My research is at the interface of theoretical machine learning and economics, encompassing topics such as information elicitation, crowdsourcing, and markets. I also work in dynamical systems.
I was previously a postdoc at MSR-NYC and then at Harvard's CRCS with Yiling Chen and Yaron Singer in the EconCS group. I completed my Ph.D. in theoretical computer science at Berkeley, advised by Christos Papadimitriou and funded by the NDSEG Fellowship.
- I am currently taking on students. If you have a strong math background and are interested in tackling exciting problems in algorithmic economics and theoretical machine learning, please apply.
- I am advising the Colorado Data Science Team, teaching algorithms, and co-organizing the Statistics, Optimization, and Machine Learning Seminar
- I am co-organizing the NIPS'16 Workshop on Crowdsourcing and Machine Learning (CrowdML).
- I am co-chairing the SIGAI Career Network Conference (CNC) 2016 in Boston, MA.
- Bo Waggoner and I gave an EC 2016 tutorial on elicitation and machine learning.
- I co-organized the ICML'15 Workshop on Crowdsourcing and Machine Learning (CrowdML).