A little about me: I am an assistant professor of Statistics and Electrical Engineering at Stanford University. I completed my PhD in computer science at Berkeley in 2014. My research interests are a bit eclectic, and they span computation, statistics, optimization, and machine learning; if you like any of these, we can probably find something interesting to chat about. At Berkeley, I worked in the Statistical Artificial Intelligence Lab (SAIL) under the joint supervision of Michael Jordan and Martin Wainwright. I obtained my master's degree (MA) in statistics in Fall 2012. I was an undergrad and a masters student at Stanford University, where I worked with Daphne Koller, and I also spent some time at Google Research, where I had the great fortune to work with Yoram Singer. (Here is a slightly more formal bio, with photo, in the third-person.)
Publications: [a list of my publications] in mostly chronological order.
Curriculum Vitae: [cv.pdf]
Contact info: [Visit]
Please note: unfortunately, I am unable to respond to most inquiries regarding openings for graduate and postdoctoral positions in my group. Admissions to Stanford are handled at a department-wide level, not by me individually, so I am unable to comment on your suitability for graduate school or work with me. If you are already a Stanford student or have been admitted to Stanford, feel free to contact me about interests we may share.
Electrical Engineering 364a: Convex Optimization (Winter 2020)
Statistics 300b: Theory of Statistics (Winter 2017, 2018, 2019)
Statistics 311/Electrical Engineering 377: Information Theory and Statistics (Fall 2014, Winter 2016, Winter 2019)
Statistics 101: Data Science (Autumn 2018)
CS 229T/Statistics 229T: Machine Learning Theory (Autumn 2017)
Electrical Engineering 364b: Convex Optimization II (Spring 2015, Spring 2018)
CS/Stats 229: Machine learning (Spring 2016, Autumn 2016)