Bingjing Tang

Postdoctoral Researcher
Department of Statistics, Stanford University

I work on Bayesian nonparametrics, generative modeling, coalescent models, Markov chain Monte Carlo, variational inference, and missing data. I have temporarily moved from Stanford Statistics to UCSF Biostatistics, and my previous Stanford email has not worked since December 2025.

I completed my PhD in Statistics at Purdue University under the supervision of Vinayak Rao. Before that, I received a master's degree from JHU AMS and an undergraduate degree in Management Information Systems, with a minor in English Literature, from Beijing Language and Culture University.

Publications

• Group-representative functional network estimation from multi-subject fMRI data via MRF-based image segmentation.
  Bingjing Tang, Aditi Iyer, Vinayak Rao, Nan Kong. Computer Methods and Programs in Biomedicine, 2019.
• Marginally constrained nonparametric Bayesian inference through Gaussian processes.
  Bingjing Tang, Vinayak Rao. Journal of Statistical Planning and Inference, 2024.
• Exact Bayesian Gaussian Cox processes using random integrals.
  Bingjing Tang, Julia Palacios. SIAM Journal on Mathematics of Data Science, 2026.
• Score Correction for Generative Models with Probabilistic Constraints.
  Shishang Wu, Bingjing Tang, Vinayak Rao. ICML, 2026.

Contact

Email: bingjing.tang@gmail.com
GitHub: github.com/bingjingle

My favourite

Writers: F. Scott Fitzgerald, Eileen Chang.
Poets: Lake District poets (William Wordsworth).
Music: Impressionism (Claude Debussy).
Painting: Impressionism (Jean Frédéric Bazille).
Illustration: Jean-Jacques Sempé.