Junxiao Wang (王军晓)

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Postdoctoral Fellow
Department of Computing
Faculty of Engineering
Hong Kong Polytechnic University
Hung Hom, Kowloon, Hong Kong SAR
Work Email: email
Personal Email: email

Find me at  linkedin github google scholar

About Me

I am working as a Postdoctoral Fellow with PolyU Edge Intelligence Laboratory (PEILab), directed by Prof. Song Guo, at Department of Computing, Hong Kong Polytechnic University.

I once worked as a Visiting Researcher with Networks Research Group, directed by Prof. Steve Uhlig, at School of Electronic Engineering and Computer Science, Queen Mary University of London. I received my PhD from College of Computer Science and Technology, Dalian University of Technology in 2020, advised by Prof. Keqiu Li. Before that, I received my MEng and BE in 2017, 2014.

Research Interests

I am broadly interested in privacy-preserving machine learning and programmable networking with a special focus on federated learning, machine unlearning, software-defined networking and network functions virtualization.

Recent Professional Activities

  • Invited Talk, in Ritsumeikan University and CCF Dalian International Academic Seminar, 2022.03

  • Postdoctoral Fellow, working with Prof. Song Guo, at Department of Computing, Hong Kong Polytechnic University, 2021.03

  • PC Member for IEEE ICPADS Workshop on Network Computing and Data Management (NCDM), 2020.10

  • Session Chair for IEEE International Conference on Parallel and Distributed Systems (ICPADS), 2019.12

  • Visiting Researcher, working with Prof. Steve Uhlig, at School of Electronic Engineering and Computer Science, Queen Mary, University of London, 2018.10-2019.10

News

  • Apr 2022   Our paper entitled "Efficient Integrity Authentication Scheme for Large-scale RFID Systems" was accepted by IEEE Transactions on Mobile Computing.

  • Apr 2022   Our paper entitled "Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations" was available in arXiv pre-print.

  • Apr 2022   Our paper entitled "A Survey on Gradient Inversion: Attacks, Defenses and Future Directions" was accepted by Survey track of IJCAI2022.

  • Jan 2022   Our paper entitled "Federated Unlearning via Class-Discriminative Pruning" was accepted by ACM WWW2022.

  • Dec 2021   Our paper entitled "Protect Privacy from Gradient Leakage Attack in Federated Learning" was accepted by IEEE INFOCOM2022.

  • Oct 2021   Our paper entitled "Federated Unlearning via Class-Discriminative Pruning" was available in arXiv pre-print.

  • Dec 2020   Our paper entitled "Dynamic SDN Control Plane Request Assignment in NFV Datacenters" was accepted by IEEE Transactions on Network Science and Engineering.

  • Oct 2020   Our paper entitled "A Blockchain-driven IIoT Traffic Classification Service for Edge Computing" was accepted by IEEE Internet of Things Journal.

  • Feb 2020   Our paper entitled "Click-UP: Toward the Software Upgrade of Click-Based Modular Network Function" was accepted by IEEE Systems Journal.

  • Aug 2019   Our paper entitled "FlowTracer: An Effective Flow Trajectory Detection Solution Based on Probabilistic Packet Tagging in SDN-Enabled Networks" was accepted by IEEE Transactions on Network and Service Management.

  • Jun 2018   Our paper entitled "CLICK-UP: Towards Software Upgrades of Click-driven Stateful Network Elements" was accepted by Demo track of ACM SIGCOMM2018.

  • Jan 2018   Our paper entitled "PRSFC-IoT: A Performance and Resource Aware Orchestration System of Service Function Chaining for Internet of Things" was accepted by IEEE Internet of Things Journal.