Jessalyn Sebastian

PhD Candidate in Statistics at the University of California, Irvine

I am a PhD candidate studying Statistics at UCI, advised by Dr. Volodymyr Minin. My research focuses on developing Bayesian methods that are flexible enough to address complex scientific questions while remaining transparent, robust, and usable in substantive applications. I am particularly interested in stochastic processes, latent function inference, and the role of modeling assumptions and prior choices in statistical inference, with applications in infectious disease epidemiology. I am also interested in statistics education.

My current methodological work develops computationally efficient Bayesian methods for smoothing and latent function inference using Gaussian process priors with Markov structure. I also work on collaborative applied projects using Bayesian phylogenetic methods to study respiratory virus and tuberculosis transmission.