth, G., Sage, J., Oliver, T.G., Weaver, A.M., Quaranta, V. (2022). Archetype tasks link intratumoral heterogeneity to plasticity and cancer hallmarks in small cell lung cancer. Cell Systems, doi: 10.1016/j.cels.2022.07.006
- Wooten, D, Groves, S.M., Tyson, D.R., Liu, Q., Lim, J.S., Albert, R., Lopez, C.F., Sage, J., and Quaranta, V. (2019). Systems-level network modeling of Small Cell Lung Cancer subtypes identifies master regulators and destabilizers. PLOS Computational Biology 15, e1007343.