I am a postdoctoral research fellow in the Electrical Engineering and Computer Science Department at the University of Michigan, Ann Arbor, advised by Prof. Lei Ying. Previously, I completed my Ph.D. in the same department, also advised by Prof. Ying. I received my master's and bachelor's degrees from Sun Yat-sen University, Guangzhou, China.
My research interests lie in joint online learning and decision making problems, which include recommendation, queueing, scheduling, matching, and pricing in unknown environments.
[Nov-2025] I will attend NeurIPS 2025 in San Diego and present our work Near-Optimal Regret-Queue Length Tradeoff in Online Learning for Two-Sided Markets. Dec 3 (Wednesday) 4:30-7:30 p.m., Exhibit Hall C,D,E #916.
[Oct-2025] I will attend INFORMS Annual Meeting 2025 in Atlanta and present our work on Online Learning for Two-Sided Markets in the Job Market Showcase cluster. Session: Learning, Ranking, and Selection. Oct 26 (Sunday), 2:45-4:00 pm, Building A Level 3 A315.
[1] Zixian Yang, Sushil Mahavir Varma, and Lei Ying, "Near-Optimal Regret-Queue Length Tradeoff in Online Learning for Two-Sided Markets," in NeurIPS 2025 (acceptance rate 25%). link of the paper
[2] Zixian Yang and Lei Ying, "Learning-based pricing and matching for two-sided queues", Stochastic Systems, 2025. link of the paper
[3] Zixian Yang, R. Srikant, and Lei Ying, "Learning While Scheduling in Multi-Server Systems with Unknown Statistics: MaxWeight with Discounted UCB," in AISTATS 2023 (acceptance rate 29%). link of the paper
[4] Zixian Yang, Xin Liu, and Lei Ying. "Exploration. Exploitation, and Engagement in Multi-Armed Bandits with Abandonment." Journal of Machine Learning Research, 2024. link of the paper
[5] Honghao Wei, Zixian Yang, Xin Liu, Zhiwei Qin, Xiaocheng Tang, and Lei Ying. "A Reinforcement Learning and Prediction-Based Lookahead Policy for Vehicle Repositioning in Online Ride-Hailing Systems." IEEE Transactions on Intelligent Transportation Systems, 2023. link of the paper
Zixian Yang, R. Srikant, and Lei Ying, “Learning While Scheduling in Multi-Server Systems with Unknown Statistics: MaxWeight with Discounted UCB,” 2023, available at https://arxiv.org/abs/2209.01126v3