Wendy K Tam Cho

Wendy K Tam Cho
Wendy K Tam Cho
Professor
(217) 333-9588
304E David Kinley Hall

For more information

Education

  • A.B. Political Science, University of California at Berkeley, Berkeley, California, 1990
  • A.B. Applied Mathematics (applied field: ComputerScience), University of California at Berkeley, Berkeley, California, 1990
  • M.A. Political Science, University of California at Berkeley, Berkeley, California, 1992
  • M.A. Statistics, University of California at Berkeley, Berkeley, California, 1997
  • Ph.D Political Science, University of California at Berkeley, Berkeley, California, 1997

Academic Positions

  • Senior Research Scientist, National Center for Supercomputing Applications University of Illinois at Urbana-Champaign, 2006-
  • Professor, University of Illinois at Urbana-Champaign, Department of Political Science, Department of Statistics, Department of Mathematics, Department of Computer Science, Department of Asian American Studies, Law School, 2010-

Selected Articles in Journals

  • “A Parallel Evolutionary Multiple-Try Metropolis Markov Chain Monte Carlo Algorithm for Sampling Spatial Partitions,” with Yan Y. Liu. Statistics and Computing. 2021. Forthcoming.
  • “Human-Centered Redistricting Automation in the Age of AI,” with Bruce E. Cain. Science 369, 6508 (September 4, 2020): 1179-1181.
  • “A Spatially Explicit Evolutionary Algorithm for the Spatial Partitioning Problem,” with Yan Y. Liu. Applied Soft Computing Journal 90 (May 2020): Article 106129.
  • “Parallel Hybrid Metaheuristics with Distributed Intensification and Diversification for Large-scale Opti- mization in Big Data Statistical Analysis,” with Yan Y. Liu. In C. Baru, J. Huan, L. Khan, X. T. Hu, R. Ak, Y. Tian, R. Barga, C. Zaniolo, K. Lee, & Y. F. Ye (Eds.), Proceedings of the 2019 IEEE International Conference on Big Data, pp. 3312-3320. Institute of Electrical and Electronics Engineers Inc.
  • “Understanding Significance Tests from a Non-Mixing Markov Chain for Partisan Gerrymandering Claims,” with Simon Rubinstein-Salzedo. Statistics and Public Policy 6, 1 (2019): 44-49.
  • “Technology-Enabled Coin Flips for Judging Partisan Gerrymandering.” Southern California Law Re- view Postscript 93 (May 2019): 11-27.
  • “Algorithms Can Foster a More Democratic Society.” Nature 558, 7711 (June 28, 2018): 487.
  • “Sampling from Complicated and Unknown Distributions: Monte Carlo and Markov Chain Monte Carlo Methods for Redistricting,” with Yan Y. Liu. Physica A 506 (September 2018): 170-178.
  • “An Evolutionary Algorithm for Subset Selection in Causal Inference Models.” Journal of the Operational Research Society 69, 4 (2018): 630-644.
  • “Causal Inferences from Many Experiments.” Journal of Applied Statistics 44, 16 (2017): 2908-2922.
  • “Toward a Talismanic Redistricting Tool: A Computational Method for Identifying Extreme Redistricting Plans,” with Yan Y. Liu. Election Law Journal 15, 4 (December 2016): 351-366.
  • “PEAR: A Massively Parallel Evolutionary Computation Approach for Political Redistricting Optimization and Analysis,” with Yan Y. Liu and Shaowen Wang. Swarm and Evolutionary Computation 30 (October 2016): 78-92.
  • “A Parallel Evolutionary Algorithm for Subset Selection in Causal Inference Models,” with Yan Y. Liu. 2016. In Proceedings of XSEDE 2016: Diversity, Big Data, and Science at Scale. Association for Computing Machinery, a7. ACM International Conference Proceeding Series. Volume 17–21. Article 7, pp. 1-8. July 17-21.
  • “A Scalable Computational Approach to Political Redistricting Optimization,” with Yan Y. Liu and Shaowen Wang. 2015. In Proceedings of the XSEDE 2015 Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure. Association for Computing Machinery, a6. ACM International Conference Proceeding Series. Article 6, pp. 1-2. July 26-30.
  • “An Optimization Approach for Making Causal Inferences,” with Jason J. Sauppe, Alexander G. Nikolaev, Sheldon H. Jacobson and Edward C. Sewell. Statistica Neerlandica 27, 2 (May 2013): 211-226.
  • “Balance Optimization Subset Selection (BOSS): An Alternative Approach to Causal Inference with Observational Data,” with Alexander Nikolaev, Sheldon H. Jacobson, Jason Sauppe, and Edward C. Sewell. Operations Research 61,2 (2013): 398-412.
  • “Voter Migration and the Geographic Sorting of the American Electorate,” with James G. Gimpel and Iris S. Hui. Annals of the Association of American Geographers. 103, 4 (2013): 856-870.
  • "Geo-Graphs: An Efficient Model for Enforcing Contiguity and Hole Constraints in Planar Graph Partitioning,” with Douglas M. King, Sheldon H. Jacobson, and Edward C. Sewell. Operations Research 60, 5 (September-October 2012): 1213-1228.
  • "The Tea Party and the Geography of Collective Action,” with James G. Gimpel and Daron R. Shaw. Quarterly Journal of Political Science 7, 2 (2012): 105–133
  • “Rough Terrain: Spatial Variation in Campaign Contributing and Volunteerism,” with James G. Gimpel. American Journal of Political Science 54, 1 (January 2010): 74–89.
  • "Legislative Success in a Small World: Social Network Analysis and the Dynamics of Congressional Legislation," with James H. Fowler. Journal of Politics 71, 2 (January 2010): 1-12.
  • "Breaking the (Benford) Law: Statistical Fraud Detection and Campaign Finance," with Brian J. Gaines. The American Statistician 61, 3 (August 2007): 218--223.
  • "Prospecting for (Campaign) Gold," with James G. Gimpel. American Journal of Political Science 51,2(April 2007): 255-268.
  • "Clarifying the Role of SES in Political Participation: Policy Threat and Arab American Mobilization," with James G. Gimpel and Tony Wu. Journal of Politics 68,4(November 2006): 974-988.
  • "Residential Concentration, Socialization, and Voter Turnout," with James G. Gimpel and Joshua J. Dyck. Journal of Politics 68,1(February 2006): 156-167.
  • "The Limits of Ecological Inference: The Case of Split-Ticket Voting," with Brian J. Gaines. American Journal of Political Science 48,1(January 2004): 152-171.
  • "Contagion Effects and Ethnic Contribution Networks." American Journal of Political Science 47,2(April 2003): 368-387.
  • "Spatial Effects and Ecological Inference," with Luc Anselin. Political Analysis 10,3(Summer 2002): 276-297.
  • "Naturalization, Socialization, Participation: Immigrants and (Non-)Voting." Journal of Politics 61,4(November 1999): 1140-1155.
  • "Iff the Assumption Fits...:A Comment on the King Ecological Inference Solution." Political Analysis 7(1998): 143-163.

Invited Lectures

  • Keyfitz Lecture. The Fields Institute for Research in Mathematical Sciences

Journal Editorships

  • Editor, Political Analysis (with Robert Franzese and Andrew Martin) 2009-2010

Honors

  • John Simon Guggenheim Memorial Foundation Fellow, 2015-16

Teaching Honors

  • List of Teachers Ranked as Excellent by their Students, Multiple Years

Research Honors

  • HPC Innovation Excellence Award by Hyperion Research

Recent Courses Taught

  • PS 300 - Law of Democracy
  • PS 302 - The US Constitution II
  • PS 323 - Law and Representation
  • PS 531 - Quant Pol Analysis II
  • PS 532 - Quant Pol Analysis III
  • PS 590 - Statistical Computing

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