Hi! I'm a postdoc at Berkeley EECS. Starting in July 2021, I'll be an assistant professor at Cornell Tech as part of the Cornell School of Operations Research and Information Engineering.

My research is at the intersection of computer science, economics, and operations -- on the application of algorithms, data science, and mechanism design to the study of democracy, markets, and societal systems at large. Things I've worked on include surge pricing, rating systems, how to vote on budgets, the role of testing in college admissions, stereotypes in word embeddings, and polarization on Twitter.

My work has been covered in the New York Times, Washington Post, Science Magazine, Smithsonian Magazine (in print), Stanford Engineering magazine, Stanford News, and other places. I like to have first-hand practical experience in a domain before tackling research questions, and have built real systems (including for participatory budgeting and at NASA, Uber, and Upwork). I am senior scientific advisor to PredictWise, where I led data science efforts during the 2020 US election cycle.

I received a MS/PhD from Stanford in 2020, where I was lucky to be advised by Ashish Goel and Ramesh Johari and was part of the Stanford Crowdsourced Democracy Team and the Society and Algorithms Lab. Before that, I graduated with a BS/BA from The University of Texas at Austin in 2015.

Contact me at nkgar6@REMOVETHISgmail.REMOVETHIScom or Twitter.

What's new

Nov 2020 I received the INFORMS Dantzig Dissertation award, and 2nd place in the MSOM Student Paper competition.
Oct 2020 New paper online, "Standardized Tests and Affirmative Action: The Role of Bias and Variance."
May 2020 Two papers accepted to EC'20, "Driver Surge Pricing" and "Designing Informative Rating Systems: Evidence from an Online Labor Market."
Nov 2019 New paper online, "Fair Allocation through Selective Information Acquisition." December update: Accepted to the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society.