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@kt4ngw
kt4ngw
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Working in Home

Jian, Tang kt4ngw

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Working in Home
I'm Jian Tang, Incoming Ph.D. student in School of Computing Technologies at RMIT University. Thank you for visiting and like.

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kt4ngw /README.md

πŸ‘‹ Hello, here is kt4ngw (Jian Tang).
  • πŸ“Œ Incoming Ph.D. student in School of Computing Technologies at RMIT University.
  • πŸ™‹β€β™‚οΈ M.S. Software Engineering, Chongqing University, Chongqing, China (Jun. 2025); B.S. Engineering, Hunan University of Technology and Business, Changsha, China (Jun. 2022)
  • 🌱 Current research interest includes Federated Learning (FL), Edge Intelligence, FL for LLM, Network & System Security.
  • πŸ‘€ Please do not hesitate to contact me with any questions.
  • πŸ“§ Email: kt4ngw@gmail.com(mainly). (Please state your affiliation and name and indicate your intention.)
  • ✨ Progressing together, please!⚑⚑⚑⚑⚑⚑
  • πŸ‘ Last but not least, to learn & to cope (that's my motto)!

Pinned Loading

  1. HFL-M3 HFL-M3 Public

    Source code for the paper "Accelerating Hierarchical Federated Learning under Mobility via Model Migration in Cloud–Edge–End Collaborative Networks".

    Python 4

  2. GFLCSM GFLCSM Public

    Source code for the paper "Group-based Federated Learning with Cost-efficient Sampling Mechanism in Mobile Edge Computing Networks".

    Python 37

  3. ICC-2024 ICC-2024 Public

    Source code for the paper "Energy-Efficient Client Sampling for Federated Learning in Heterogeneous Mobile Edge Computing Networks", this paper is pulished in ICC 2024.

    Python 14

  4. BAPFT BAPFT Public

    Source code for the paper "Accelerating Federated Learning under Client Dropout via Joint Bandwidth Allocation and Prototype Fine-Tuning in Mobile Edge Computing Networks".

    Python 10

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