Kang Wei

Associate Professor, School of Cyber Science and Engineering, Southeast University
Email: kangwei [at] polyu [dot] edu [dot] hk

Dr. Kang Wei will being an Associate Professor at Southeast University. He was previously a postdoctoral fellow at The Hong Kong Polytechnic University. He received his Ph.D. from Nanjing University of Science and Technology in 2023 and his B.S. in Information Engineering from Xidian University in 2014. From June to December 2021, he was a research intern at Tencent’s Rhinoceros Bird Project.

Dr. Kang Wei’s research focuses on trustworthy AI and distributed machine learning. His works has been published in flagship conferences and journals such as ICML, CVPR and TIFS. He also served as a reviewer for several top conferences and journals, such as Nature Communications, PATTERNS, NeurIPS, ICLR, KDD, IEEE JSAC, IEEE TWC, IEEE TSP, IEEE JSTSP, IEEE TIFS, IEEE TKDE, IEEE TMC and etc.

Research Interests

  • Trustworthy AI, e.g., diffusion modesl, GNN and federated learning
  • Efficiency in distributed machine learning

Honors and Awards

  • 2023.10: IEEE VTC2023-Fall Volunteer Service Award, Awarded by IEEE Vehicular Technology Society (VTS)
  • 2023.06: Excellent Academic Paper, Awarded by Chinese Institute of Electronics
  • 2023.04: Post-doctoral Matching Fund., Awarded by PolyU
  • 2023.02: Wiley China Open Science Author of the Year, Awarded by Wiley
  • 2022.12: Best Paper Award, Awarded by IEEE Signal Processing Society
  • 2021.12: First Place of iDASH Privacy and Security Workshop-Secure Genome Analysis Competition, Awarded by National Institutes of Health
  • 2021.10: National Scholarship for Doctoral Students, Awarded by Nanjing University of Science and Technology
  • 2021.04: Tencent Rhinoceros Bird Project, Awarded by Tencent
  • 2021-2023: Outstanding Doctoral Program, Awarded by Nanjing University of Science and Technology

Academic Services

Editor Board
  • Young Editorial Board, Cybersecurity (CCF-C Journal)
TPC chair
  • IEEE ICWS-Internet of Intelligent Service Systems (IISS) Workshop (CCF-B Conference)
TPC member
  • AAAI 2024 (CCF-A Conference)
  • IEEE iThings-International Workshop on Future Mobile Computing and Networking for Internet of Things (FMobile) (CCF-C Conference)
Journal reviewer (selected)
  • Nature Communications, PATTERNS, IEEE JSAC, IEEE TIFS, IEEE TKDE, IEEE TMC, IEEE TSP
Conference reviewer (selected)
  • NeurIPS, ICML, ICLR, KDD, WWW, AAAI

Publications

Trustworthy AI

[1] Shuchi Wu, Chuan Ma, Kang Wei **, Xiaogang Xu, Ming Ding, Yuwen Qian, Tao Xiang, Refine, Discriminate and Align: Stealing Encoders via Sample-Wise Prototypes and Multi-Relational Extraction, **The 18th European Conference on Computer Vision (ECCV), 2024. [Code]

[2] Yifan Shi, Yingqi Liu, Kang Wei, Li Shen, Xueqian Wang and Dacheng Tao, Make Landscape Flatter in Differentially Private Federated Learning, IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2023. [Code]

[3] Kang Wei, Jun Li, Ming Ding, Chuan Ma, Yo-Seb Jeon and H. Vincent Poor, Covert Model Poisoning Against Federated Learning: Algorithm Design and Optimization, IEEE Transactions on Dependable and Secure Computing (TDSC), 2023.

[4] Kang Wei, Jun Li, Ming Ding, Chuan Ma, Wen Chen, Jun Wu, Meixia Tao and H. Vincent Poor, Personalized Federated Learning with Differential Privacy and Convergence Guarantee, IEEE Transactions on Information Forensics & Security (TIFS), 2023.

[5] Kang Wei, Jun Li, Ming Ding, Chuan Ma, Hang Su, Bo Zhang and H Vincent Poor, User-level Privacy-preserving Federated Learning: Analysis and Performance Optimization, IEEE Transactions on Mobile Computing (TMC), 2022.

[6] Kang Wei, Jun Li, Ming Ding, Chuan Ma, Howard H. Yang, Farhad Farokhi, Shi Jin, Tony Q. S. Quek and H. Vincent Poor, Federated Learning with Differential Privacy: Algorithms and Performance Analysis, IEEE Transactions on Information Forensics and Security (TIFS), 2020.

[7] Jun Li, Kang Wei **, Chuan Ma and Feng Shu, DP-GenFL: A Local Differentially Private Federated Learning System through Generative Data, **SCIENCE CHINA Information Sciences (SCIS), 2022.

[8] Xin Yuan, Wei Ni, Ming Ding, Kang Wei **, Jun Li and H. Vincent Poor, Amplitude-Varying Perturbation for Balancing Privacy and Utility in Federated Learning, **IEEE Transactions on Information Forensics & Security (TIFS), 2023.

[9] Chuan Ma, Jun Li, Ming Ding, Bo Liu, Kang Wei **, RDP-GAN: A R{'e}nyi-Differential Privacy based Generative Adversarial Network, Jian Weng and H. Vincent Poor, **IEEE Transactions on Dependable and Secure Computing (TDSC), 2023.

[10] Chuan Ma, Jun Li, Kang Wei **, Bo Liu, Ming Ding, Long Yuan, Zhu Han, H Vicent Poor, Trusted AI in multi-agent systems: An overview of privacy and security for distributed learning, **Proceedings of the IEEE, 2023.

[11] Jun Li, Yumeng Shao, Kang Wei, Ming Ding, Chuan Ma, Long Shi, Zhu Han and H Vincent Poor, Blockchain Assisted Decentralized Federated Learning (BLADE-FL): Performance Analysis and Resource Allocation, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2022.

[12] Kang Wei, Jun Li, Chuan Ma, Ming Ding and H. Vincent Poor, Differentially Private Federated Learning: Algorithm, Analysis and Optimization, Federated Learning Systems, Springer Nature, 2021.

End-Edge-Cloud Networks

[1] Jun Li, Weiwei Zhang, Kang Wei **, Guangji Chen, Long Shi, Wen Chen, Deploying Graph Neural Networks in Wireless Networks: A Link Stability Viewpoint, **IEEE Wireless Communications Letters, 2024.

[2] Kang Wei, Jun Li, Chuan Ma, Ming Ding, Feng Shu, Haitao Zhao, Wen Chen and Hongbo Zhu, Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy, SCIENCE CHINA Information Sciences (SCIS), 2024.

[3] Jun Li, Weiwei Zhang, Kang Wei **, Guangji Chen, Feng Shu, Wen Chen, Shi Jin, Blockchain-aided wireless federated learning: Resource allocation and client scheduling, **IEEE Internet of Things Journal, 2024.

[4] Jing Li, Song Guo, Weifa Liang, Jianping Wang, Quan Chen, Wenchao Xu, Kang Wei, Xiaohua Jia, Mobility-Aware Utility Maximization in Digital Twin-Enabled Serverless Edge Computing, IEEE Transactions on Computers, 2024.

[5] Xuefeng Han, Jun Li, Wen Chen, Zhen Mei, Kang Wei, Ming Ding and H. Vincent Poor, Analysis and Optimization of Wireless Federated Learning with Data Heterogeneity, IEEE Transactions on Wireless Communications, 2024.

[6] Quan Chen, Song Guo, Wenchao Xu, Jing Li, Kang Wei, Zhipeng Cai and Hong Gao, Peak AoI Minimization With Directional Charging for Data Collection At Wireless-Powered Network Edge, IEEE Transactions on Services Computing, 2024.

[7] Kang Wei, Jun Li, Chuan Ma, Ming Ding, Cailian Chen, Shi Jin, Zhu Han and H. Vincent Poor, Low-Latency Federated Learning Over Wireless Channels With Differential Privacy, IEEE Journal on Selected Areas in Communications (JSAC), 2022.

[8] Xiumei Deng, Jun Li, Chuan Ma, Kang Wei, Long Shi, Ming Ding and Wen Chen, Low-latency Federated Learning with DNN Partition in Distributed Industrial IoT Networks, IEEE Journal on Selected Areas in Communications (JSAC), 2023.

[9] Xiumei Deng, Jun Li, Chuan Ma, Kang Wei, Long Shi, Ming Ding, Wen Chen and H. Vincent Poor, Blockchain Assisted Federated Learning over Wireless Channels: Dynamic Resource Allocation and Client Scheduling, IEEE Transactions on Wireless Communications (TWC), 2022.

[10] Yifan Shi, Li Shen, Kang Wei, Yan Sun, Bo Yuan, Xueqian Wang and Dacheng Tao, Improving the Model Consistency of Decentralized Federated Learning, International Conference on Machine Learning (ICML), 2023.

Data Analytics

[1] Jixuan Cui, Jun Li, Zhen Mei, Kang Wei, Sha Wei, Ming Ding, Wen Chen and Song Guo, Federated Meta-Learning for Few-Shot Fault Diagnosis With Representation Encoding, IEEE Transactions on Instrumentation and Measurement, 2023.

[2] Yajiao Dai, Zhen Mei, Jun Li, Zengxiang Li, Kang Wei, Ming Ding, Sheng Guo and Wen Chen, Clustering-Based Contrastive Learning for Fault Diagnosis With Few Labeled Samples, IEEE Transactions on Instrumentation and Measurement, 2023.

Coded Flash Memory

[1] Kang Wei, Jun Li, Lingjun Kong, Feng Shu, Francis C. M. Lau, Page-based Dynamic Partitioning Scheduling for LDPC Decoding in MLC NAND Flash Memory, IEEE Transactions on Circuits and Systems II: Express Briefs (TCAS-II), 2019.

[2] Kang Wei, Jun Li, Lingjun Kong, Feng Shu and Yonghui Li, Read-Voltage Optimization for Finite Code Length in MLC NAND Flash Memory, IEEE Information Theory Workshop (ITW), 2018.