Xinyi (Cindy) Zhang

I’m a postdoctoral researcher in biostatistics at Johns Hopkins University, where I’m fortunate to be mentored by Professors Brian Caffo and Zheyu Wang. I obtained my Ph.D. from the Department of Statistical Sciences at the University of Toronto in 2023, under the supervision of Professors Dehan Kong, Linbo Wang, and Stanislav Volgushev.

My research focuses on developing statistical and machine learning methods for large-scale and complex data. Driven by key areas including causal discovery from observational studies, neuroimaging analysis, and multi-view data analysis for personalized healthcare, I work on real-world data that features high-dimensionality, massive volume, complex correlation structures, unmeasured confounders, and incompleteness. Recently, I’ve also become interested in the application of deep learning methods to brain imaging for disease detection and monitoring.

A snapshot of my methodological research:

Education

• Ph.D. in Statistics, University of Toronto, 2018–2023.
• M.S. in Statistics, University of California, Berkeley, 2017–2018.
• B.Sc. in Mathematical Application in Economics and Finance, University of Toronto,
  2014–2017.
• B.Sc. in Statistics, University of Toronto, 2014–2017.

Awards

• Ontario Trillium Scholarship, 2018–2022
• Statistical Society of Canada (SSC) Annual Meeting Student Travel Grant, 2022
• School of Graduate Studies (SGS) Conference Grant, University of Toronto, 2020
• Department Citation Award in the Statistics Master’s Program, UC Berkeley, 2018
• ASA Nonparametric Statistics Section Student Paper Awards Finalist, 2018
• Dean’s list Scholar, University of Toronto, 2015–2017
• In-course scholarship, New College, University of Toronto, 2017