I am currently a postdoctoral fellow at The Hong Kong Polytechnic University, supervised by Prof. Song Guo, Fellow of IEEE and Prof. Bin Xiao, Fellow of IEEE. I received the Ph.D. degree from Nanjing University of Science and Technology, supervised by Prof. Jun Li. Before that, I received the B.S. degree in information engineering from Xidian University, Xian, China, in 2014. From Jun. 2021 to Dec. 2021, I was a research intern (Rhinoceros Bird Project) at Tencent, Shenzhen, supervised by Dr. Yong Cheng.

I mainly focus on privacy protection and optimization techniques for edge intelligence, such as federated learning, differential privacy and network resource allocation. I have published several prestigious papers at the top international AI conferences and journals. I am 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.

🔥 News

2023.10: 🎉🎉 Kang Wei won the IEEE VTC2023-Fall Volunteer Service Award
2023.08: 🎉🎉 Our paper has been accepted by Proceedings of the IEEE
2023.06: 🎉🎉 Our paper has won the excellent academic paper award from Chinese Institute of Electronics
2023.04: 🎉🎉 One paper has been accepted by ICML 2023

📝 Publications

Trustworthy AI

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.
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]
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.
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.
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.
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 .
Jun Li, Kang Wei (导师一作), Chuan Ma and Feng Shu, DP-GenFL: A Local Differentially Private Federated Learning System through Generative Data, SCIENCE CHINA Information Sciences (SCIS), 2022.
Xin Yuan, Wei Ni, Ming Ding, Kang Wei (通讯作者), 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.
Chuan Ma, Jun Li, Ming Ding, Bo Liu, Kang Wei (通讯作者), 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.
Chuan Ma, Jun Li, Kang Wei (通讯作者), 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.
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.

Cloud-Edge-Terminal Networks

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.
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.
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.
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.
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.
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.

Distributed Optimization

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.

Industrial Data Analytics

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.
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

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.
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.

🎖 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 (中国电子学会)
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 (IEEE信号处理学会)
2021.12: First Place of iDASH Privacy and Security Workshop-Secure Genome Analysis Competition, Awarded by National Institutes of Health (美国国立卫生研究院)
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

📖 Educations

2023.01 - now: Post-doctoral Fellow, The Hong Kong Polytechnic University, Hong Kong
2018.09 - 2023.01: Ph.D., Nanjing University of Science and Technology, Nanjing China
2017.09 - 2018.06: Master, Nanjing University of Science and Technology, Nanjing China
2010.08 - 2014.07: B.E., Xidian University, Xian China
2007.09 - 2010.06: High school, Nanjing Dongshan Foreign Language School, Nanjing China

💬 Invited Talks

2020: Communication Rounds Discounting in Federated Learning with Differential Privacy, IEEE International Symposium on a Word of Wireless, Mobile and Multimedia Networks (WOWMOM)-Intelligent Things and Services (INTHINGS)
2020: Privacy and Security in Federated Learning, IEEE/CIC ICCC

💻 Experiences

2021.06 - 2021.12: Research Intern, Tencent, Shenzhen China
2014.08 - 2016.06: Engineer, Panda Group, Nanjing China

Kang Wei