I am a Research Fellow in Computational Mathematics at the Flatiron Institute, a part of the Simons Foundation. In 2022, I earned a PhD in Statistics from Columbia University. You can find out more by browsing this website or looking at my CV.

My research concerns statistics and probabilistic machine learning. My work bridges methodology, computation, and application through the development of probabilistic programming languages such as Stan and TensorFlow Probability. Some keywords:

• Computation: Markov chain Monte Carlo, Variational inference, integrated Laplace approximation, automatic differentiation
• Modeling: Bayesian workflow, Hierarchical models, ODE-based models
• Applications: Pharmacometrics, Epidemiology, Astrophysics

News

• Starting in the summer of 2025, I will be an assistant professor of statistics at the University of British Columbia.

• May 2025: I will attend AISTATS in Thailand to present our recent paper on Variational Inference in Location-Scale Families. (Depending on circumstances, I may attend virtually.)

• June 2025: I will attend BayesComp in Singapore to chair a session on Parallel Computation for Markov chain Monte Carlo, and give an invited talk at the session on Advances in Variational Inference.

(last updated: March 2025)