BRIEF BIOGRAPHY
Currently I am an associate professor at School of Computer Science, Beijing University of Posts and Telecommunications. I received my PhD degree in Computer Science from Peking University in 2022, advised by Prof. Yao Guo and Prof. Xiangqun Chen. I previously interned in MSRA working with Senior Researcher Yuanchun Li and Principle Researcher Yunxin Liu.
I work on Efficient and Secure Collaborative AI Systems, which covers a wide range of research topics including mobile/edgeAI system, federated learning, privacy computing, and AI security.
Specifically, my goal is to make AI Models efficient, secure, and personalized for ubiquitous devices.
- Efficiency: Efficient data/model adaptation for multiple resource-constrained devices.
- Security: Trusted federated learning; AI attack/defense; Privacy-sensitive applications.
- Personalization: Edge-cloud collaboration; User-side deployment.
I'm always looking for highly self-motivated PhD/master students, visiting students, and undergraduate interns (RAs) to work with me. Please directly send your CV to me if you find my research interesting.
NEWS
- Feb 2025 - Our paper, "PracMHBench: Re-evaluating Model-Heterogeneous Federated Learning Based on Practical Edge Device Constraints", was accepted by DAC 2025.
- Dec 2024 - Our paper, "PA3Fed: Period-Aware Adaptive Aggregation for Improved Federated Learning", was accepted by AAAI 2025.
- Nov 2024 - Our paper, "BTFL: A Bayesian-based Test-Time Generalization Method for Internal and External Data Distributions in Federated learning", was accepted by KDD 2025.
- June 2024 - Our paper, "Recent advances on federated learning: A systematic survey", was accepted by Neurocomputing 2024.
- May 2024 - Our paper, "Image-based Molecular Representation Learning for Drug Development: A Survey", was accepted by BIB 2024.
- May 2024 - Our paper, "FAMOS:Robust Privacy-Preserving Authentication on Payment Apps via Federated Multi-Modal Contrastive Learning
", was accepted by USENIX Security 2024.
- Feb 2024 - Our paper, "Traceable Federated Continual Learning", was accepted by CVPR 2024.
- July 2023 - Our paper, "No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML", was accepted by IEEE S&P 2024.
- Feb 2023 - Our paper, "Multi-view Scholar Clustering with Dynamic Interest Tracking", was accepted by TKDE 2023.
- Jan 2023 - Our paper, "Beyond Fine-Tuning: Efficient and Effective Fed-Tuning for Mobile/Web Users", was accepted by WWW 2023.
- Dec. 2022 - Our paper, "FedSlice: Protecting Federated Learning Models from Malicious Participants with Model Slicing", was accepted by ICSE 2023.
SELECTED PUBLICATIONS
- [DAC'25] PracMHBench: Re-evaluating Model-Heterogeneous Federated Learning Based on Practical Edge Device Constraints. (CCF-A, full paper)
Yuanchun Guo, Bingyan Liu, Yulong Sha, Zhensheng Xian.
In Proceedings of Design Automation Conference (DAC), June. 2025.
- [AAAI'25] PA3Fed: Period-Aware Adaptive Aggregation for Improved Federated Learning. (CCF-A, full paper)
Chengxiang Huang, Bingyan Liu.
In Proceedings of AAAI Conference on Artificial Intelligence (AAAI), Feb. 2025.
- [KDD'25] BTFL: A Bayesian-based Test-Time Generalization Method for Internal and External Data Distributions in Federated learning. (CCF-A, full paper)
Yu Zhou, Bingyan Liu.
In Proceedings of KDD, Aug. 2025.
- [Neurocomputing'24] Recent advances on federated learning: A systematic survey. (JCR-Q1, full paper)
Bingyan Liu, Nuoyan Lv, Yuanchun Guo, and Yawen Li.
In Neurocomputing, June. 2024.
- [BIB'24] Image-based Molecular Representation Learning for Drug Development: A Survey. (JCR-Q1/CCF-B, full paper)
Yue Li, Bingyan Liu, Jinyan Deng, Yi Guo, and Hongbo Du.
In Briefing In Bioinformatics, May. 2024.
- [Security'24] FAMOS:Robust Privacy-Preserving Authentication on Payment Apps via Federated Multi-Modal Contrastive Learning. (CCF-A, full paper)
Yifeng Cai, Ziqi Zhang, Jiaping Gui, Bingyan Liu, Xiaoke Zhao, Ruoyu Li, Zhe Li, and Ding Li.
In Proceedings of USENIX Security Symposium (Security), May. 2024.
- [CVPR'24] Traceable Federated Continual Learning. (CCF-A, full paper)
Qiang Wang, Bingyan Liu, and Yawen Li.
In IEEE / CVF Computer Vision and Pattern Recognition Conference, Feb. 2024.
- [IEEE S&P'24] No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML. (CCF-A, full paper)
Ziqi Zhang, Chen Gong, Yifeng Cai, Yuan yuanyuan, Bingyan Liu, Shuai Wang, Ding Li, Yao Guo, and Xiangqun Chen.
In IEEE Symposium on Security and Privacy, July. 2023.
- [TKDE'23] Multi-view Scholar Clustering with Dynamic Interest Tracking. (CCF-A, full paper)
Ang Li, Yawen Li, Yingxia Shao, and Bingyan Liu.
In IEEE Transactions on Knowledge and Data Engineering, Feb. 2023.
- [WWW'23] Beyond Fine-Tuning: Efficient and Effective Fed-Tuning for Mobile/Web Users. (CCF-A, full paper)
Bingyan Liu, Yifeng Cai, Hongzhe Bi, Ziqi Zhang, Ding Li, Yao Guo, and Xiangqun Chen.
In Proceedings of the 32th Web Conference, Jan. 2023.
- [ICSE'23] FedSlice: Protecting Federated Learning Models from Malicious Participants with Model Slicing. (CCF-A, full paper)
Ziqi Zhang, Yuanchun Li, Bingyan Liu, Yifeng Cai, Ding Li, Yao Guo, and Xiangqun Chen.
In International Conference on Software Engineering, Dec. 2022.
- [ISSTA'22] TEESlice: Slicing DNN Models for Secure and Efficient Deployment. (CCF-A, full paper)
Ziqi Zhang, Lucien K. L. Ng, Bingyan Liu, Yifeng Cai, Ding Li, Yao Guo, and Xiangqun Chen.
In International Symposium on Software Testing and Analysis(workshop), June. 2022.
- [ICSE'22] ReMoS: Reducing Defect Inheritance in Transfer Learning via Relevant Model Slicing. (CCF-A, full paper)
Ziqi Zhang, Yuanchun Li, Jindong Wang, Bingyan Liu, Ding Li, Yao Guo, Xiangqun Chen, and Yunxin Liu.
In International Conference on Software Engineering, Dec. 2021.
- [ACM Ubicomp'22]
DistFL: Distribution-aware Federated Learning for Mobile Scenarios. [PDF] (CCF-A, full paper)
Bingyan Liu, Yifeng Cai, Ziqi Zhang, Yuanchun Li, Leye Wang, Ding Li, Yao Guo, and Xiangqun Chen.
In ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Oct 2021.
- [ISSTA'21]
ModelDiff: Testing-based DNN Similarity Comparison for Model Reuse Detection. [PDF] (CCF-A, full paper, 51/233≈21.9%)
Yuanchun Li, Ziqi Zhang, Bingyan Liu, Ziyue Yang, Yunxin Liu.
In Proceeding of the 30th ACM SIG-SOFT International Symposium on Software Testing and Analysis.
- [WWW'21]
PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization. [PDF] (CCF-A, full paper, 357/1736≈20.6%)
Bingyan Liu, Yao Guo, and Xiangqun Chen.
In Proceedings of the 30th Web Conference.
- [ACM Ubicomp'21]
PMC: A Privacy- preserving Deep Learning Model Customization Framework for Edge Computing. [PDF] (CCF-A, full paper, 149/848≈17.5%)
Bingyan Liu, Yuanchun Li, Yunxin Liu, Yao Guo, and Xiangqun Chen.
In Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4, 4, Article 139 (December 2020), 25 pages.
- [AAAI'21]
TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning. [PDF] (CCF-A, full paper, 1692/7961≈21.3%)
Bingyan Liu, Yifeng Cai, Yao Guo, and Xiangqun Chen.
In Proceedings of the 35th AAAI Conference on Artificial Intelligence.
- [ACM MM'19]
WealthAdapt: A General Net-Adaptation Framework for Small Data Tasks. [PDF] (CCF-A, full paper, 248/936≈26.5%)
Bingyan Liu, Yao Guo, Xiangqun Chen.
In Proceedings of the 27th ACM International Conference on Multimedia.
INVITED TALKS
- Ant Group, Beijing. Security and Privacy in Split Learning, May 2023
- Huawei, Beijing. Security and Privacy in Federated Learning, Apr 2023
- The 32th Web Conference (WWW), Apr 2023
- ACM Conference on Pervasive and Ubiquitous Computing (UbiComp), Sep 2021
- Introduction of our work on federated personalization, AI Drive, June 2021
- Introduction of our work on model adaptation, AIIT, Hangzhou, May 2021
- The 30th Web Conference (WWW), Virtual Event, Apr 2021
- The 35th AAAI Conference on Artificial Intelligence (AAAI), Virtual Event, Feb 2021
- The 27th ACM International Conference on Multimedia (ACMMM), France, Oct 2019
ACADEMIC SERVICES
Conference Reviewer/PC member
- ICML 2025 (CCF-A), Reviewer
- ICLR 2025 (Top-tie), Reviewer
- AAAI 2025 (CCF-A), PC member
- Neurips 2024 (CCF-A), Reviewer
- CVPR 2024,2025 (CCF-A), Reviewer
- KDD 2023,2024,2025 (CCF-A), Reviewer
- WWW 2022,2023,2024,2025 (CCF-A), Reviewer
- Ubicomp 2020,2024 (CCF-A), Reviewer
- ACM MM 2023,2024,2025 (CCF-A), Reviewer
Transaction/Journal Reviewer
- Nature Communications 2025, Reviewer
- TMC 2024 (CCF-A), Reviewer
- TPAMI 2024 (CCF-A), Reviewer
- TKDE 2022,2023 (CCF-A), Reviewer
- IJCV 2023 (CCF-A), Reviewer
- TOIS 2022 (CCF-A), Reviewer
- JSAC 2022 (CCF-A), Reviewer
TEACHING EXPERIENCE
- Course Instructor, Machine Learning Practical Training, Beijing University of Posts and Telecommunications (Fall 2024)
- Course Instructor, Operating System, Beijing University of Posts and Telecommunications (Fall 2023,Fall 2024)
- Course Instructor, Operating System Practice, Beijing University of Posts and Telecommunications (Spring 2024)
- Teaching Assistant, Operating System, Peking University (Spring 2018 - Fall 2020)
SELECTED HONORS
- Excellent Advisor for Undergraduate Thesis of Beijing, 2024
- Excellent Advisor for Undergraduate Thesis of BUPT, 2024
- Outstanding Graduate of Beijing, 2022
- Outstanding Graduate of Peking University, 2022
- Academic Innovation Award, Peking University, 2021
- PhD National Scholarship, Ministry of Education, 2021
- Merit student, Peking University, 2021
- Huawei Scholarship, Huawei, 2021
- Stars of Tomorrow Internship Program, Microsoft Research Asia, 2020
- Scientific Research Excellence Award, Peking University, 2019
- Scientific Research Excellence Award, Peking University, 2018
- Outstanding Undergraduate Students of Beijing, 2017
Last Updated: 2023-02
