Sheng Yue (岳晟)

Sheng Yue (岳晟)

Associate Professor

Welcome to my homepage! I am currently an associate professor in the School of Cyber Science and Technology at Sun Yat-sen University. I was a postdoctoral researcher in the Department of Computer Science Technology at Tsinghua University from 2023 to 2024. I received my Ph.D. from the School of Computer Science and Engineering (advised by Prof. Ju Ren) at Central South University. I was a visiting Ph.D. student at the Davis AI, Robotics, and Edge (DARE) Lab (from 2020 to 2022, advised by Prof. Junshan Zhang) and Decision Intelligence Lab (Fall 2018, advised by Prof. Longbo Huang). My research is centered on the field of decision intelligence. Currently, I am exploring reinforcement learning, continual learning, LLM optimization, and LLM agents.

Students (招生): If you are interested in our research directions, please contact me: yuesh5 AT mail DOT sysu DOT edu DOT cn.

Recent News

  • [01/2026] 🎉 Paper “Less Is More: Clustered Cross-Covariance Control for Offline RL” is accepted to ICLR’25. Congrats to Nan!
  • [01/2026] 🎉 Paper “Context Learning for Multi-Agent Discussion” is accepted to ICLR’25. Congrats to Xingyuan!
  • [06/2025] 🎉 Paper “FocusX: All-in-Focus Image Synthesis for Dynamic Scenes on Mobile Devices”, is accepted to MobiCom’25. Congrats to Jinrui!
  • [02/2025] 🎉 Paper “AugFL: Augmenting Federated Learning with Pretrained Models” is accepted to IEEE Transctions on Networking. Congrats to Zerui!
  • [01/2025] 🎉 Paper “DualRec: A Collaborative Training Framework for Device and Cloud Recommendation Models” is accepted to IEEE Transctions on Mobile Computing. Congrats to Yongheng!

Conference Papers

(* Corresponding author, # Mentored student)

  1. Nan Qiao#, Sheng Yue*, Shuning Wang, Yongheng Deng, and Ju Ren. Less Is More: Clustered Cross-Covariance Control for Offline RL. International Conference on Learning Representations (ICLR), Rio de Janeiro, Brazil, 23-27 April, 2026.

  2. Xingyuan Hua#, Sheng Yue*, Xinyi Li, Yizhe Zhao, Jinrui Zhang, and Ju Ren. Context Learning for Multi-Agent Discussion. International Conference on Learning Representations (ICLR), Rio de Janeiro, Brazil, 23-27 April, 2026.

  3. Ningxin He, Yongheng Deng, Sheng Yue, Yongjian Fu, Zehui Zhang, and Tiegang Gao. RAG4DMC: Retrieval-Augmented Generation for Data-Level Modality Completion. International Conference on Learning Representations (ICLR), Rio de Janeiro, Brazil, 23-27 April, 2026.

  4. Nan Qiao# and Sheng Yue*. FORLER: Federated Offline Reinforcement Learning with Q-Ensemble and Actor Rectification. IEEE International Conference on Communications (ICC), Glasgow, UK, 24-28 May, 2026.

  5. Jinrui Zhang, Pengkai Li, Fengzu Li, Deyu Zhang, Wei Gao, Sheng Yue, Yaoxue Zhang, and Ju Ren. FocusX: All-in-Focus Image Synthesis for Dynamic Scenes on Mobile Devices. The 31st Annual International Conference on Mobile Computing and Networking (MobiCom), Hong Kong, China, 4-8 Nov, 2025.

  6. Lili Chen, Yizhe Zhao, Shuning Wang, Linghui Zhong, Yongjian Fu, Sheng Yue, Ju Ren, and Yaoxue Zhang. Towards Distance-Adaptive Wireless Charging. ACM International Conference on Mobile Systems, Applications, and Services (MobiSys), Anaheim, US, 23-27 June, 2025.

  7. Sheng Yue, Jiani Liu#, Xingyuan Hua#, Ju Ren, Sen Lin, Junshan Zhang, and Yaoxue Zhang. How to Leverage Imperfect Demonstrations in Offline Imitation Learning, International Conference on Machine Learning (ICML), Vienna, Austria, 21-27 July, 2024. [Code]

  8. Sheng Yue, Xingyuan Hua#, Ju Ren, Sen Lin, Junshan Zhang, and Yaoxue Zhang. OLLIE: Imitation Learning from Offline Pretraining to Online Finetuning, International Conference on Machine Learning (ICML), Vienna, Austria, 21-27 July, 2024. [Code]

  9. Sheng Yue, Xingyuan Hua#, Lili Chen, and Ju Ren. Momentum-Based Federated Reinforcement Learning with Interaction and Communication Efficiency, IEEE International Conference on Computer Communications (INFOCOM), Vancouver, Canada, 20-23 May, 2024. [Code]

  10. Sheng Yue, Zerui Qin#, Xingyuan Hua#, Yongheng Deng, and Ju Ren. Federated Offline Policy Optimization with Dual Regularization, IEEE International Conference on Computer Communications (INFOCOM), Vancouver, Canada, 20-23 May, 2024. [Code]

  11. Jing Qiao#, Zuyuan Zhang, Sheng Yue*, Yuan Yuan, Zhipeng Cai, Xiao Zhang, Ju Ren, and Dongxiao Yu. BR-DeFedRL: Byzantine-Robust Decentralized Federated Reinforcement Learning with Fast Convergence and Communication Efficiency, IEEE International Conference on Computer Communications (INFOCOM), Vancouver, Canada, 20-23 May, 2024.

  12. Yongheng Deng, Guanbo Wang, Sheng Yue, Wei Rao, Qin Zu, Wenjie Wang, Shuai Chen, Ju Ren, and Yaoxue Zhang. RelayRec: Empowering Privacy-Preserving CTR Prediction via Cloud-Device Relay Learning, ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Hong Kong, China,13-16 May, 2024.

  13. Yongheng Deng, Sheng Yue, Guanbo Wang, Tuowei Wang, Ju Ren, and Yaoxue Zhang. FedINC: An Exemplar-Free Continual Federated Learning Framework with Small Labeled Data, ACM Conference on Embedded Networked Sensor Systems (SenSys),13-15 Nov, Istanbul, Turkiye, 2023.

  14. Sheng Yue, Guanbo Wang#, Wei Shao, Zhaofeng Zhang, Sen Lin, Ju Ren, and Junshan Zhang. CLARE: Conservative Model-Based Offline Inverse Reinforcement Learning, International Conference on Learning Representations (ICLR), Kigali, Rwanda, 1-5 May, 2023.

  15. Tengxi Xia, Yongheng Deng, Sheng Yue, Junyi He, Ju Ren, and Yaoxue Zhang. HSFL: An Efficient Split Federated Learning Framework via Hierarchical Organization, International Conference on Network and Service Management (CNSM), Thessaloniki, Greece, 31 Oct - 4 Nov, 2022.

  16. Sheng Yue, Ju Ren, Jiang Xin, Sen Lin, and Junshan Zhang. Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning, ACM International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing (MobiHoc), Shanghai, China, 26-29 July, 2021.

Journal Papers

(* Corresponding author, # Mentored student)

  1. Nan Qiao#, Sheng Yue*, Ju Ren, and Yaoxue Zhang. FOVA: Offline Federated Reinforcement Learning With Mixed-Quality Data. IEEE/ACM Transactions on Networking (ToN), Early Access, 2025.

  2. Jialin Guo, Yongjian Fu, Zhiwei Zhai, Xinyi Li, Yongheng Deng, Sheng Yue, Lili Chen, Hao Pan, and Ju Ren. MASA: Multimodal Federated Learning through Modality-Aware and Secure Aggregation. IEEE Transactions on Mobile Computing (TMC), vol. 24, no. 8, pp. 7328-7344, 2025.

  3. Sheng Yue, Zerui Qin#, Yongheng Deng, Ju Ren, Yaoxue Zhang, and Junshan Zhang. AugFL: Augmenting Federated Learning with Pretrained Models. IEEE/ACM Transactions on Networking (ToN), vol. 33, no. 4, pp. 1870-1885, 2025.

  4. Ye Zhang, Yongheng Deng, Sheng Yue, Qiushi Li, and Ju Ren. DualRec: A Collaborative Training Framework for Device and Cloud Recommendation Models. IEEE Transactions on Mobile Computing (TMC), vol. 24, no. 6, pp. 5202-5213, 2025.

  5. Sheng Yue, Xingyuan Hua#, Yongheng Deng, Lili Chen, Ju Ren, and Yaoxue Zhang. Momentum-Based Contextual Federated Reinforcement Learning. IEEE/ACM Transactions on Networking (ToN), vol. 33, no. 2, pp. 865-880, 2024.

  6. Jun Lu, Zhenya Ma, Yinggang Gao, Sheng Yue, Ju Ren, and Yaoxue Zhang. StreamSys: A Lightweight Executable Delivery System for Edge Computing. IEEE Transactions on Cloud Computing (TCC), vol. 13, no. 1, pp. 213-226, 2024.

  7. Jiang Xin, Sheng Yue*, Jinrui Zhang, Ju Ren, Feng Qian, and Yaoxue Zhang. MAML-RAL: Learning Domain-Invariant HOI Rules for Real-Time Video Matting, IEEE Transactions on Circuits and Systems for Video Technology (TCVST), vol. 35, no. 4, pp. 3172-3184, 2025.

  8. Sheng Yue, Yongheng Deng, Xingyuan Hua#, Guanbo Wang#, Ju Ren, and Yaoxue Zhang. Federated Offline Reinforcement Learning with Proximal Policy Evaluation, Chinese Journal of Electronics (CJE), vol. 33, no. 6, pp. 1-13, 2024.

  9. Ye Zhang, Jinrui Zhang, Sheng Yue*, Wei Lu, Ju Ren, and Xuemin (Sherman) Shen. Mobile Generative AI: Opportunities and Challenges, IEEE Wireless Communications (WC), vol. 31, no. 4, pp. 58-64, 2024.

  10. Zequn Cao, Xiaoheng Deng, Sheng Yue, Ping Jiang, Ju Ren, and Jinsong Gui. Dependent Task Offloading in Edge Computing Using GNN and Deep Reinforcement Learning, IEEE Internet of Things Journal (IoTJ), vol. 11, no. 12, pp. 21632 - 21646, 2024.

  11. Jiani Liu#, Ju Ren, Yongmin Zhang, Sheng Yue, and Yaoxue Zhang. SESAME: A Resource Expansion and Sharing Scheme for Multiple Edge Services Provider, ACM/IEEE Transaction on Networking (ToN), vol. 32, no. 4, pp. 3189 - 3204, 2023.

  12. Nan Qiao#, Sheng Yue, Yongmin Zhang, and Ju Ren. POPEC: PAoI-Centric Task Offloading with Priority over Unreliable Channels, ACM/IEEE Transactions on Networking (ToN), vol. 32, no. 3, pp. 2376 - 2390, 2023.

  13. Zhaofeng Zhang, Sheng Yue*, and Junshan Zhang. Towards Resource-Efficient Edge AI: From Federated Learning to Semi-Supervised Model Personalization, IEEE Transactions on Mobile Computing (TMC), vol. 23, no. 5, pp. 6104 - 6115, 2024.

  14. Sheng Yue, Ju Ren, Jiang Xin, Deyu Zhang, Yaoxue Zhang, and Weihua Zhuang. Efficient Federated Meta-Learning over Multi-Access Wireless Networks, IEEE Journal on Selected Areas in Communications (JSAC), vol. 40, no. 5, pp. 1556-1570, 2022.

  15. Sheng Yue, Ju Ren, Nan Qiao#, Yongmin Zhang, Hongbo Jiang, Yaoxue Zhang, and Yuanyuan Yang. TODG: Distributed Task Offloading with Delay Guarantees for Edge Computing, IEEE Transactions on Parallel and Distributed Systems (TPDS), vol. 33, no. 7, pp. 1650-1665, 2022.

  16. Ju Ren, K. M. Mahfujul#, Feng Lyu, Sheng Yue, and Yaoxue Zhang. Joint Channel Allocation and Resource Management for Stochastic Computation Offloading in MEC, IEEE Transactions on Vehicular Technology (TVT), vol. 69, no. 8, pp. 8900-8913, 2020.

  17. Ju Ren, Sheng Yue, Deyu Zhang, Yaoxue Zhang, and Jiannong Cao. Joint Channel Assignment and Stochastic Energy Management for RF-Powered OFDMA WSNs, IEEE Transactions on Vehicular Technology (TVT), vol. 68, no. 2, pp. 1578-1592, 2019.

Books

Sheng Yue, Ju Ren. Efficient Federated Meta-Learning over Multi-Access Wireless Networks, Book Chapter of Next Generation Multiple Access, Wiley, 2023.

Grants

[NSFC] Principle Investigator, Research on End-Cloud Collaborative Computing for LLM-based Agents, National Natural Science Foundation of China (国家自然科学基金面上项目), 1/2026-12/2029.

[GDSTC] Principle Investigator, Research on Heterogeneity-Adaptive LLM-Based Edge Computing, Natural Science Foundation of Guangdong Province (广东省基础与应用基础研究基金自然科学基金面上项目), 1/2026-12/2028.

[SZSTI] Principle Investigator, Research on Heterogeneity-Adaptive Construction and Decision-Making for Mobile Agents, Natural Science Foundation of Shenzhen (深圳市自然科学基金面上项目), 1/2026-12/2029.

[NSFC] Principle Investigator, Research on Offline Federated Reinforcement Learning without Environmental Interaction, Young Scientists Found of NSFC (国家自然科学基金青年科学基金), 1/2024-12/2024.

[CPSF] Principle Investigator, Research on Privacy-Preserving Distributed Offline Federated Reinforcement Learning, General Fund of CPSF (中国博士后科学基金面上资助), 1/2024-12/2024.

[CPSF] Principle Investigator, Distributed Offline Policy Optimization under Limited Samples and Heterogeneous Environments, Postdoctoral Fellowship Program of CPSF (国家资助博士后研究人员计划项目), 1/2024-12/2024.

[Industrial Project] Co-Principle Investigator, Application of Edge Intelligence in the Hotel and Travel Business, Tsinghua-Meituan Cooperation and Development Project (清华-美团技术合作开发项目), 8/2022-8/2023.

[Industrial Project] Co-Principle Investigator, Multi-Satellite Collaborative Intelligent Computing Key Technology R&D, Aerospace Hongtu Core R&D Project (航天宏图核心研发委托项目), 7/2022-6/2024.

[Industrial Project] Co-Principle Investigator, Atomic Scene Recognition Technology R&D, Tsinghua-Honor Cooperation and Development Project (清华-荣耀技术合作开发项目), 9/2024-9/2025.

[NSFC] Key Member (Ranked First), Research on Edge-Cloud Collaborative Computing for Large Models with Heterogeneous End Devices, Key Program of NSFC (国家自然科学基金重点项目), 1/2025-12/2029.

[MOST] Key Member, Probe Computer Software System Development, National Key R&D Program of China (国家重点研发计划), 12/2019-12/2024.

[MOST] Key Member, Research of Intelligent Computing Key Standards for Heterogeneous Devices, National Key R&D Program of China (国家重点研发计划), 10/2022-9/2025.

[MOST] Key Member, Blockchain-based Trusted Sharing Technology and Demonstration Application for Health Data, National Key R&D Program of China (国家重点研发计划).

[NSFC] Key Member, Research on Edge Server Deployment and Resource Allocation Optimization, General Program of NSFC (国家自然科学基金面上项目), 1/2021-12/2023.

Honors and Activities

Awards

  • 2025: Young Elite Scientists Sponsorship Program of CAST
  • 2024: CIE Doctoral Dissertation Incentive Program
  • 2023: ACM China SIGAPP Doctoral Dissertation Award
  • 2023: Postdoctoral Fellowship Program of CPSF

Conference Organization

TPC Member

Invited Reviewer

Teaching

  • Computer Programming I, Undergraduate Course, Sun Yat-sen University, Fall 2025.
  • Introduction to Artificial Intelligence, Postgraduate Course, Sun Yat-sen University, Spring 2025.
  • Computer Networking, Undergraduate Course, School of Computer Science and Engineering @ CSU, 2018-2021, TA.

Talks