Luke Yukun Jiang (江钰坤 in Chinese)
Biography
I am Luke, a Ph.D. student at CISPA Helmholtz Center for Information Security (Saarbrücken, Germany), co-supervised by Prof. Michael Backes and Dr. Yang Zhang. I obtained my B.E. degree at Sichuan University (Chengdu, China) advised by Prof. Beibei Li in 2022.
Research Interests
- AI Security
- Privacy Preservation
- Federated Learning
- Computer Vision
Research Experience
- Feb. 2022 - Aug. 2022, Research Intern at Tencent Cloud, advised by Dr. Yong Cheng
- Apr. 2020 - June 2022, Research Assistant at Sichuan University, advised by Prof. Beibei Li
- Jul. 2021 - Nov. 2021, Remote Research Intern at Duke Univesity, advised by Prof. Neil Gong
Publications
- Yukun Jiang, Xiaoyu Cao, Hao Chen, Neil Gong: ‘‘FedER: Communication-Efficient Byzantine-Robust Federated Learning’’. International Conference on Learning Representations 2022 Workshop on Socially Responsible Machine Learning (ICLR 2022-SRML) [PDF]
- Beibei Li, Yukun Jiang, Qingqi Pei, Tao Li, Liang Liu, Rongxing Lu: ‘‘FEEL: Federated End-to-End Learning with Non-IID Data for Vehicular Ad Hoc Networks’’. in IEEE Transactions on Intelligent Transportation Systems T-ITS (T-ITS) [Link]
- Beibei Li, Yukun Jiang, Wenbin Sun, Weina Niu, Peiran Wang: ‘‘FedVANET: Efficient Federated Learning with Non-IID Data for Vehicular Ad Hoc Networks’’. In Proceedings of IEEE Global Communications Conference 2021 (GLOBECOM 2021) [Link] [PDF]
- Beibei Li, Yaxin Shi, Yuqing Guo, Qinglei Kong, Yukun Jiang: ‘‘Incentive-Based Adaptive Federated Knowledge Distillation for Cross-Silo Applications’’. In Proceedings of IEEE International Conference on Computer Communications Workshops (INFOCOM 2022 WORKSHOPS) [PDF]
- Beibei Li, Peiran Wang, Hanyuan Huang, Shang Ma, Yukun Jiang: ‘‘FLPhish: Reputation-Based Phishing Byzantine Defense in Ensemble Federated Learning’’. In Proceedings of IEEE Symposium on Computers and Communications 2021 (ISCC 2021) Best Paper Award [Link] [PDF]
Awards
- Best Paper Award, ISCC 2021
Last Modified: Dec. 2022
What I've done cannot be undone.