I am a Postdoctoral Research Fellow in the Department of Biostatistics at Harvard, working with Jeff Miller and Scott Carter. The primary focus of my research is developing reliable approximate inference methods that are scalable to large datasets and complex models. My goal is to create algorithms with finite-data accuracy guarantees that users can trust in safety-critical domains such as clinical and medical diagnostic settings. Previously, I was a Ph.D. candidate at MIT, where I was advised by Tamara Broderick. Before coming to MIT, I was a mathematics major at Columbia University, where I worked with Frank Wood on Bayesian nonparametric modeling and with Liam Paninski on statistical methods for neuroscience.
Ph.D. in Computer Science, 2018
Massachusetts Institute of Technology
B.A. in Mathematics, 2012