🍾 Biography

Hi! I’m a first-year PhD student in the Department of Electrical and Computer Engineering (ECE) at The University of Hong Kong (HKU), under the supervision of Prof. Edith Cheuk Han Ngai. Previously, I obtained my M.E. degree in Computer Science and Technology in the School of Artificial Intelligence (SAI) at Sun Yat-sen University (SYSU), supervised by Prof. Xuehe Wang and B.E. degree in Mechanical Design, Manufacturing and Automation from the University of Electronic Science and Technology of China (UESTC) in 2022.

My research interests include Large Language Models (LLMs), Agents, Distributed Optimization (e.g., Federated Learning), etc.

📢 I’m actively looking forward to collaborating with self-motivated researchers in the field of LLMs, Agentic AI, etc. Feel free to drop me an email or contact me via WeChat if you’re interested!

🔥 News

📝 Selected Publications [Full List]

(* = Equal Contribution, † = Corresponding Author)

EMNLP'2026 Findings

Leaving the Past Behind: Breaking Personalization Inertia in Long-Term LLM Agents

• Wenhao Yuan, Chenchen Lin, Jian Chen, Weijie Liu, Jinfeng Xu, Shuo Yang, Edith Cheuk Han Ngai
• [Paper]

CIKM'2026

When Is Shallow Enough? Adaptive Split Federated Learning with Client-Specific Sufficiency Estimation

• Wenhao Yuan^*, Chenchen Lin^*, Wentao Hu, Jian Chen, Jinfeng Xu, Shujie Li, Edith Cheuk Han Ngai
• [Paper]

ECCV'2026

Fisher-Routed Mixture of Experts for Federated Class-Incremental Learning

• Wenhao Yuan, Chenchen Lin, Jian Chen, Jinfeng Xu, Zewei Liu, Edith Cheuk Han Ngai
• [Paper]

ACL'2026 Main

Verify Before You Commit: Towards Faithful Reasoning in LLM Agents via Self-Auditing

• Wenhao Yuan, Chenchen Lin, Jian Chen, Jinfeng Xu, Xuehe Wang, Edith Cheuk Han Ngai
• [Paper]

KnowFM@ACL'2026

Belief-Guided Inference Control for Large Language Model Services via Verifiable Observations

• Wenhao Yuan, Chenchen Lin, Jian Chen, Jinfeng Xu, Shuo Yang, Edith Cheuk Han Ngai
• [Paper]

CIKM'2025(Oral)

Aggregated Gradients-based Adaptive Learning Rate Design in Federated Learning

• Wenhao Yuan, Xuehe Wang
• [Paper]

ToN'2025

A Game-Theoretic Framework for Privacy-Aware Client Sampling in Federated Learning

• Wenhao Yuan, Xuehe Wang
• [Paper]

TMC'2024

Adaptive Federated Learning via New Entropy Approach

• Shensheng Zheng^*, Wenhao Yuan^*, Xuehe Wang, Lingjie Duan
• [Paper]

📖 Educations

The University of Hong Kong

2025.09 - current

PhD, Department of Electrical and Computer Engineering.

Sun Yat-sen University

2022.09 - 2025.06

M.E., School of Artificial Intelligence.

University of Electronic Science and Technology of China

2018.09 - 2022.06

B.E., School of Mechanical and Electrical Engineering.

🎖 Honors and Awards

• ICML’2026 Silver Reviewer
• SYSU Excellent Graduate (2025)
• National Scholarship (2024)
• Excellent Graduate Academic Scholarship (2022-2024)
• SYSU Excellent Teaching Assistant (2024)
• The 19th China Post-Graduate Mathematical Contest in Modeling, National Third Prize (Dec. 2022)

💁 Academic Service

Journal Reviewer

• Transactions on Machine Learning Research (TMLR)
• IEEE Transactions on Mobile Computing (TMC)
• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• IEEE Transactions on Parallel and Distributed Systems (TPDS)
• IEEE Transactions on Industrial Informatics (TII)
• IEEE Transactions on Communications (TCOM)
• Future Generation Computer Systems (FGCS)

Conference Reviewer

• International Conference on Machine Learning (ICML), 2026
• ACM International Conference on Multimedia (ACM MM), 2026
• International Joint Conference on Neural Networks (IJCNN), 2025
• IEEE Congress on Evolutionary Computation (CEC), 2024-2025

Conference Committee Service

• Program Committee & Track Chair @ IEEE CloudCom 2025
• Program Committee @ AAAI 2026-2027
• Program Committee @ IJCAI-ECAI 2026

🧑🏻‍🏫 Teaching Assistant

• Distributed systems (ELEC7083), HKU, Jan, 2026.

💻 Internships

• 2025.07 - 2025.09, Lorem, China.

⛰️ Life beyond Research