Jiang Sheng's research interests primarily lie in Bayesian nonparametrics, encompassing both theoretical and computational aspects, as well as applications to real-world data. His goal is to develop novel methods for understanding large, complex datasets in scientific applications, aiming to strike a balance between modeling flexibility and scientific interpretability. Before joining CUHK-Shenzhen, Jiang served as a visiting assistant professor in the Department of Statistics at the University of California, Santa Cruz. He received his statistics training at Duke University, where his PhD advisor was Professor Surya T. Tokdar. During his postdoctoral work, he collaborated with Professor Alex Volfovsky and Professor Galen Reeves. Prior to his studies in statistics, Jiang studied economics at Tsinghua University.