Yanjun Han

Assistant Professor of Mathematics and Data Science, Courant Institute of Mathematical Sciences, Center for Data Science, and Computer Science Department (affiliated), New York University I received my B.E. in Electronic Engineering from Tsinghua University in Jul 2015, and my M.S. and Ph.D. in Electrical Engineering from Stanford University in Aug 2021, under the supervision of Tsachy Weissman. I was a postdoctoral scholar at the Simons Institute for the Theory of Computing, University of California, Berkeley in 2021-22, and a Norbert Wiener postdoctoral associate at the Statistics and Data Science Center (SDSC) in MIT IDSS in 2022-23. I am broadly interested in the mathematics of data science, including statistics, learning theory, bandits, and information theory.

Recent papers

• Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability
  with Fan Chen, Dylan J. Foster, Jian Qian, Alexander Rakhlin, and Yunbei Xu, NeurIPS 2024, to appear (Spotlight).

• Approximate independence of permutation mixtures
  with Jonathan Niles-Weed, Aug 2024. (slides)

• Causal Inference with High-dimensional Discrete Covariates
  with Zhenghao Zeng, Sivaraman Balakrishnan, and Edward H. Kennedy, May 2024.

• Prediction from compression for models with infinite memory, with applications to hidden Markov and renewal processes
  with Tianze Jiang and Yihong Wu, COLT 2024.

• Online Estimation via Offline Estimation: An Information-Theoretic Framework
  with Dylan J. Foster, Jian Qian, and Alexander Rakhlin, NeurIPS 2024, to appear.

• Stochastic contextual bandits with graph feedback: from independence number to MAS number
  with Yuxiao Wen and Zhengyuan Zhou, NeurIPS 2024, to appear.

• Covariance alignment: from maximum likelihood estimation to Gromov--Wasserstein
  with Philippe Rigollet and George Stepaniants, Nov. 2023.

Contact

Email: yanjunhan [at] nyu [dot] edu

Office: WWH 1110 or CDS 705