Jaewon Lim

I am a fifth-year PhD student in Biostatistics at the University of Washington, advised by Alex Luedtke.

My research focuses on causal inference, data fusion, and semiparametric efficiency theory, with an emphasis on efficient estimation and statistical inference for smooth function-valued parameters. In this paper, I develop methods for estimating causal dose-response functions under data fusion. This framework incorporates partially aligned data sources to estimate dose-response functions and demonstrates that data fusion yields tighter finite-sample regret bounds and improved worst-case performance, supported by minimax lower-bound comparisons.

I am also working with Thomas Fleming and collaborators at Regeneron on developing sample size calculation methods for recurrent event data under the Andersen-Gill model with between-subject heterogeneity. In addition to methodological work, I have participated in several applied statistical projects in epidemiology and public health, including differential network analysis with Ali Shojaie and cardiovascular and metabolic disease research with the CHSCC under Robyn McClelland.