Yu Qiao

Research Professor at Kyung Hee University, South Korea.

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I am currently a Research Professor at the School of Computing, Kyung Hee University (KHU), South Korea.

I received my B.E. degree in Internet of Things Engineering in 2016, my M.E. degree in Computer Science and Technology from Nanjing University of Information Science and Technology (NUIST), Nanjing, China, in 2019, and my Ph.D. degree in Artificial Intelligence from Kyung Hee University (KHU), South Korea, in 2025. I am currently a Research Professor in the School of Computing, Kyung Hee University (KHU), South Korea. Prior to my Ph.D., I worked as an R&D Engineer at Spreadtrum Communications (UNISOC), Shanghai, China, from 2019 to 2022.

My interests include efficient and trustworthy AI, generative AI (AIGC), computer vision, and wireless networking. I have high-impact IEEE journal and conference papers, and serves as a reviewer for leading journals, including IEEE Transactions on Information Forensics and Security, IEEE Transactions on Cognitive Communications and Networking, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Mobile Computing, etc.

I am currently on the job market, seeking a full-time postdoctoral research or teaching position. Please feel free to reach out if you have potential job opportunities. You can access my CV here and contact me via qiaoyu1002@gmail.com.

news

Nov 12, 2025 We are excited to share that one paper has been accepted in the IEEE Internet of Things (IoT) journal :sparkles:
Nov 02, 2025 We are excited to share that one paper has been accepted in the ACM Computing Surveys (CSUR) journal :sparkles:
Sep 12, 2025 We are excited to share that one paper has been accepted in the IEEE Transactions on Network Science and Engineering (TNSE) journal :sparkles:

selected publications

  1. ACM CSUR
    Deepseek-inspired exploration of rl-based llms and synergy with wireless networks: A survey
    Yu Qiao, Phuong-Nam Tran, Ji Su Yoon, and 4 more authors
    ACM Computing Surveys, 2025
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  2. IEEE IoTJ
    Robust Federated Learning with Heterogeneous Clients via Classifier Calibration and Alignment
    Yu Qiao, Zilong Jin, Avi Deb Raha, and 5 more authors
    IEEE Internet of Things Journal, 2025
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  3. IEEE TNSE
    Federated hybrid training and self-adversarial distillation: Towards robust edge networks
    Yu Qiao, Apurba Adhikary, Kitae Kim, and 3 more authors
    IEEE Transactions on Network Science and Engineering, 2025
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  4. INFFUS
    Fedccl: Federated dual-clustered feature contrast under domain heterogeneity
    Yu Qiao, Huy Q Le, Mengchun Zhang, and 3 more authors
    Information Fusion, 2025
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  5. IEEE TNSE
    Logit calibration and feature contrast for robust federated learning on non-iid data
    Yu Qiao, Chaoning Zhang, Apurba Adhikary, and 1 more author
    IEEE Transactions on Network Science and Engineering, 2024
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  6. IEEE IoTJ
    Mp-fedcl: Multiprototype federated contrastive learning for edge intelligence
    Yu Qiao, Md Shirajum Munir, Apurba Adhikary, and 4 more authors
    IEEE Internet of Things journal, 2023
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