Luhuan Wu

LuhuanWu-Photo.JPG

I am an associate research scientist in the Center for Computational Mathematics at the Flatiron Institute. I will be joining the Department of Applied Mathematics and Statistics at Johns Hopkins University as an Assistant Professor in July, 2026.

I did my Ph.D. in Statistics at Columbia University, supervised by John Cunningham and David Blei. Before that, I received an M.S. in Data Science also from Columbia, and a B.S. in Mathematics from Nanjing University.

My research focuses on generative modeling, approximate inference, sampling and Bayesian methods. Here is my CV.

Selected Publications

  1. Reverse Diffusion Sequential Monte Carlo Samplers
    Luhuan Wu, Han Yi, Christian Naesseth, and John Cunningham
    In Conference on Neural Information Processing Systems, 2025
  2. Bayesian Invariance Modeling of Multi-Environment Data
    Luhuan Wu, Mingzhang Yin, Yixin Wang, John Cunningham, and David Blei
    arXiv preprint , 2025
  3. Posterior Uncertainty Quantification in Neural Networks using Data Augmentation
    Luhuan Wu and Sinead A Williamson
    In International Conference on Artificial Intelligence and Statistics, 2024
  4. Practical and Asymptotically Exact Conditional Sampling in Diffusion Models
    Luhuan Wu Wu, Brian Trippe, Christian Naesseth, David Blei, and John Cunningham
    In Conference on Neural Information Processing Systems, 2023
  5. Variational Nearest Neighbor Gaussian Process
    Luhuan Wu, Geoff Pleiss, and John Cunningham
    In International Conference on Machine Learning, 2022
  6. Bias-free Scalable Gaussian Processes via Randomized Truncations
    Andres Potapczynski, Luhuan Wu, Dan Biderman, Geoff Pleiss, and John P Cunningham
    In International Conference on Machine Learning, 2021
  7. Hierarchical Inducing Point Gaussian Process for Inter-domian Observations
    Luhuan Wu, Andrew Miller, Lauren Anderson, Geoff Pleiss, David Blei, and 1 more author
    In International Conference on Artificial Intelligence and Statistics, 2021
  8. Variational Objectives for Markovian Dynamics with Backward Simulation
    Antonio Khalil Moretti, Zizhao Wang, Luhuan Wu, Iddo Drori, and Itsik Pe’er
    In European Conference on Artificial Intelligence, 2020