Zhongxuan Sun

PhD student

Department of Biostatistics & Medical Informatics
University of Wisconsin–Madison

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About

I am a PhD student in Biomedical Data Science at the University of Wisconsin–Madison, co-advised by Prof. Sündüz Keleş and Prof. Hyunseung Kang. My research develops methods for causal inference and statistical genomics, motivated by challenges that arise in the analysis of complex biomedical data.

My current work centers on large-scale CRISPR perturbation data, with applications to studying gene regulation and other complex biological processes. Before graduate school, I worked with Prof. Qiongshi Lu on statistical methods for complex trait genetics and genetic risk prediction using biobank-scale data.

Currently working on: CRISPR off-target effects heterogeneous treatment effects instrumental variables causal representation learning

Education

PhD, Biomedical Data Science · University of Wisconsin–Madison, 2023–Present
MS, Computer Sciences · University of Wisconsin–Madison, expected 2026
BS, Mathematics & Statistics · University of Wisconsin–Madison, 2023

Research Experience

Graduate Researcher, UW–Madison 2024–Present
Undergraduate Researcher, UW–Madison 2021–2023

Selected Publications

* Equal contribution.

First / Co-first author

Sun, Z., Kang, H., Keleş, S. (2026). Causal gene regulatory network inference from Perturb-seq via adaptive instrumental variable modeling. Research in Computational Molecular Biology (RECOMB). (Acceptance Rate: 15.8%).
Wu, Y.*, Sun, Z.*, Zheng, Q., Miao, J., Dorn, S., Mukherjee, S., Fletcher, J., Lu, Q. (2024). Pervasive biases in proxy genome-wide association studies based on parental history of Alzheimer’s disease. Nature Genetics.

Co-author

Park, K., Sun, Z., Liao, R., Bresnick, E. H., Keleş, S. (2026). Systematic background selection with BasCoD enhances contrastive dimension reduction in single cell genomics. Nature Communications.
Zhao, Z., Gruenloh, T., Yan, M., Wu, Y., Sun, Z., Miao, J., Wu, Y., Song, J., Lu, Q. (2024). Optimizing and benchmarking polygenic risk scores with GWAS summary statistics. Genome Biology.
Miao, J., Wu, Y., Sun, Z., Miao, X., Lu, T., Zhao, J., Lu, Q. (2024). Valid inference for machine learning-assisted genome-wide association studies. Nature Genetics.
Furuya, S., Liu, J., Sun, Z., Lu, Q., Fletcher, J. (2023). The Big (Genetic) Sort? A Research Note on Migration Patterns and Their Genetic Imprint in the United Kingdom. Demography.
Amin, V., Fletcher, J., Sun, Z., Lu, Q. (2022). Higher educational attainment is associated with longer telomeres in midlife: Evidence from sibling comparisons in the UK Biobank. SSM–Population Health.