About

I am currently a postdoctoral researcher Simons Institute at UC Berkeley where I am hosted by Peter Bartlett and Bin Yu, affiliated with the Machine Learning Research Pod and the Berkeley Statistical Machine Learning Group. My research focuses on diffusion models, optimization of neural networks, and Markov Chain Monte Carlo (MCMC). I received my undergraduate and master’s degrees in Applied Mathematics and Engineering from Queen’s University advised by Serdar Yüksel. I received my PhD in Statistics and Data Science from Yale University in 2025 advised by Andrew Barron.

The main theme of my research has been the convergence behaviour of stochastic processes: how error propagates through a random system, how quickly a system converges to its invariant distribution, and the properties of this distribution in downstream applications. In my early research, this focused on filter stability for Hidden Markov Models (HMM) and applications to robust stochastic control. Namely, given bad prior information can an agent still learn an accurate posterior on the hidden state of a system and use this to make good control decisions.

More recently, I am interested in mixing time guarantees of sampling algorithms for multi modal and non-log-concave target densities and improved sample accuracy for diffusion models. What methods are most effective to produce samples from such difficult densities? Traditional MCMC methods based on time invariant local likelihood updates can have difficulty exploring the full state space and can get trapped in local modes of the log-likelihood for long periods of time. Time varying transition rules, annealing, auxiliary random variables, and diffusion models all present interesting alternatives to produce samples for such densities beyond traditional MCMC.

In addition to theoretical properties of stochastic algorithms I am also interested in applications of generative models in the physical sciences and their use in studying AI Safety.

I currently co-organize the ML and AI Theory Seminar and reading group.

For more information, please see my Publications page, CV, or LinkedIN profile.

Upcoming News

• I am currently on the academic job market interested in Assistant Professor positions beginning September 2027 in Statistics, Computer Science, and Engineering departments with a focus on stochastic processes and machine learning.