Journal paper

• Wenhan Yu, Terence Jie Chua, Jun Zhao. “Asynchronous Hybrid Reinforcement Learning for Latency and Reliability Optimization in the Metaverse over Wireless Communications.”
  — IEEE Journal on Selected Areas in Communications (JSAC), 2023.
• Wenhan Yu, Terence Jie Chua, Jun Zhao. “User-centric Heterogeneous-action Deep Reinforcement Learning for Virtual Reality in the Metaverse over Wireless Networks.”
  — IEEE Transactions on Wireless Communications (TWC), 2023.
• Wenhan Yu, Jun Zhao. “Optimization for 6G Wireless Communications with Heterogeneous VR and Non-VR 360-Degree Videos: A Differentiated Reinforcement Learning Approach.”
  — IEEE Transactions on Wireless Communications (TWC), 2024.
• Terence Jie Chua, Wenhan Yu, Jun Zhao. “Mobile Edge Adversarial Detection for Digital Twinning to the Metaverse with Deep Reinforcement Learning.”
  — IEEE Transactions on Wireless Communications (TWC), 2023.
• Jun Zhao, Liangxin Qian, Wenhan Yu. “Human-Centric Resource Allocation in the Metaverse over Wireless Communications.”
  — IEEE Journal on Selected Areas in Communications (JSAC), 2023.

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preprint

• Terence Jie Chua, Wenhan Yu, Jun Zhao. “Play to Earn in the Metaverse with Mobile Edge Computing over Wireless Networks: A Deep Reinforcement Learning Approach.”
  — IEEE Transactions on Wireless Communications (TWC), Minor revision, 2024.
• Peiyuan Si, Wenhan Yu, Jun Zhao, Kowk-Yan Lam. “Hybrid Convex Optimization and Reinforcement Learning (HCORL).”
  — IEEE Transactions on Communications (TCOM), Submitted, 2023.
• Terence Jie Chua, Wenhan Yu, Jun Zhao. “Unified, User and Task Centered (UUT) Artificial Intelligence for Metaverse Edge Computing.”
  — IEEE Vehicular Technology Magazine, Submitted, 2022.
• Terence Jie Chua*, Wenhan Yu*, Jun Zhao. “FedPEAT: Convergence of 6G-enabled Federated Learning, Parameter-Efficient Fine Tuning, and Emulator Assisted Tuning for Foundation Models”
  — submit to Nature Scientific Reports, February, 2024. (* means equal contribution)

Conference paper

• Wenhan Yu, Liangxin Qian, Terence Jie Chua, Jun Zhao. “Counterfactual Reward Estimation for Credit Assignment in Multi-agent Deep Reinforcement Learning over Wireless Video Transmission.”
  — IEEE International Conference on Distributed Computing Systems (ICDCS), 2024. (Acceptance ratio: 121/552≈21.9%)
• Wenhan Yu, Terence Jie Chua, Jun Zhao. “Virtual Reality in Metaverse over Wireless Networks with User-centered Deep Reinforcement Learning.”
  — IEEE International Conference on Communications (ICC), 2023.
• Wenhan Yu, Terence Jie Chua, Jun Zhao. “Multi-Agent Deep Reinforcement Learning for Digital Twin over 6G Wireless Communication in the Metaverse.”
  — IEEE INFOCOM Workshop on PerAI-6G: Pervasive Network Intelligence for 6G Networks, 2023.
• Wenhan Yu, Jun Zhao. “Heterogeneous 360 Degree Videos in Metaverse: Differentiated Reinforcement Learning Approaches.”
  — IEEE Global Communications Conference (GLOBECOM), 2023.
• Wenhan Yu, Terence Jie Chua, Jun Zhao. “Mobile Edge Computing and AI Enabled Web3 Metaverse over 6G Wireless Communications: A Deep Reinforcement Learning Approach.”
  — IEEE Vehicular Technology Conference (VTC2023-Spring), 2023.
• Wenhan Yu, Jun Zhao. “Semantic communications, semantic edge computing, and semantic caching with applications to the Metaverse and 6G mobile networks.”
  — IEEE International Conference on Distributed Computing Systems (ICDCS), PhD symposium, 2023.
• Wenhan Yu, Jun Zhao. “Quantum Multi-Agent Reinforcement Learning as an Emerging AI Technology: A Survey and Future Directions.”
  — IEEE International Conference on Computer and Applications (ICCA), 2023.
• Wenhan Yu, Terence Jie Chua, Jun Zhao. “Orchestration of Emulator Assisted Mobile Edge Tuning for AI Foundation Models: A Multi-Agent Deep Reinforcement Learning Approach.”
  — IEEE Vehicular Technology Conference (VTC2023-Spring), 2024.
• Terence Jie Chua, Wenhan Yu, Jun Zhao. “Mobile Edge Adversarial Detection for Digital Twinning to the Metaverse with Deep Reinforcement Learning.”
  — IEEE International Conference on Communications (ICC), 2023.
• Terence Jie Chua, Wenhan Yu, Jun Zhao. “Mobile Edge Adversarial Detection for Digital Twinning to the Metaverse with Deep Reinforcement Learning.”
  — IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Best paper award, 2022.
• Terence Jie Chua, Wenhan Yu, Jun Zhao. “Resource allocation for mobile metaverse with the Internet of Vehicles over 6G wireless communications: A deep reinforcement learning approach.”
  — IEEE World Forum on the Internet of Things (WF-IoT), 2022.

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preprint

• Peiyuan Si, Wenhan Yu, Jun Zhao, Kowk-Yan Lam. “UAV aided Metaverse over Wireless Communications: A Reinforcement Learning Approach.”
  — arXiv preprint.

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