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 obtained my M.E. degree at the School of Computing from Nanjing University of Information Science and Technology (NUIST), China, in 2019, and my Ph.D. degree at School of Computing from Kyung Hee University (KHU), South Korea, in 2025. I also served as a Camera Software Engineer at Spreadtrum Communications (UNISOC), Shanghai, China, from 2019 to 2022.

My research interests are in efficient & trustworthy AI, federated learning, and adversarial machine learning. 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 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. 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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  2. 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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  3. 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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  4. 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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  5. IEEE ICC
    Knowledge distillation assisted robust federated learning: Towards edge intelligence
    Yu Qiao, Apurba Adhikary, Ki Tae Kim, and 2 more authors
    In ICC 2024-IEEE International Conference on Communications, 2024
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