In January I will start as a Simons-Berkeley Research Fellow at UC Berkeley, working with Nika Haghtalab and Michael Jordan. I am especially interested in topics at the intersection of machine learning, algorithmic game theory, and causal inference.

I received my PhD in Machine Learning from Carnegie Mellon University, where I was advised by Nina Balcan and Steven Wu. My thesis was on the interplay between information, incentives, and uncertainty in data-driven decision making. During the PhD, I was supported by the NDSEG Fellowship and was the editor-in-chief of the ML@CMU blog. I also spent two summers at Microsoft Research, working with Alex Slivkins.

Before coming to CMU, I studied computer science and physics at Penn State. In the startup world, I have spent time at Lux Capital, US Innovative Technology, and Vitable Health.

Some other pages I find interesting:

• The Berkeley AI Research blog
• The Matrix Cookbook
• The No Hands Across America homepage
• The SIGBOVIK homepage