I am the ITT Career Development Assistant Professor at MIT. I work in the areas of machine learning and statistics. Before coming to MIT, I completed my PhD at UC Berkeley. You can learn more about my background in the following short bio.
I am interested in understanding how we can reliably quantify uncertainty and robustness in modern, complex data analysis procedures. To that end, I'm particularly interested in Bayesian inference and graphical models—with an emphasis on scalable, nonparametric, and unsupervised learning.
Current PhD Students and Postdocs.
Interested in working with me?
- In Fall 2017, I am teaching 6.436 Fundamentals of Probability.
- In Spring 2018, I am teaching 6.882 Bayesian Modeling and Inference.
- To apply to work with me as a PhD student starting in 2018, submit your application to MIT EECS. More info at this link.
- I have an open postdoc position. Learn more at this link.