Erin Craig, PhD

• PhD, Biomedical Data Science, Stanford University, 2025
• MS, Data Science, New College of Florida, 2017
• BA, Mathematics, New College of Florida, 2009

My work focuses on improving healthcare through:

• developing statistical methods with emphasis on predictive modeling and interpretability,
• creating well-documented, user-friendly software, and
• teaching statistics for biomedical applications in a friendly, accessible way.

I typically work in the areas of cancer, immunology, and their intersection.

I am particularly interested in identifying opportunities for AI and statistics to learn from one another. For example, how can statistical models make use of AI-derived embeddings, and can we interpret them? Or, how can we augment traditional statistical modeling methods using ideas inspired by AI modeling approaches?

Craig, E., Keyes, T. J., Sarno, J., D’Silva, J. P., Domizi, P., Zaslavsky, M., ... & Davis, K. L. (2025). Annotation-free discovery of disease-relevant cells in single-cell datasets. Science Advances, 11(35), eadv5019.

Craig, E., Pilanci, M., Le Menestrel, T., Narasimhan, B., Rivas, M. A., Gullaksen, S. E., ... & Tibshirani, R. (2025). Pretraining and the lasso. Journal of the Royal Statistical Society Series B: Statistical Methodology, qkaf050.

Zaslavsky, M. E., Craig, E., Michuda, J. K., Sehgal, N., Ram-Mohan, N., Lee, J. Y., ... & Boyd, S. D. (2025). Disease diagnostics using machine learning of B cell and T cell receptor sequences. Science, 387(6736), eadp2407.