Meng Zhang, researcher

Publications

Journal Papers

  • L. Jin, Y. Zhang, Y. Li, S. Wang, H. H. Yang, J. Wu, and M. Zhang*, MoE²: Optimizing Collaborative Inference for Edge Large Language Models, IEEE/ACM Transactions on Networking (ToN), 2026.

  • M. Tang, L. Jin, M. Zhang*, and H. Wang, Asynchronous Fractional Multi-Agent Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing, To appear in IEEE/ACM Transactions on Networking (ToN), 2026.

  • J. Zhu, C. Feng, G. Geraci, C. Liu, M. Zhang, and H. H. Yang, The Meta Distribution of the SINR in Joint Communication and Sensing Networks, To appear in IEEE Transactions on Network Science and Engineering (TNSE), 2026.

  • M. Zhou, M. Zhang*, H. H. Yang, and R. Yates, Timely CPU Scheduling for Computation-intensive Status Updates, To appear in IEEE Transactions on Information Theory (TIT), 2026.

  • N. Yang, Y. Liu, S. Chen, M. Zhang, and H. Zhang, Minimizing Age of Information in Mobile Edge Computing: Nested Index Policy with Preemptive and Non-Preemptive Structure, IEEE Transactions on Mobile Computing (TMC), 2026.

  • J. He, Q. Ma, M. Zhang, and J. Huang, Optimizing Fresh Data Sampling and Trading, IEEE/ACM Transactions on Networking (ToN), 2025.

  • J. He, M. Zhang, Q. Ma, and J. Huang, Trading Fresh IoT Data with Strategic Users, IEEE Transactions on Mobile Computing (TMC), 2025.

  • N. Yang, J. Wen, M. Zhang, and M. Tang, Generalizable Pareto-Optimal Offloading with Reinforcement Learning in Mobile Edge Computing, IEEE Transactions on Services Computing (TSC), 2025.

  • F. Peng, M. Zhang, and M. Tang, An Information-Theoretic Analysis for Federated Learning under Concept Drift, IEEE Transactions on Network Science and Engineering (TNSE), 2025.

  • F. Zhao, N. Pappas, M. Zhang, and H. H. Yang, Age of Information in Random Access Networks with Energy Harvesting, IEEE Journal on Selected Areas in Communications (JSAC), 2025.

  • M. Zhang and D. Vasal, Large-Scale Mechanism Design for Networks: Superimposability and Dynamic Implementation, IEEE Transactions on Mobile Computing (TMC), 2025.

  • G. Liao, B. Luo, Y. Feng, M. Zhang*, and X. Chen, Optimal Mechanism Design for Heterogeneous Client Sampling in Federated Learning, IEEE Transactions on Mobile Computing (TMC), 2024.

  • M. Zhang, E. Wei, R. Berry, and J. Huang, Age-Dependent Differential Privacy, IEEE Transactions on Information Theory (TIT), 2024.

  • Z. Yue, H. H. Yang, M. Zhang, and N. Pappas, Age of Information under Frame Slotted ALOHA-based Status Updating Protocol, IEEE Journal on Selected Areas in Communications (JSAC), 2023.

  • M. Zhang, E. Wei, and R. Berry, Faithful Edge Federated Learning: Scalability and Privacy, IEEE Journal on Selected Areas in Communications (JSAC), 2022.

  • M. Zhang, A. Arafa, E. Wei, and R. Berry, Optimal and Quantized Mechanism Design for Fresh Data Acquisition, IEEE Journal on Selected Areas in Communications (JSAC), 2021.

  • M. Zhang, A. Arafa, J. Huang, and H. V. Poor, Pricing Fresh Data, IEEE Journal on Selected Areas in Communications (JSAC), 2021.

  • M. Zhang, J. Huang, and R. Zhang, Wireless Power Transfer with Information Asymmetry: A Public Goods Perspective, IEEE Transactions on Mobile Computing (TMC), 2021.

  • M. Zhang and J. Huang, Efficient Network Sharing with Asymmetric Constraint Information, IEEE Journal on Selected Areas in Communications (JSAC), 2019.

  • M. Zhang, L. Gao, J. Huang, and M. Honig, Hybrid Pricing for Mobile Collaborative Internet Access, IEEE/ACM Transactions on Networking (ToN), 2019.

  • M. Zhang, and Y. Liu, Secure Beamforming for Untrusted MISO Cognitive Radio Networks, IEEE Transactions on Wireless Communications (TWC), 2018.

  • M. Zhang, Y. Liu, and R. Zhang, Artificial Noise Aided Secrecy Information and Power Transfer in OFDMA Systems, IEEE Transactions on Wireless Communications (TWC), 2016.ESI Highly Cited Paper

  • M. Zhang, and Y. Liu, Energy harvesting for physical-layer security in OFDMA networks, IEEE Transactions on Information Forensics and Security (TIFS), 2016.ESI Highly Cited Paper

Conference Papers

  • X. Qiao, X. Du, W. Liu, J. Zhang, P. Mai, M. Zhang, and Y. Pang, When Sample Selection Bias Precipitates Model Collapse, International Conference on Machine Learning (ICML), 2026.

  • Y. Fu, X. Zhang, and M. Zhang*, Heterogeneous Mean-Field Reinforcement Learning for Age-Minimal GPU Batching, IEEE International Conference on Computer Communications (INFOCOM), 2026.

  • H. Huang, H. Shao, Z. Wang, and M. Zhang*, Conditional Age-at-Risk for Task Assignment across Heterogeneous Servers, IEEE International Conference on Computer Communications (INFOCOM), 2026.

  • S. Wen, M. Zhang, Y. Yang, and N. Ding, FedShard: Federated Unlearning with Efficiency Fairness and Performance Fairness, AAAI Conference on Artificial Intelligence (AAAI), 2026.

  • M. Zhou, L. Yang, V. Y. F. Tan, and M. Zhang, Age-Optimal Best Arm Identification, International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2026.

  • J. He, M. Zhang, Q. Ma, and J. Huang, Trading Fresh Data with Correlation, International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2025.

  • F. Zhao, N. Pappas, M. Zhang, and H. H. Yang, Age of Information in Energy-Harvesting-Enabled Random Access Networks, IEEE International Conference on Computer Communications (INFOCOM), 2025.

  • X. Qiao, M. Zhang*, M. Tang, and E. Wei, Hessian-Free Online Certified Unlearning, International Conference on Learning Representations (ICLR), 2025.

  • S. Wang, Z. Shen, X. Qiao, T. Zhang, and M. Zhang*, DynFrs: An Efficient Framework for Machine Unlearning in Random Forest, International Conference on Learning Representations (ICLR), 2025.

  • Q. Wang, R. Xu, S. He, R. Berry, and M. Zhang*, Unlearning Incentivizes Learning under Privacy Risk, ACM Web Conference (WWW), 2025.

  • M. Tang, L. Jin, M. Zhang*, and H. Wang, Fractional Deep Reinforcement Learning for Age-Minimal Mobile Edge Computing, AAAI Conference on Artificial Intelligence (AAAI), 2024.

  • M. Zhang, H. H. Yang, A. Arafa, and H. V. Poor, Age of Information in Mobile Networks: Fundamental Limits and Tradeoffs, ACM MobiHoc, 2024.

  • M. Zhou, M. Zhang*, H. Yang, and R. Yates, Age-minimal CPU Scheduling, IEEE International Conference on Computer Communications (INFOCOM), 2024.

  • M. Zhang, E. Wei, R. Berry, and J. Huang, Age-Dependent Differential privacy, ACM Sigmetrics, 2022.

  • J. He, Q. Ma, M. Zhang, and J. Huang, Optimal Fresh Data Sampling and Trading, WiOpt, 2021.Best Paper Award

  • M. Zhang, E. Wei, and R. Berry, Faithful Edge Federated Learning: Scalability and Privacy, NetEcon, 2021.

  • M. Zhang, A. Arafa, E. Wei, and R. Berry, Optimal Mechanism Design for Fresh Data Acquisition, IEEE International Symposium on Information Theory (ISIT), 12-20 July 2021.

  • M. Zhang, B. Swenson, J. Huang, and H. V. Poor, Truthful Mobile Crowd Sensing with Interdependent Valuations, ACM MobiHoc, 2020.Acceptance rate 15%

  • M. Zhang, A. Arafa, J. Huang, and H. V. Poor, How to Price Fresh Data, International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), 2019.

  • M. Zhang and J. Huang, Mechanism Design for Network Utility Maximization with Private Constraint Information, IEEE International Conference on Computer Communications (INFOCOM), 2019.Best In-Session Presentation Award