CV
Education
- B.S. in Applied Mathematics, University of Science and Technology of China (USTC), 2015-2019
- M.S. in Electrical Engineering, Texas A&M University, 2019-2022
- Ph.D in Computer Science, Texas A&M University, 2023-present
Selected Research Experience
My research spans optimization theory, machine learning, and practical AI systems, with focus on fairness, efficiency, and multi-agent learning.
- Fall 2025 – present: Multi-agent Joint Training in Large Language Models
- Summer 2025 – present: Quantization in Large Language Models
- Fall 2023 – present: Fairness in Submodular Optimization
- Summer 2022 – Spring 2023: Uncertainty in Motion Planning for Autonomous Driving
- Fall 2021 – Summer 2022: Goal-oriented Reinforcement Learning
- Fall 2019 – Fall 2020: Partial Ranking Data Aggregation
Work Experience
- May 2025 – Aug 2025: Machine Learning Engineer Intern, Meta
Technical Skills
- Programming: Python, C/C++, MATLAB, Mathematica, LaTeX
- Machine Learning: PyTorch, TensorFlow, Scikit-Learn, Transformers, Reinforcement Learning
- Optimization: Linear/Integer Programming (CPLEX, CVXPY), Convex Optimization, Submodular Optimization, Bayesian Optimization
- Data Tools: SQL, Pandas, NumPy, Dynamic Dashboards
Honors and Awards
- NeurIPS 2024 Travel Grant Award
Talks and Presentations
- Fall 2024: “Threshold Adaptive Sampling for Submodular Maximization under Bandit Feedback” (AI Seminar, Texas A&M University)
Selected Publications
For a complete list of publications, please see my Google Scholar profile.
2025
- W. Chen, S. Xing, S. Zhou, V. Crawford. “Fair Submodular Cover.” ICLR 2025.
- W. Chen, V. Crawford. “Linear Submodular Maximization with Bandit Feedback.” AISTATS 2025.
- W. Chen, S. Xing, V. Crawford. “Adaptive Threshold Sampling for Pure Exploration in Submodular Bandits.” UAI 2025.
2024
- W. Chen, V. Crawford. “Bicriteria Approximation Algorithms for the Submodular Cover Problem.” NeurIPS 2023.
2022
- W. Chen, C. Tian. “A New Approach to Compute Information Theoretic Outer Bounds and Its Application to Regenerating Codes.” ISIT 2022.
- W. Chen, R. Zhou, C. Tian, C. Shen. “On Top-k Selection from m-wise Partial Rankings via Borda Counting.” IEEE Transactions on Signal Processing, Vol. 70, pp. 2031–2045, 2022.
- M. Yin*, W. Chen*, M. Wang, Y. Wang. “Offline Stochastic Shortest Path: Learning, Evaluation and Towards Optimality.” UAI 2022. (*Equal contribution)
Teaching
Academic Service
- Reviewer: NeurIPS 2024, 2025; ICLR 2025, 2026; UAI 2023, 2024
