Sheng Jiang 江声

Hello there. Welcome to my website! 

I am a tenure-track Assistant Professor in the School of Data Science at The Chinese University of Hong Kong, Shenzhen. My research focuses on Bayesian nonparametrics and computational Bayesian statistics. I develop flexible, scalable methods for analyzing large and complex datasets, with recent work motivated by applications in traffic flow networks and cryo-electron microscopy (cryo-EM). My work on Bayesian nonparametric methods with Gaussian process priors has appeared in The Annals of Statistics and the Journal of the American Statistical Association. 

Before joining CUHK-Shenzhen, I was a Visiting Assistant Professor in the Department of Statistics at the University of California, Santa Cruz. Prior to that, I earned my Ph.D. in Statistical Science from Duke University, advised by Professor Surya T. Tokdar. After my Ph.D., I remained at Duke for a postdoctoral appointment jointly advised by Professors Tokdar and Alex Volfovsky, during which I also collaborated with Professor Galen Reeves. 

Prior to studying statistics, I studied economics at Tsinghua University. 

Here are my resume, Google Scholar, and GitHub. 

We are looking for motivated students! 

For prospective PhD students interested in the application, computational and/or theoretical aspects of Bayesian nonparametrics, I encourage you to reach out. Please send me an email that includes a brief overview of your research interests, relevant experience, and, if available, a short writing sample or statement of purpose. I look forward to learning more about your goals and how we might collaborate. 

We are currently seeking motivated graduate students to join us in addressing critical challenges in urban transportation systems. We focus on building intelligent systems that model, predict, and optimize urban mobility, from multi-agent traffic flows to human travel behaviors, enhancing efficiency, safety, resilience, and sustainability. Our work spans traffic flow modeling and forecasting, public transit network evaluation, travel mode choice modeling, and the development of “digital twin” platforms for data-driven and model-based policy-making.  

Websites: CUHK(SZ) website (official), Github (more detailed, maintained periodically) 

To apply, please follow the instructions on this page.