Yu-Chien Ning's Personal Website Yu-Chien Ning's Personal Website

Bo Y.-C. Ning 甯宇謙

Postdoctoral Research Fellow
T. H. Chan School of Public Health
Harvard University
 Boston, MA, USA
 Google Scholar


Dr. Bo (Yu-Chien) Ning is a Research Fellow at Harvard T.H. Chan School of Public Health working with Molin Wang. Before Harvard, he worked at the LPSM (a department has a rich history with its inception tracing back to Denis Siméon Poisson) of Sorbonne Université in Paris, and in the Department of Statistics at the University of California Davis and Yale University. He received his Ph.D. in Statistics from North Carolina State University in 2018.

Dr. Ning holds a broad interest in statistics and data science. He has spent years investigating frequentist properties of Bayesian machine learning methods for complex data, including minimax estimation and uncertainty quantification of various nonparametric and high-dimensional Bayesian models as well as large-scale multiple testing problems. His research style is highly influenced by two amazing researchers and advisors in Bayesian statistical theory, Subhashis Ghoshal and Ismael Castillo. He is also highly motivated to work with applied scientists in addressing challenging problems in data science, including astronomy, economics, sociology, and public health.

Research interests

Statistical theory, Data science, Bayesian machine learning


  • 05/13/2024 My paper, "Spike and slab Bayesian sparse principal component analysis", co-authored with Ning Ning was published on Statistics and Computing.
  • 05/06/2024 I will give a talk at the Department of Economics at Harvard University
  • 07/13/2023 My new paper on "Empirical Bayes multiple testing for sparse binary data" is available on arXiv! [Link].
  • 06/14/2023 My paper, "Bayesian multiscale analysis of the Cox model", co-authored with Ismael Castillo was accepted by Bernoulli!
  • 01/06/2023 My master's student Ms. Shuyu Guo developed an R package for computing a Bayesian high-dimensional errors-in-variables model with spike and slab prior---link to the package: https://github.com/ShuyuG/MUSS-package
  • 12/26/2022 I will give a talk at the Institute of Statistical Science Academia Sinica in Taipei, Taiwan!
  • 10/24/2022 I am attending the 13th International Conference on Bayesian nonparametrics in Chile
  • 10/03/2022 I am attending the Non-Linear and High Dimensional Inference workshop at Institut Henri Poincare in Paris
  • 09/29/2022 I am excited to present my work on the uncertainty quantification of the Bayesian Cox model at BASICS Workshop.
  • I will visit LPSM @ Sorbonne Universite, Paris, France from Sep 19 to Oct 18, feel free to contact me if you are in Europe and want to chat in person!
  • 09/06/2022 I am at the 2022 O'Bayes Meeting @ UC Santa Cruz
  • 07/01/2022 I won an ISBA Poster Award, see [Poster]
  • 06/22/2022 I am at the Bayesian Young Statistians Meeting (June 22-23) and ISBA World meetings (June 26-July 1)
  • 05/30/2022 Details of my statistical machine learning course teaching materials can be found [here]
  • 05/25/2022 My new paper "Bayesian Multiscale Analysis of the Cox Model" is available on arXiv. [Link].