Xinkai Zhou (周新凯)

I am a postdoctoral fellow in the Department of Biostatistics at Johns Hopkins University, mentored by Ciprian Crainiceanu.

My research focuses on developing flexible and scalable statistical modeling and inference tools for large-scale, high-dimensional, and repeatedly collected modern health data, with applications to electronic medical records, wearable computing, and many other fields.

Prior to joining Hopkins, I received PhD in Biostatistics from UCLA, mentored by Hua Zhou. Before that, I was a senior statistician at the UCLA Department of Medicine Statistics Core led by David Elashoff. I collaborated with investigators from the Department of Medicine, Stein Eye Institute, Jonsson Comprehensive Cancer Center, and Cedars-Sinai Medical Center on a variety of clinical trials and biomedical research projects.

In my free time, I enjoy playing soccer and reading history books. I am also the founder and co-host of the Two Nearest Neighbors podcast (link to: Spotify, Apple Podcast) with Nicholas Marco, where we talk to professors about current topics in statistics, machine learning, and big data.

Honors and Awards

• Biostatistics Outstanding Student Award, UCLA, June, 2023
• Delta Omega Honorary Society in Public Health, June, 2023
• ASA Student Paper Award, Sections on Computing and Graphics, August, 2022
• Eugene and Sallyann Fama Fellowship, UCLA, June, 2020
• Graduate Summer Research Fellowship, UCLA, 2019 and 2020