Joshua D. Loyal

I am a PhD candidate in the Department of Statistics at the University of Illinois at Urbana-Champaign advised by Professor Yuguo Chen and Ruoqing Zhu.

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.