Biography
Wendy K. Tam Cho is Professor in the Departments of Political Science, Statistics, Mathematics, Computer Science, Asian American Studies, and the College of Law, Senior Research Scientist at the National Center for Supercomputing Applications, Faculty in the Illinois Informatics Institute, and Affiliate of the Cline Center for Advanced Social Research, the CyberGIS Center for Advanced Digital and Spatial Studies, the Computational Science and Engineering Program, and the Program on Law, Behavior, and Social Science at the University of Illinois at Urbana-Champaign. She is also a Fellow of the John Simon Guggenheim Memorial Foundation, the Society for Political Methodology, the Center for Advanced Study in the Behavior Sciences at Stanford University, and a Visiting Fellow at the Hoover Institution at Stanford University.
Additional Campus Affiliations
Professor, Political Science
Professor, National Center for Supercomputing Applications (NCSA)
Professor, Statistics
Professor, Mathematics
Professor, College of Law
Professor, Computer Science
External Links
Recent Publications
Cho, W. K. T., & Hwang, D. G. (2023). Differential Effects of Race/Ethnicity and Social Vulnerability on COVID-19 Positivity, Hospitalization, and Death in the San Francisco Bay Area. Journal of Racial and Ethnic Health Disparities, 10(2), 834-843. https://doi.org/10.1007/s40615-022-01272-z
Cho, W. K. T., & Hwang, D. G. (2023). Racial/Ethnic, Biomedical, and Sociodemographic Risk Factors for COVID-19 Positivity and Hospitalization in the San Francisco Bay Area. Journal of Racial and Ethnic Health Disparities, 10(4), 1653-1668. https://doi.org/10.1007/s40615-022-01351-1
Cho, W. K. T., & Cain, B. E. (2022). AI and Redistricting: Useful Tool for the Courts or Another Source of Obfuscation? Forum (Germany), 20(3-4), 395-408. https://doi.org/10.1515/for-2022-2061
Knox, D., Lucas, C., & Cho, W. K. T. (2022). Testing Causal Theories with Learned Proxies. Annual Review of Political Science, 25, 419-441. https://doi.org/10.1146/annurev-polisci-051120-111443
Cho, W. K. T., & Liu, Y. Y. (2021). A parallel evolutionary multiple-try metropolis Markov chain Monte Carlo algorithm for sampling spatial partitions. Statistics and Computing, 31(1), Article 10. https://doi.org/10.1007/s11222-020-09977-z