I am currently (Apr. 2026) an assistant professor in the School of Electronic Information at Central South University. I received my Ph.D. in Electrical Engineering from the University of Texas at San Antonio in Dec. 2025, and was fortunate to be advised by advised by Dr. Yanmin Gong (Texas A&M University). I also hold an M.S. in Applied Mathematics School of Science and a B.S. in Infromation and Computing Science from the East China University of Science and Technology.

My research interests include Cybersecurity, Foundation Models, Edge Intelligence, and Trustworthy Artificial Intelligence.

🔥 News

• 2026.03: I joined the School of Electronic Information at Central South University as a tenure-track assistant professor!

• 2026.01: I am invited to serve as TPC member for Communication and Information System Security at IEEE GLOBECOM 2026.

• 2025.12: I defended my Ph.D. dissertation!

• 2025.09: Our paper “Online Client Scheduling and Resource Allocation for Efficient Federated Edge Learning” was accepted by IEEE Transactions on Vehicular Technology (TVT 2025).

• 2025.07: Our paper “Heterogeneity-Aware Resource Allocation and Topology Design for Hierarchical Federated Edge Learning” was accepted by IEEE Internet of Things Journal (IoT-J 2025).

• 2025.01: Our paper “pFedSAM: Secure Federated Learning Against Backdoor Attacks via Personalized Sharpness-Aware Minimization” was accepted by IEEE International Conference on Communications (ICC 2025).

• 2024.12: Our paper “Federated Adaptive Fine-Tuning of Large Language Models with Heterogeneous Quantization and LoRA” was accepted by IEEE International Conference on Computer Communications (INFOCOM 2025). (Acceptance ratio: 18.65%)

• 2024.10: Our paper “Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression” was accepted by IEEE Transactions on Mobile Computing (TMC).

📝 Publications

See Google Scholar for a comprehensive list of publications.

Selected Papers in Refereed Journals:

• Online Client Scheduling and Resource Allocation for Efficient Federated Edge Learning, Yu Zhang, Zhidong Gao, Zhenxiao Zhang, Tongnian Wang, Yanmin Gong, Yuanxiong Guo, IEEE Transactions on Vehicular Technology (TVT), 2025.

• Heterogeneity-Aware Resource Allocation and Topology Design for Hierarchical Federated Edge Learning, Zhidong Gao, Zhenxiao Zhang, Yu Zhang, Yuanxiong Guo, Yanmin Gong, IEEE Internet of Things Journal (IoT-J), 2025.

• Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression, Zhenxiao Zhang, Zhidong Gao, Yuanxiong Guo, Yanmin Gong, IEEE Transactions on Mobile Computing (TMC), 2024.

• Communication and Energy Efficient Wireless Federated Learning with Intrinsic Privacy, Zhenxiao Zhang, Yuanxiong Guo, Yuguang Fang, Yanmin Gong, IEEE Transactions on Dependable and Secure Computing (TDSC), 2023.

• Scalable and Low-Latency Federated Learning with Cooperative Mobile Edge Networking, Zhenxiao Zhang, Zhidong Gao, Yuanxiong Guo, Yanmin Gong, IEEE Transactions on Mobile Computing (TMC), 2022.

Selected Papers in Refereed Inferences:

• Federated Adaptive Fine-Tuning of Large Language Models with Heterogeneous Quantization and LoRA, Zhidong Gao*, Zhenxiao Zhang*, Yuanxiong Guo, Yanmin Gong, IEEE International Conference on Computer Communications (INFOCOM), 2025. (Acceptance ratio: 18.65%)
• pFedSAM: Secure Federated Learning Against Backdoor Attacks via Personalized Sharpness-Aware Minimization, Zhenxiao Zhang, Yuanxiong Guo, Yanmin Gong, IEEE International Conference on Computer Communications (ICC), 2025.

Preprints:

• DP$^2$-FedSAM: Enhancing Differentially Private Federated Learning Through Personalized Sharpness-Aware Minimization, Zhenxiao Zhang, Yuanxiong Guo, Yanmin Gong. arXiv preprint, 2024.
• FedPT: Federated Proxy-Tuning of Large Language Models on Resource-Constrained Edge Devices, Zhidong Gao, Yu Zhang, Zhenxiao Zhang, Yanmin Gong, Yuanxiong Guo. arXiv preprint, 2024.
• Online Client Scheduling and Resource Allocation for Efficient Federated Edge Learning, Zhidong Gao, Zhenxiao Zhang, Yu Zhang, Tongnian Wang, Yanmin Gong, Yuanxiong Guo. arXiv preprint, 2024.

📖 Educations

• 2020.09 - 2025.12, University of Texas at San Antonio (UTSA), San Antonio, USA.
• 2017.09 - 2020.07, Master of Science, East China University of Science and Technology (ECUST), Shanghai, China.
• 2013.09 - 2017.07, Bachelor of Science, East China University of Science and Technology (ECUST), Shanghai, China.

✅ Professional Services

Journal Reviewer:

• IEEE Transactions on Mobile Computing (TMC), 2023, 2024.
• IEEE Transactions on Information Forensics and Security (TIFS), 2023, 2024.
• Computers & Security, 2023, 2024.
• Expert Systems with Applications (ESWA), 2024.
• Cluster & Computing, 2024.
• Computing, 2024.
• Mobile Networks and Application, 2024.
• iScience, 2025.

Conference Reviewer:

• IEEE International Conference on Computer Communications (INFOCOM), 2023, 2024.
• IEEE International Conference on Distributed Computing Systems (ICDCS), 2024, 2025.
• IEEE International Conference on Pervasive Computing and Communications (PerCom), 2024.

Technical Program Committee Member:

• Workshop on Generative AI for Smart and Connected Health: Innovations, Challenges, and Applications (GenAI4SCH), IEEE/ACM CHASE, 2025.

🏆 Honors and Awards

• Graduate School Professional Development Award, UTSA, USA, 2024.
• CPS-IoT Week Student Travel Grant, National Science Foundation, 2023.
• Teaching Assistant Work Award, ECUST, China, 2018.

🌍 Outreach

• Poster presentation at New In ML workshop of NeurIPS, New Orleans, USA, 2023.
• Volunteer at CPS-IoT Week, San Antonio, USA, 2023.