Ruize Gao (Machine Learning Researcher)
Home
 |
Ruize Gao (高瑞泽)
Ph.D. Candidate @ SOC NUS |
Biography
-
I am a Ph.D. candidate of School of Computing at National University of Singapore, fortunately supervised by Prof. Xiaokui Xiao and Prof. Bogdan Cautis. My current research interests include trustworthy machine learning and machine learning for privacy protection, especially for adversarial robustness, statistical machine learning, and trustworthy AI for LLMs/VLMs and agents. I received my B.E. degree at Shanghai Jiao Tong University (SJTU) in 2020.
I used to be a Research Assistant of Department of Computer Science and Engineering at The Chinese University of Hong Kong, fortunately supervised by Prof. James Cheng. During my academic life in Hong Kong, I work closely with Prof. Bo Han @HKBU, Prof. Feng Liu @UniMelb, Dr. Kaiwen Zhou @CUHK, and fortunately collaborate with Dr. Gang Niu and Prof. Masashi Sugiyama @RIKEN.
I have served as a program committee (PC) member for NeurIPS'22-25, ICML'21-26, ICLR'22-26 and so on. I was awarded the DesCartes-AISG fellowship at NUS, and awarded as the Chun Tsung Scholar (entitled by Nobel Laureate Dr. Tsung-Dao Lee) at SJTU.
Preprints
(* indicates equal contributions)
Local Reweighting for Adversarial Training.
R. Gao*, F. Liu*, K. Zhou, G. Niu, B. Han and J. Cheng.
[PDF].
Selected Publications
(* indicates equal contributions)
A Unified Perspective on Adversarial Membership Manipulation in Vision Models.
R. Gao, K. Zhou, Y. Chen, F. Liu.
In Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026 (CCF A) [PDF][Code][Poster].HATS: Hardness-Aware Trajectory Synthesis for GUI Agents. (Technical Lead)
R. Shao*, R. Gao*, B. Xie, Y. Li, K. Zhou, S. Wang, W. Guan, G. Chen.
In Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026 (CCF A) [PDF][Code][Poster].Topic-aware Influence Maximization with Deep Reinforcement Learning and Graph Attention Networks.
T. Halal, B. Cautis, B. Groz, R. Gao.
In Proceedings of European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), 2025 (CCF B) [PDF].Scalable Continuous-time Diffusion Framework for Network Inference and Influence Estimation. (Oral)
K. Huang, R. Gao, B. Cautis, X. Xiao.
In Proceedings of ACM Web Conference (WWW), 2024 (CCF A) [PDF][Code][Poster].Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack.
R. Gao, J. Wang, K. Zhou, F. Liu, B. Xie, G. Niu, B. Han, J. Cheng.
In Proceedings of 39th International Conference on Machine Learning (ICML), 2022 (CCF A) [PDF] [ Code] [Poster].Maximum Mean Discrepancy Test is Aware of Adversarial Attacks.
R. Gao*, F. Liu*, J. Zhang*, B. Han, T. Liu, G. Niu, and M. Sugiyama.
In Proceedings of 38th International Conference on Machine Learning (ICML), 2021 (CCF A) [PDF] [ Code] [Poster].Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem.
J. Li, Y. Ma, R. Gao, Z. Cao, A. Lim, W. Song, and J. Zhang.
IEEE Transactions on Cybernetics (T-Cybernetics), 2021 (JCR Q1) [PDF] [ Code] [Poster].