Saurabh Bhandari

I am a postdoctoral scholar at the University of Chicago, working with Professors Yuan Ji and Brian Chiu. In this position, I conduct methodological research in Bayesian machine learning with applications to cancer clinical trials and observational studies. I completed my Ph.D. in Statistics at the University of Florida under the supervision of Prof. Michael J. Daniels.

Research Interests

My methodological research interests lie at the intersection of Bayesian statistics, causal inference, and machine learning. My work spans applications in epidemiology, marketing, and oncology.

Recent Publications/Preprints

• Aug 2026: Bhandari, S., Kar, W., Daniels, M.J., Karmakar, B. Causal mediation analysis for longitudinal data in the presence of treatment non-compliance and multiple mediators. ArXiv Link

• May 2026: Bhandari, S., Bhatti, P., Chiu, B., Ji, Y. Semi-parametric Bayesian additive regression trees for risk prediction with high-dimensional epigenetic signatures and low-dimensional covariates. ArXiv Link

Recent Events / Talks

• Aug 2026: Topic Contributed Talk at JSM 2026, Boston, MA

• July 2026: Invited Talk at ISBA 2026, Nagoya, Japan

• Jan-Feb 2026: Two guest lectures on causal inference and machine learning in the PHS 31001- Epidemiological Methods class at UChicago

• Feb 2026: Invited Talk at UIC Biostatistics Seminar Series