Junxiao Wang (王军晓)
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.
|