Hi, my name is Xutong (James) Liu. I am now a Tenure-Track Assistant Professor at the University of Washington, affiliated with the Department of Computer Science & Systems at the Tacoma School of Engineering & Technology. At UW, I build the Learning, Evaluation, and Advanced Decision-making (LEAD) research lab and actively recruiting Ph.D. students, master students, and undergraduate interns, check group information for details if you are interested in joining us.

Previously, I was a postdoctoral researcher in LIONS research group at Carnegie Mellon University, fortunately advised by Prof. Carlee Joe-Wong. Before that, I was a visiting postdoc in SOLAR Lab at the University of Massachusetts Amherst, fortunately advised by Prof. Mohammad Hajiesmaili, and a postdoctoral fellow in ANSR Lab at the Chinese University of Hong Kong (CUHK), advised by Prof. John C.S. Lui (IEEE/ACM Fellow). I received my Ph.D. degree from the Computer Science and Engineering Department at CUHK in 2022, proudly advised by Prof. John C.S. Lui. Prior to that, I received my bachelor’s degree with an honored rank (top 5%) from the University of Science and Technology of China (USTC) in 2017.

Research

My research focuses on developing structure-aware reinforcement learning (RL) and online learning algorithms that leverage inherent action, feedback, and agent structures—such as smoothness, sparsity, and clustering—to enable data-efficient, scalable, and robust decision-making. I aim to bridge theory and practical applications for cost-effective LLM serving (rounting/caching/domain adaptation), mobile/edge/cloud co-optimization (VR/AR immersive computing, CDNs), and robust multi-agent learning systems (federated learning systems), guided by three core questions:

1. Data Efficiency: How much offline and/or online data is needed to identify near-optimal policies?
2. Scalability: How can we design algorithms that scale efficiently across high-dimensional action spaces and multiple agents?
3. Robustness: How can learning remain stable and adaptive in dynamic, uncertain, and heterogeneous learning environments?

My recent projects focus on building:

🚀 Structure-aware Online/Reinforcement Learning (RL):

• Hybrid Reinforcement Learning with Fused Offline-Online Data:
  [NeurIPS ‘25], [ICML ‘25b], [KDD ‘25], [arXiv ‘25]

• Reinforcement Learning with Large Action Spaces:
  [ICML ‘25a], [ICML ‘24] [NeurIPS ‘22], [ICML ‘21, 🎤️Long Oral]
• Generalizable Combinatorial Online Learning with Function Approximation:
  [SIGMETRICS ‘25, 🏆Best Paper Runner-Up], [INFOCOM ‘24], [ICML ‘23]
• Robust Multi-agent Reinforcement Learning in Heterogeneous and Unreliable Environments:
  [IEEE TON ‘26]), ICLR ‘25], [SIGMETRICS ‘25], [INFOCOM ‘25], [AAAI ‘24], [NeurIPS ‘23], [UAI ‘23], [AISTATS ‘23], [ICLR ‘23], [UAI ‘23]

🛜 Learning and Optimization for Networked AI Systems:

• Cost-effective Large Language Model (LLM) Caching/Routing/Adaptation Systems:
  [AAAI ‘26], [INFOCOM ‘26], [INFOCOM ‘26], [arXiv ‘25a], [arXiv ‘24]
• Edge/Cloud Computing, Multimedia Networking, and IoT Systems:
  [IEEE TMC’ 26]), IEEE/ACM TON], [ACM MM ‘24], [INFOCOM ‘23], [INFOCOM ‘18], [IEEE TMC]
• Conversational Recommendation Systems and Social Network Marketing:
  [KDD ‘25], [AAAI ‘23], [AISTATS ‘22], [IEEE TKDE]

News

• April 2026: My incoming Ph.D. student, Junkai Wang from Fudan University, received his first journal acceptance from IEEE Transactions on Networking (TON). Congratulations, Junkai!
• April 2026: My undergraduate intern Jingyuan Liu from Nanjing University is admitted to the IEOR PhD program @ UC Berkeley. Congratulations, Jingyuan!
• April 2026: I am invited as a TPC for IEEE INFOCOM 2027 and ACM Mobihoc 2026.
• Dec. 2025: Our works on LLM caching, MoE model merging, and constraint-aware combinatorial bandits have been accepted by INFOCOM 2026.
• Nov. 2025: I am invited as a web chair for the 32nd International European Conference on Parallel and Distributed Computing (Euro-Par 2026).
• Sept. 2025: I join the University of Washington - Tacoma as a Tenure-Track Assistant Professor In CSS.
• June. 2025: I am invited as a TPC for ACM SIGMETRICS 2026 and ACM e-Energy 2026!
• May. 2025: Our paper “Combinatorial Logistic Bandits” has been selected as one of the Best Paper Runner-Up at SIGMETRICS 2025!
• Dec. 2024: We are excited to co-organize the 3rd Annual Workshop on Learning-Augmented Algorithms: Theory and Applications at ACM SIGMETRICS 2025. The workshop will take place at Stony Brook University, New York, USA. For more details, visit the official workshop website.
• Sept. 2024: I join Carnegie Mellon University as a postdoctoral researcher advised by Prof. Carlee Joe-Wong.
• Oct. 2023: I am visiting the University of Massachusetts Amherst as a visiting scholar advised by Prof. Mohammad Hajiesmaili.
• April. 2023: I am awarded RGC Postdoctoral Fellowship (one of 50 awardees globally)!