I am an assistant professor of statistical science and computer science at Duke University. I work primarily on fundamental properties of different statistical concepts with broad inetrests in network analysis, causal inference and computational constraints of statistical methods. I am the Co-Director two labs at Duke: (1) The Polarization Lab at Duke brings together scholars from the social sciences, statistics, and computer science to develop new technology to bridge America’s partisan divide. Check our our newest work on assessing the effects of Russian trolls on political attitudes and behaviors in 2017. (2) The Almost Matching Exactly Lab at Duke brings together statisticians, computer scientists, economists and political scientists to develop tools for interpretable causal inference.
I was one of the organizers of the SAMSI Semester Program on Causal Inference in Spring 2020. The opening workshop was held in December 2019. Closing workshops will be held at some point (possibly at next year's ACIC!).
I help run the New Researchers Group at the Institute of Mathematical Statistics which coordinates the Meeting of New Researchers in Statistics and Probability (supported by the National Science Foundation). Our 2020 meeting is currently on hold but check out the website for new developments (for NRC and the group in general)!
If interested in joining our group to work on exciting problems in statistical methodology for political polarization, network analysis and large scale causal inference, please reach out via email with your CV.
Travel is mainly postponed. Depending on how conferences go online you will find me or members of the lab at AISTATS, UAI, JSM, CMSTATS and others.
Our work is graciously supported by NIH, NSF, ARI, Facebook, and Duke University.