Zhongxuan Sun

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. I am broadly interested in developing and applying statistical methods to solve real-world problems.

My current work focuses on statistical genomics and causal inference, specifically the analysis of large-scale CRISPR perturbation data to illuminate gene regulation and other complex biological processes. Prior to graduate school, I worked with Prof. Qiongshi Lu, developing methods for genetic epidemiology and polygenic risk scoring using biobank-scale data.

Education

• PhD · Biomedical Data Science, University of Wisconsin–Madison (2023–Present)
  Advisors: Prof. Sündüz Keleş and Prof. Hyunseung Kang
• BS · Mathematics and Statistics, University of Wisconsin–Madison (2019–2023)
  Advisor: Prof. Qiongshi Lu

Experiences

• Graduate Research Assistant, Keleş Research Group, UW–Madison (2024–Present)
• Undergraduate Researcher, Lu Laboratory, UW–Madison (2021–2023)

Selected Publications

* First author with equal contribution; dagger indicates last author with equal contribution.

• 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%).
• Park, K., Sun, Z., Liao, R., Bresnick, E. H., Keleş, S. (2025). Systematic Background Selection for Enhanced Contrastive Dimension Reduction. bioRxiv, 2025-05.
• 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, 25(1): 260.
• 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, 56(11): 2361–2369.
• 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, 1–8.
• Sun, Z., Wu, Y., Fletcher, J., Lu, Q. (2023). Pervasive biases in GWAS using family history of Alzheimer’s disease as proxy phenotypes. Alzheimer’s & Dementia, 19: e080435.
• 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, 60(6): 1649–1664.
• 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, 17: 101018.

Full list: Google Scholar profile.

Invited Talks and Presentations

• 2025 · ACIC — Poster and lightning talk: Estimating Gene Regulatory Networks Using Perturb-seq Data.
• 2024 · ASHG — Poster: Pervasive Biases in GWAS Using Family History of Alzheimer’s Disease.
• 2024 · IGSS — Talk: Pervasive Biases in GWAS Using Family History of Alzheimer’s Disease.
• 2024 · TAGC — Talk: Pervasive Biases in GWAS Using Family History of Alzheimer’s Disease.
• 2022 · ASHG — Poster: Pervasive Biases in GWAS Using Family History of Alzheimer’s Disease.

Honors and Affiliations

• 2022 · Wisconsin Hilldale Undergraduate/Faculty Research Fellowship (advisor: Qiongshi Lu)
• 2025 · Society for Causal Inference (SCI) — Member