Di Wu

I am a second-year Ph.D. student in the Applied Mathematics & Statistics, and Scientific Computation (AMSC) program at the University of Maryland, College Park, a program whose name is a good summary of my research interests. I am fortunate to be advised by Prof. Haizhao Yang. I also work closely with Prof. Ling Liang. I received my bachelor's and master's degrees in Computational Mathematics from Wuhan University, under the guidance of Prof. Yuling Jiao and Prof. Xiliang Lu. I also spent time as a research intern at JD Explore Academy, where I was mentored by Prof. Li Shen. I am interested in a wide range of topics related to applied mathematics and machine learning. My recent research focuses on Bayesian statistics, optimization, and reinforcement learning. e-mail: dwuwd 'at’ umd 'dot’ edu

Research

• Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions
  Di Wu, Ling Liang, Haizhao Yang
  arXiv preprint, 2026

• Randomized Subsystem Descent for Fermion-to-Qubit Mapping
  Gengzhi Yang, Di Wu, Haizhao Yang, Xiaodi Wu, Ji Liu
  arXiv preprint, 2026

• PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport
  Di Wu, Ling Liang, Haizhao Yang
  arXiv preprint, 2025

• Neural Network Approximation for Pessimistic Offline Reinforcement Learning
  Di Wu, Yuling Jiao, Li Shen, Haizhao Yang, Xiliang Lu
  Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024

Teaching

Teaching Assistant

University of Maryland, College Park
(leading discussion sections, holding office hours, and grading)

• MATH 240: Introduction to Linear Algebra

• STAT 400: Applied Probability and Statistics

• AMSC 460: Computational Methods

Earlier TA Experience

Wuhan University: Teaching assistant for graduate courses including Numerical Analysis, Statistical Computing, High Dimensional Data and Machine Learning, Theory and Algorithms of Machine Learning, and Advanced Engineering Mathematics.

National Tianyuan Mathematics Center: Teaching assistant for the summer school on ‘‘Mathematical Theory and Applications of Deep Learning’’.

Activities

Talks

• Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions
  Sayas Numerics Day (formerly DelMar Numerics Day), May 2026

• PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport [Slide]
  Department of Mathematics, George Washington University, February 2026

• Neural Network Approximation for Pessimistic Offline Reinforcement Learning [Slide]
  School of Mathematics and Statistics, Wuhan University, March 2024

Professional Services & Activities

• Review Panelist, NASA Research Proposal Review

• Co-organizer, Minisymposium on Optimal Transport, SIAM MDS 2026 (link)

Awards & Honors

• Mark E. Lachtman Award, University of Maryland, 2026

• Dean's Fellowship, University of Maryland, 2025, 2026

Earlier Awards & Honors

• Lei Jun Educational Fund (around 5,000 USD), Wuhan University

• First-Class Scholarship (Undergraduate & Graduate), Wuhan University

• First Prize, Contemporary Undergraduate Mathematical Contest in Modeling (Team Leader), CSIAM

• Outstanding Graduate, Wuhan University

• Merit Student (3 times), Wuhan University

• First Prize, National High School Mathematics Competition

• First Prize, National High School Physics Competition