I am currently a postdoctoral fellow in Assured Information Management and Sharing (AIMS) at the Computer Science Department of Emory University, supervised by Prof. Li Xiong since Aug. 2023. Previously, I was a Ph.D. student supervised by Prof. Hong Chen at the School of Information, Renmin University of China from Sep. 2018 to June, 2023. During my Ph.D. study, I was a research intern at Amazon AWS AI lab, hosted by Zhiqi Bu and Zha Sheng in 2023, and I was a research intern at Microsoft Research Asia, hosted by Fangzhao Wu and Xing Xie in 2021-2022. I received my Bachelor’s degree from China University of Petroleum in June, 2018. During my undergraduate stage, I was a visiting student in Biometric Technologies Laboratory (BTLAB) at University of Calgary, supervised by Prof. Marina L. Gavrilova.

My works focus on advancing privacy enhancement techniques (PETs) to create machine learning systems that are not only theoretically privacy-preserving but also practically viable with better utility, efficiency and inclusiveness. I am broadly interested in trustworthy AI.

📝 Publications ()

See full list here

Conference Papers

PreCurious: How Innocent Pre-Trained Language Models Turn into Privacy Traps
Ruixuan Liu, Tianhao Wang, Yang Cao, Li Xiong
Proceedings of the 31th ACM Conference on Computer and Communications Security (CCS)

Supporting Pandemic Preparedness with Privacy Enhancing Technology
Ruixuan Liu, Sepanta Zeighami, Haowen Lin, Cyrus Shahabi, Yang Cao, Shun Takagi, Yoko Konishi, Masatoshi Yoshikawa, Li Xiong
Proceedings of the 5th IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

PrivateRec: Differentially Private Model Training and Online Serving for Federated News Recommendation
Ruixuan Liu, Yang Cao, Yanlin Wang, Lingjuan Lyu, Yun Chen, Hong Chen
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD)

No one left behind: Inclusive federated learning over heterogeneous devices
Ruixuan Liu, Fangzhao Wu, Chuhan Wu, Yanlin Wang, Lingjuan Lyu, Hong Chen, Xing Xie
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD)

Flame: Differentially private federated learning in the shuffle model
Ruixuan Liu, Yang Cao, Hong Chen, Ruoyang Guo, Masatoshi Yoshikawa
Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI)

Efficient-FedRec: Efficient federated learning framework for privacy-preserving news recommendation
Jingwei Yi, Fangzhao Wu, Chuhan Wu, Ruixuan Liu, Guangzhong Sun, Xing Xie
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Fedsel: Federated sgd under local differential privacy with top-k dimension selection
Ruixuan Liu, Yang Cao, Masatoshi Yoshikawa, Hong Chen
Proceedings of 25th International Conference of Database Systems for Advanced Applications (DASFAA)

Mixgeo: Efficient secure range queries on encrypted dense spatial data in the cloud
Ruoyang Guo, Bo Qin, Yuncheng Wu, Ruixuan Liu, Hong Chen, Cuiping Li
Proceedings of the 27th IEEE/ACM International Symposium on Quality of Service (IWQoS)

Journal Papers

LuxGeo: Efficient and Security-Enhanced Geometric Range Queries
Ruoyang Guo, Bo Qin, Yuncheng Wu, Ruixuan Liu, Hong Chen, Cuiping Li
IEEE Transactions on Knowledge and Data Engineering (TKDE)

Survey on Privacy Attacks and Defenses in Machine Learning
Ruixuan Liu, Hong Chen, Ruoyang Guo, Dan Zhao, Wenjuan Liang, Cuiping Li
Journal of Software (Chinese)

A pufferfish privacy mechanism for monitoring web browsing behavior under temporal correlations
Wenjuan Liang, Hong Chen, Ruixuan Liu, Yuncheng Wu, Cuiping Li
Computers & Security

Preprints

Zero redundancy distributed learning with differential privacy, Zhiqi Bu, Ruixuan Liu, Justin Chiu, Sheng Zha, George Karypis

On the accuracy and efficiency of group-wise clipping in differentially private optimization, Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis

🎖 Honors and Awards

• Outstanding Doctoral Graduate, Renmin University of China, 2023
• 2nd Prize of CIKM 2022 AnalytiCup Competition (with 3,000 USD), 2022
• 1st-Class Academic Scholarship, School of Information, Renmin University of China, 2019-2022
• Outstanding Visiting Student of University of Calgary, 2018
• Outstanding Undergraduate Scholarship of China Scholarship Council, 2017
• 1st Prize of Software Design Competition of Shandong Province, 2017
• Special Prize of Bochuang Cup National College Students Embedded System Design Competition, 2017
• Excellent Student Leader of Shandong Province, 2017
• Shengli Scholarship of China University of Petroleum, 2017
• Simei Star of China University of Petroleum, 2017
• National Scholarship, Chinese Ministry of Education, 2016

💻 Services

• Journal Reviewer
  • IEEE Transactions on Mobile Computing (TMC) 2024
  • IEEE Transactions on Information Forensics & Security (TIFS) 2024
  • IEEE Transactions on Dependable and Secure Computing (TDSC) 2023-2024
• Conference Program Committee Member
  • IEEE Conference on Secure and Trustworthy Machine Learning (SatML) 2025
  • AAAI Conference on Artificial Intelligence (AAAI) 2023-2025
  • ACM International Conference on Information and Knowledge Management (CIKM) 2024
• Conference Reviewer
  • ACM Knowledge Discovery and Data Mining (SIGKDD) 2024-2025
  • KDD-Workshop on FedKDD 2024
  • ICML-Workshop on FM-Wild 2024
  • SIGKDD-Workshop on Federated Learning for Distributed Data Mining (FL4Data) 2023
• External Reviewer
  • IEEE International Conference on Data Engineering (ICDE) 2020-2021

👩‍🏫 Teaching & Talks

• Privacy Challenge as Models Scale: Training Efficiency and Amplified Risk, @University of Virginia, AI ML seminar
• Co-instructor @Emory University, CS573 fall 2024
• Guest lecturer @THokkaido University, heory and Practice of Algorithms, 2023 Spring