725 S. Wright St.
Champaign, IL 61820
Yuguo Chen is Professor at Department of Statistics , University of Illinois at Urbana-Champaign. He is Director of Illinois Statistics Office. He is also affiliated with Department of Computer Science, Information Trust Institute, Computational Science and Engineering, and Illinois Informatics Institute. Prior to joining UIUC, he was an Assistant Professor at the Institute of Statistics and Decision Sciences, Duke University, from 2001 to 2005.
Monte Carlo theory and methodology, and their applications to scientific problems
Statistical inference on network data
State space models and dynamic systems
Bioinformatics and population genetics
PhD, Statistics, Stanford University, 2001
B.S., Mathematics, University of Science and Technology of China, 1997
Awards and Honors
Data Science Founder Professorial Scholar, 2019
Fellow of American Statistical Association, 2018
Charles Edison Lecturer, University of Notre Dame, 2018
Lists of Teachers Ranked as Excellent, 2010, 2013, 2015, 2017, 2018
Invited Lecture at the “Best of Computational and Graphical Statistics” session of Interface, 2015
ICSA Student Paper Award, 2001
Associate Editor, Journal of American Statistical Association, 2014-present.
Associate Editor, Journal of Computational and Graphical Statistics, 2007-present.
Editorial Board, Journal of Algebraic Statistics, 2009-present.
Editorial Board, ISRN Computational Mathematics, 2011-present.
Additional Campus Affiliations
Professor, Information Trust Institute
Professor, Coordinated Science Lab
Eisinger, R. D., Su, X., & Chen, Y. (2020). Sampling high dimensional tables with applications to assessing linkage disequilibrium. Statistics and its Interface, 13(2), 157-166. https://doi.org/10.4310/SII.2020.v13.n2.a2
Huang, W., Liu, Y., & Chen, Y. (2020). Mixed membership stochastic blockmodels for heterogeneous networks. Bayesian Analysis, 15(3), 711-736. https://doi.org/10.1214/19-BA1163
Loyal, J. D., & Chen, Y. (2020). Statistical Network Analysis: A Review with Applications to the Coronavirus Disease 2019 Pandemic. International Statistical Review, 88(2), 419-440. https://doi.org/10.1111/insr.12398
Paul, B. S., & Chen, Y. (2020). A random effects stochastic block model for joint community detection in multiple networks with applications to neuroimaging. Annals of Applied Statistics, 14(2), 993-1029. https://doi.org/10.1214/20-AOAS1339
Paul, S., & Chen, Y. (2020). Spectral and matrix factorization methods for consistent community detection in multi-layer networks. Annals of Statistics, 48(1), 230-250. https://doi.org/10.1214/18-AOS1800