About
Tyler is a PhD student in Political Science and Scientific Computing at the University of Michigan, also pursuing a dual master's degree in Statistics. His research lies at the intersection of social demography and party politics, studying how aggregate population data can be decomposed to uncover the long-term effects of demographic trends on political parties and party systems.
Substantively, Tyler focuses on East and Southeast Asia, conducting research in Chinese, Malay, Indonesian, and Japanese. His interest in the region stems from the diversity of its electoral systems, where institutional constraints shape the political consequences of demographic change in distinct ways.
Methodologically, Tyler's current project is a large-scale simulation study comparing ecological inference methods, spanning classical bounds estimators, Bayesian MCMC, MRP, semiparametric sieve estimators, and likelihood-free methods, under varying conditions of segregation, polarization, survey quality, and model misspecification. A central contribution is the development of a hierarchical ABC-SMC estimator that integrates survey microdata with aggregate election returns through a likelihood-free framework. He has taught both undergraduate and graduate courses in statistical methods.
Tyler co-organizes the Rackham China Reading Group (2023– ), serves as president of the Graduate Association of Political Scientists, and is a council member of the LSA Graduate Student Advisory Council and the inter-university GETSEA consortium.
