Portrait of Ziang Zhang

Ziang Zhang, Ph.D.

Postdoctoral scholar, University of Chicago.

[News: Starting in January 2027, I will join The Hong Kong University of Science and Technology (Guangzhou) as an Assistant Professor in the Data Science and Analytics (DSA) Thrust. I am looking for self-motivated PhD and master's students starting in Spring or Fall 2027. Other job positions, including research assistant and postdoc, are also available. Please contact me if you are interested!]

Bio

I am a postdoctoral scholar at the University of Chicago, supervised by Dr. Matthew Stephens. Previously, I completed my PhD in the Department of Statistical Sciences at the University of Toronto, supervised by Drs. Patrick Brown and Jamie Stafford. Before my PhD study, I completed my undergraduate study also at University of Toronto, with a specialist degree in statistics.

My research interests span Bayesian inference and computation, Gaussian process methodology, functional data analysis, and statistical genetics. My work develops interpretable statistical methods motivated by interdisciplinary scientific problems and applies them to complex datasets, particularly those arising in biology and genetics.

Education

  • PhD in Statistics, 2020 - 2024, University of Toronto
  • HBSc in Statistics, 2016 - 2020, University of Toronto

Highlighted Work by Research Direction

For the full publication list, see the Research page.

Bayesian Method

Zhang, Z., Carbonetto, P., & Stephens, M. (2026). Empirical Bayes Shrinkage of Functional Effects, with Application to Analysis of Dynamic eQTLs. Under revision at Journal of the American Statistical Association.

Gaussian Process Method

Zhang, Z., Stringer, A., Brown, P., & Stafford, J. (2024). Model-based Smoothing with Integrated Wiener Processes and Overlapping Splines. Journal of Computational and Graphical Statistics.

Statistical Genetics

Zhang, Z., Lawless, J., Paterson, A. D., & Sun, L. (2025). Detecting latent interaction effects when analyzing binary traits. PLOS Genetics.