My research interests include statistical network analysis, Bayesian inference, machine learning, data science, and statistical computing.
From 2015 to 2018, I was a Data Scientist at DataRobot, a start-up in Boston aimed at building an automated machine learning platform. I received an M.S. in Physics from Yale University and a B.S. in Physics and Mathematics from Duke University. During my physics career, I worked as a particle phycisist as part of the ATLAS collaboration at the Large Hadron Collider in Geneva, Switzerland. There I performed large scale data analytics and contributed to the development of a Deep Learning framework for classifying subatomic-particle jets.
|Mar 24, 2021||New pre-print: “Dimension Reduction Forests: Local Variable Importance using Structured Random Forests”, with Ruoqing Zhu, Yifan Cui, and Xin Zhang.|
|Mar 23, 2021||New pre-print: “An Eigenmodel for Dynamic Multilayer Networks”, with Yuguo Chen.|
|Jul 29, 2020||“Statistical network analysis: A review with applications to the coronavirus disease 2019 pandemic”, with Yuguo Chen, is now published online in International Statistical Review.|
|Mar 16, 2020||New pre-print: “A Bayesian Nonparametric Latent Space Approach to Modeling Evolving Communities in Dynamic Networks”, with Yuguo Chen.|
|Sep 13, 2021||ICSA Applied Statistics Symposium. Online. Poster.|
|Aug 11, 2021||Joint Statistical Meetings 2021. Online. Talk.|
|Jun 29, 2021||2021 ISBA World Meeting. Online. Talk.|
|Jun 23, 2021||Networks 2021 Satellite: Statistical Inference for Network Models. Online. Talk.|
|Apr 17, 2021||Bohrer Workshop in Statistics. Department of Statistics, University of Illinois at Urbana-Champaign, Poster.|