Sheng Jiang 江声

Welcome to my website! 

My research interests primarily lie in Bayesian nonparametrics, encompassing both theoretical and computational aspects, as well as applications to real-world data. My goal is to develop novel methods for understanding large, complex datasets in scientific applications, striking a balance between modeling flexibility and scientific interpretability. Specifically, I have been working on Bayesian nonparametric methods with Gaussian process priors, variable/model selection, variational Bayes, Bayesian (dynamic) network models, and oceanographic flow cytometry data analysis.

Before joining CUHK-Shenzhen, I served as a Visiting Assistant Professor in the Department of Statistics at the University of California, Santa Cruz. Before moving to Santa Cruz, I received my statistics training at Duke. My PhD advisor is Professor Surya T. Tokdar; I also worked with Professor Alex Volfovsky and Professor Galen Reeves during my post-doc.  Prior to studying statistics, I studied economics at Tsinghua University. 

Here are my resume and Google Scholar. 

I'm looking for motivated students to work with me! 

For prospective PhD students interested in the computational, modeling, and/or theoretical aspects of Bayesian statistics, I warmly 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 MPhil students to join us in addressing critical challenges in urban transportation. Research topics include, but are not limited to, traffic modeling at both individual and city scales, data-driven analysis of travel behavior, and optimization of urban traffic systems using advanced computational and AI techniques.