Gautam S. Sabnis, PhD

Hi! Welcome to my website!

I apply statistical science to tackle research questions in the biological sciences. My doctoral and postdoctoral training have given me a solid foundation in high-dimensional statistics, probabilistic modeling, and statistical machine learning, empowering me to uncover meaningful biological insights from large, multimodal datasets. During my PhD, I focused on covariance estimation within high-dimensional latent generative models, developing a scalable probabilistic factor modeling framework that leverages distributed computing. In my postdoctoral work, I developed a quasi-Bayesian framework for variable selection in high-dimensional instrumental multivariable regression models, with broad applications in causal inference and statistical genetics. At The Jackson Laboratory (JAX) in Bar Harbor, Maine, I apply statistical data science and machine learning to address complex biological questions in behavioral genetics, aging, and neuropsychiatric disorders.

Outside of work, I love exploring the discographies of musicians and the filmographies of directors, and enjoy playing soccer, chess, and poker.