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R E S E A R C H
Redistricting | Ecological Inference | Computational and Statistical Methods | Health | Racial and Ethnic Politics
| American Politics
R E D I S T R I C T I N G
2019 Winner of the HPC Innovation Award for Outstanding Application of HPC Computing for Business and Scientific Achievements
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Human-Centered Redistricting Automation in the Age of AI, with Bruce E. Cain. Science 369, 6508 (September 4, 2020): 1179-1181. doi.org/10.1126/science.abd1879 PDF
A Parallel Evolutionary Multiple-Try Metropolis Markov Chain Monte Carlo Algorithm for Sampling Spatial Partitions, with Yan Y. Liu. Statistics and Computing 31, Article 10 (2021). doi.org/10.1007/s11222-020-09977-z
A Spatially Explicit Evolutionary Algorithm for the Spatial Partitioning Problem, with Yan Y. Liu. Applied Soft Computing Journal 90 (May 2020): Article 106129 doi.org/10.1016/j.asoc.2020.106129 PDF
Deploying Trustworthy AI in the Courtroom: Lessons from Examining Algorithm Bias in Redistricting AI, with Bruce E. Cain. The University of Chicago Legal Forum 2023 (2024): 87-114. PDF
AI and Redistricting: Useful Tool for the Courts or Another Source of Obfuscation?, with Bruce E. Cain. The Forum: A Journal of Applied Research in Contemporary Politics 21 (2022): 1-14. doi.org/10.1515/for-2022-2061 PDF
Technology-Enabled Coin Flips for Judging Partisan Gerrymandering. Southern California Law Review Postscript 93 (May 2019): 11-27. PDF
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. doi.org/10.1080/2330443X.2019.1574687 PDF
Rejoinder to "Understanding our Markov Chain Significance Test", with Simon Rubinstein-Salzedo. Statistics and Public Policy 6, 1 (2019): 54. doi.org/10.1080/2330443X.2019.1619427 PDF
Algorithms can foster a more democratic society. Nature 558 (June 28, 2018): 487. PDF
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. doi:10.1016/j.physa.2018.03.096
A Massively Parallel Evolutionary Markov Chain Monte Carlo Algorithm for Sampling Complicated Multimodal State Spaces, with Yan Y. Liu. SC18: The International Conference for High Performance Computing, Networking, Storage and Analysis. November 11-16. Dallas, TX.
A High-Performance Evolutionary Computation Framework for Scalable Spatial Optimization, with Yan Y. Liu. 2018. ICCS: International Conference on Computational Science: Science at the Intersection of Data, Modelling and Computation. June 11-13. Wuxi, China.
A Reasonable Bias Approach to Gerrymandering: Using Automated Plan Generation to Evaluate Redistricting Proposals, with Bruce E. Cain, Yan Y. Liu, and Emily Zhang. William & Mary Law Review 59, 5 (April 2018): 1521-1557. PDF
Massively Parallel Evolutionary Computation for Empowering Electoral Reform: Quantifying Gerrymandering via Multi-objective Optimization and Statistical Analysis, with Yan Y. Liu. SC17: The International Conference for High Performance Computing, Networking, Storage and Analysis. November 12-17. Denver, CO.
Measuring Partisan Fairness: How well does the Efficiency Gap Guard Against Sophisticated as well as Simple-Minded Modes of Partisan Discrimination? University of Pennsylvania Law Review Online 166 (July 2017): 17-36. PDF Press:
The Weekly Standard, WisCommunity
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. PDF
First Place Winner in the
2016 Common Cause "Gerrymander Standard" Writing Competition
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. doi:10.1016/j.swevo.2016.04.004
A Scalable Computational Approach to Political Redistricting Optimization, with Yan Y. Liu and Shaowen Wang. 2015. In Proceedings of the 2015 Annual Conference on Extreme Science and Engineering Discovery Environment. XSEDE15: Scientific Advancements Enabled by Enhanced Cyberinfrastructure. July 26-30. St. Louis, MO.
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. PDF
Panethnicity Revisited: Asian Indians, Asian American Politics, and the Voting Rights Act, with Albert H. Yoon. UCLA Asian Pacific American Law Journal 10 (2005): 8-30. PDF
Strange Bedfellows: Politics, Courts, and Statistics: Statistical Expert Testimony in Voting Rights Cases, with Albert H. Yoon.
Cornell Journal of Law and Public Policy 10, 2 (Spring 2001): 237-264. PDF
ECOLOGICAL INFERENCE
Top
Iff the Assumption Fits... : A Comment on the King Ecological Inference Solution. Political Analysis 7 (1998): 143-163. PDF
Cross-Level/Ecological Inference, with Charles F. Manski, in Box-Steffensmeier, Janet, Henry Brady, and David Collier, eds., Oxford Handbook of Political Methodology. Oxford University Press, 2008, pp. 547-569. PDF
Recovering Vote Choice from Partial Incomplete Data, with George G. Judge. Journal of Data Science 6, 2 (April 2008): 155-171. PDF
An Information Theoretic Approach to Ecological Estimation and Inference, with George G. Judge and Douglas J. Miller, in King, Gary, Ori Rosen, and Martin Tanner, eds., Ecological Inference: New Methodological Strategies. Cambridge University Press, 2004, pp. 162-187. PDF
The Limits of Ecological Inference: The Case of Split Ticket Voting, with Brian J. Gaines. (Previously forthcoming in the APSR).
American Journal of Political Science 48, 1 (January 2004):152-171. PDF
Reply to the Gary King Archive of the Controversy that surrounded the publication of "The Limits of Ecological Inference: The Case of Split Ticket Voting" PDF
Spatial Effects and Ecological Inference, with Luc Anselin.
Political Analysis 10, 3 (Summer 2002): 276-297. PDF
Latent Groups and Cross-Level Inferences.
Electoral Studies 20, 2 (June 2001): 243-263. PDF
COMPUTATIONAL AND STATISTICAL MODELING
Top
A GPU-Accelerated Population Generation, Sorting, and Mutation Kernel for an Optimization-Based Causal Inference Model, with Yan Y. Liu. 2023. In 52nd International Conference on Parallel
Processing Workshops (ICPP-W 2023), August 7--10, 2023, Salt Lake
City, UT, USA. ACM, New York, NY, USA.
Testing Causal Theories with Learned Proxies, with Dean Knox and Christopher Lucas. In Levi, Margaret and Nancy L. Rosenblum(Eds.), Annual Review of Political Science, Volume 25, (May 2022) pp. 419-441. https://doi.org/10.1146/annurev-polisci-051120- 111443
Parallel Hybrid Metaheuristics with Distributed Intensification and Diversification for Large-scale Optimization 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, and Y.F. Ye (Eds.), Proceedings of the 2019 IEEE International Conference on Big Data, pp. 3312-3320. Institute of Electrical and Electronics Engineers Inc. doi.org/10.1109/BigData47090.2019.9006045
An Evolutionary Algorithm for Subset Selection in Causal Inference Models. Journal of the Operational Research Society 69, 4 (2018): 630-644. doi:10.1057/s41274-017-0258-8
Causal Inferences from Many Experiments. Journal of Applied Statistics 44, 16 (2017): 2908-2922. PDF
A Scalable Evolutionary Algorithm with Intensification and Diversification Protocols Designed for Statistical Models, with Yan Y. Liu. 2016. Extended Abstract. SC16: The International Conference for High Performance Computing, Networking, Storage and Analysis. November 13-18. Salt Lake City, UT.
A Parallel Evolutionary Algorithm for Subset Selection in Causal Inference Models, with Yan Y. Liu. 2016. In Proceedings of the 2016 Annual Conference on Extreme Science and Engineering Discovery Environment. XSEDE16: Diversity, Big Data, & Science at Scale. July 17-21. Miami, FL.
A High-Performance Approach for Solution Space Traversal in Combinatorial Optimization, with Yan Y. Liu. 2015. Extended Abstract. SC15: The International Conference for High Performance Computing, Networking, Storage and Analysis. November 16-19. Austin, TX.
An Information Theoretic Approach to Network Tomography, with George Judge. Applied Economics Letters 22, 1 (January 2015): 1-6. PDF
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 (March/April 2013): 398-412. PDF
An Optimization Approach for Making Causal Inferences, with Jason J. Sauppe, Alexander G. Nikolaev, Sheldon H. Jacobson, and Edward C. Sewell. Statistica Neerlandica 67, 2 (May 2013): 211-226. PDF
Generalizing Benford's Law: A Re-examination of Falsified Clinical Data, with Joanne Lee and George G. Judge, in Miller, Steven J., Arno Berger, and Ted Hill, eds., Theory and Applications of Benford's Law, Princeton and Oxford: Princeton University Press. 2014. pp. 301-313.
An Analysis of Daily Predictions for the 2008 United States Presidential Election, with Steven E. Rigdon, Sheldon H. Jacobson, Edward C. Sewell, and Christopher J. Rigdon. Case Studies in Business, Industry and Government Statistics 4, 1 (November 2011): 1-8. PDF
Stigler's Approach to Recovering the Distribution of First Significant Digits in Natural Data Sets, with Joanne Lee and George G. Judge. Statistics and Probability Letters 80, 2 (February 2010): 82-88. PDF
A Bayesian Prediction Model for the United States Presidential Election, with Steven E. Rigdon, Sheldon H. Jacobson, Edward C. Sewell, and Christopher J. Rigdon. American Politics Research 37, 4 (July 2009): 700-724. PDF
Information Theoretic Solutions for Correlated Bivariate Processes, with George G. Judge. Economics Letters 97, 3 (December 2007): 201-207. PDF
Breaking the (Benford) Law: Statistical Fraud Detection and Campaign Finance, with Brian J. Gaines. The American Statistican 61, 3 (August 2007): 218-223. PDF
Conceptualizing Space: Reply, with Luc Anselin.
Political Analysis 10, 3 (Summer 2002): 301-303. PDF
H E A L T H Top
Sociodemographic Disparities in Preoperative Visual Acuity and Cataract Surgery Utilization in the San Francisco Bay Area, with David G. Hwang. Journal of Racial and Ethnic Health Disparities. 2024. doi.org/10.1007/s40615-024-01914-4 PDF
Racial/Ethnic, Biomedical, and Sociodemographic Risk Factors for COVID-19 Positivity and Hospitalization in the San Francisco Bay Area, with David G. Hwang. Journal of Racial and Ethnic Health Disparities 10 (2023): 1653-1668. doi:10.1007/s40615-022-01351-1 PDF
Press: San Francisco Chronicle (NextShark)
Differential Effects of Race/Ethnicity and Social Vulnerability on COVID-19 Positivity, Hospitalization, and Death in the San Francisco Bay Area, with David G. Hwang. Journal of Racial and Ethnic Health Disparities 10 (2023): 834-843.
doi:10.1007/s40615-022-01272-z PDF
Press: Illinois New Bureau
R A C I A L A N D E T H N I C
P O L I T I C S
Top
Environmental Determinants of Racial Attitudes Redux: The Critical Decisions Related to Operationalizing Context, with Neil Baer. American Politics Research 39, 2 (March 2011): 414-433. PDF
A Political Powerhouse in Search of a Home, with James G. Gimpel. Asian American Policy Review (2008) 17: 91-98.
Demythicizing the Asian-American Campaign Contributor, in Cain, Bruce E., Jaime Regalado, and Sandra Bass, eds., Racial and Ethnic Politics in California, Volume III, Berkeley, CA: Berkeley Public Policy Press, Institute of Governmental Studies, 2008, pp. 37-60. PDF
Spatial Dimensions of Arab American Voter Mobilization after September 11, with James G. Gimpel. Political Geography 26, 3 (March 2007): 330-351. PDF
Clarifying the Role of SES in Participation: Policy Threat and Arab American Mobilization, with James G. Gimpel and Tony Wu. Journal of Politics 68, 4 (November 2006): 974-988. PDF
Residential Concentration, Socialization, and Voter Turnout, with James G. Gimpel and Joshua J. Dyck. Journal of Politics 68, 1 (February 2006): 156-167. PDF
The Persistence of White Ethnicity in New England Politics, with James G. Gimpel. Political Geography 23, 8 (November 2004): 987-1008. PDF
Getting Out the Asian-Pacific-American Vote: The Value in the Unpredictable, with James G. Gimpel. Campaigns and Elections 25, 6 (July 2004): 44-45. PDF
On California's 1920 Alien Land Law: The Psychology and Economics of Discrimination, with Brian J. Gaines. State Politics and Policy Quarterly 4, 3 (Fall 2004): 271-293. PDF
Subcontinental Divide: Asian Indians and Asian American Politics, with Suneet P. Lad. American Politics Research 32, 3 (May 2004): 239-263. PDF
Contagion Effects and Ethnic Contribution Networks.
American Journal of Political Science 47, 2 (April 2003): 368-387. PDF
Tapping Motives and Dynamics Behind Campaign Contributions: Insights from the Asian American Case. American Politics Research 30, 4 (July 2002): 347-383. PDF
Asian Pacific-American Campaigns, Elections, and Elected Officials, with James S. Lai, Thomas P. Kim, and Okiyoshi Takeda.
PS: Political Science and Politics 34, 3 (September 2001): 611-617. PDF
Foreshadowing Strategic Pan-Ethnic Politics: Asian American Campaign Finance Behavior in Varying Multicultural Contexts.
State Politics and Policy Quarterly 1, 3 (September 2001): 273-294. PDF
Asian Americans as the Median Voters: An Exploration of Attitudes and Voting Patterns on Ballot Initiatives, with Bruce Cain in Chang, Gordon H., ed., Asian Americans and Politics: Perspectives, Experiences, Prospects. Stanford University Press. 2001, pp. 133-152. PDF
Naturalization, Socialization, Participation: Immigrants and (Non-) Voting. Journal of Politics 61, 4 (November 1999): 1140-1155. PDF
Asians—A Monolithic Voting Bloc?
Political Behavior 17, 2 (June 1995): 223-249. PDF
A M E R I C A N P O L I T I C S Top
Migration as an Opportunity to Register Changing Partisan Loyalty in the U.S., with James G. Gimpel and Iris S. Hui. Population, Space and Place 25, 4 (May 2019). PDF.
Spatial Dimensions of American Politics, with Iris S. Hui. In Cao, Kai and Elisabete A. Silva, eds. Comprehensive Geographic Information Systems. GIS Applications (socio-economic) Elsevier. 2017, Volume 3, Chapter 13, pp. 181-188. PDF
Legislative Networks, with Nils Ringe and Jennifer Nicoll Victor. In Victor, Jennifer Nicoll, Mark Lubell, and Alexander H. Montgomery, eds. Oxford University Press Handbook of Political Networks Oxford University Press. 2017. Chapter 19. pp. 471-489. PDF
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. PDF
Press: The New York Times, Harvard Political Review, London School of Economics US Centre,
The Tea Party and the Geography of Collective Action, with James G. Gimpel and Daron R. Shaw. Quarterly Journal of Political Science. 7, 2 (April 2012): 105-133. PDF
Geographic Information Systems and the Spatial Dimensions of American Politics, with James G. Gimpel. Annual Review of Political Science. 15 (2012): 443-460. PDF
Rough Terrain: Spatial Variation in Political Participation, with James G. Gimpel. American Journal of Political Science 54, 1 (January 2010): 74-89. PDF
Legislative Success in a Small World: Social Network Analysis and the Dynamics of Congressional Legislation, with James H. Fowler. Journal of Politics 72, 1 (January 2010): 124-135. PDF
Presidential Voting and the Local Variability of Economic Hardship, with James G. Gimpel. The Forum. 2009. Vol. 7, Iss. 1, Article 1. PDF
Geographic Proximity versus Institutions: Evaluating Borders as Real Political Boundaries, with Erinn P. Nicley. American Politics Research 36, 6 (November 2008): 803-823. PDF
Emanating Political Participation: Untangling the Spatial Structure behind Participation, with Thomas J. Rudolph. British Journal of Political Science 38, 2 (April 2008): 273-289. PDF
Prospecting for (Campaign) Gold, with James G. Gimpel. American Journal of Political Science 51, 2 (April 2007): 255-268. PDF
Crossover Voting Before the Blanket: Primaries versus Parties in California History, with Brian Gaines in Cain, Bruce E. and Elisabeth R. Gerber, eds., Voting at the Political Fault Line: California's Experiment with the Blanket Primary. University of California Press. 2002, pp. 12-35. PDF
Candidates, Donors, and Voters in California's First Blanket-Primary Elections, with Brian Gaines in Cain, Bruce E. and Elisabeth R. Gerber, eds., Voting at the Political Fault Line: California's Experiment with the Blanket Primary. University of California Press. 2002, pp. 171-191. PDF
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