Zhongxuan Sun
PhD student
Department of Biostatistics & Medical Informatics
University of Wisconsin–Madison
About
I’m a PhD student in Biomedical Data Science at the University of Wisconsin–Madison, where I am grateful to be co-advised by Prof. Sündüz Keleş and Prof. Hyunseung Kang. I am broadly interested in developing and applying statistical methods to address real-world scientific problems.
My current work focuses on causal inference, statistical genomics, and computational biology, specifically the analysis of large-scale CRISPR perturbation data to illuminate gene regulation and other complex biological processes. Prior to graduate school, I was fortunate to be advised by Prof. Qiongshi Lu, working 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
- BS, Mathematics & Statistics · University of Wisconsin–Madison, 2019–2023
Research Experience
- Graduate Researcher, UW–Madison
- Undergraduate Researcher, UW–Madison
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.
Full list on Google Scholar.
Conference Presentations
Estimating gene regulatory networks using Perturb-seq data
- 2026 · RECOMB — Talk
- 2025 · ACIC — Poster & lightning talk
Pervasive biases in GWAS using family history of Alzheimer’s disease
- 2024 · ASHG — Poster
- 2024 · IGSS — Talk
- 2024 · TAGC — Talk
- 2022 · ASHG — Poster
Honors & Awards
- RECOMB 2026 Conference Travel Fellowship
- Wisconsin Hilldale Undergraduate/Faculty Research Fellowship
Service
Peer Review
Journals
- Alzheimer’s Research & Therapy
- BMC Medical Genomics
- npj Aging
- npj Dementia
- Scientific Reports
Conferences
Mentorship
Last updated · April 28, 2026