Xingrui Yu
About me
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Dr. Xingrui Yu is currently a research scientist in Centre for Frontier AI Research (CFAR), Agency for Science, Technology and Research (A*STAR), Singapore.
Before that, he was a Ph.D. student at Australian Artificial Intelligence Institute in University of Technology Sydney(UTS),
supervised by Prof. Ivor W. Tsang and closely collaborated with Dr. Bo Han.
His research mainly focus on:
- Trustworthy AI (Robustness, Safety, Security, and Privacy),
- Reinforcement Learning (RL),
- Imitation Learning (IL) and Inverse Reinforcement Learning (IRL),
- Quality Diversity Imitation Learning (QDIL),
- Embodied AI, including Vision-Language-Action (VLA) models, and
- Agentic AI.
Opportunities
I am always looking for self-motivated student to work with me on cutting-edge research projects.
I accept CSC visiting students and research intern students supported by grants or scholarships (e.g., A*STAR SIPGA Scholarship
and A*STAR SINGA Scholarship).
I am also happy to discuss potential projects of common interests.
If you have interest for collaboration, please feel free to drop me an email.
E-mail: yu_xingrui@cfar.a-star.edu.sg
[Google Scholar]
[Github]
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News
- One paper is accepted to ICLR 2025.
- One paper is accepted to AAAI 2025.
- One paper is accepted to AAMAS 2025.
- One paper is accepted to JAIR.
Selected Publications
Heyang Zhao*, Xingrui Yu*, David Mark Bossens*, Ivor W. Tsang, Quanquan Gu.
Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration.
In International Conference on Learning Representations (ICLR), 2025,
[PDF]. Zhenglin Wan*, Anjun Gao*, Xingrui Yu, Pingfu Chao, Jun Song, Maohao Ran.
Next-POI Recommendation via Multi-Objective Adversarial Imitation Learning.
In AAAI Conference on Artificial Intelligence (AAAI), 2025. Xingrui Yu*†, Zhenglin Wan*, David Mark Bossens, Yueming Lyu, Qing Guo, and Ivor W. Tsang.
Imitation from Diverse Behaviors: Wasserstein Quality Diversity Imitation Learning with Single-Step Archive Exploration.
In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2025,
[PDF]. Xingrui Yu, Bo Han, Ivor W. Tsang.
USN: A Robust Imitation Learning Method against Diverse Action Noise.
Journal of Artificial Intelligence Research (JAIR), 2024,
[PDF]. Bo Han, Gang Niu, Xingrui Yu, Quanming Yao, Miao Xu, Ivor W. Tsang, Masashi Sugiyama.
SIGUA: Forgetting May Make Learning with Noisy Labels More Robust.
In International Conference on Machine Learning (ICML), 2020,
[PDF]. Xingrui Yu, Yueming Lyu and Ivor W. Tsang.
Intrinsic Reward Driven Imitation Learning via Generative Model.
In International Conference on Machine Learning (ICML), 2020,
[PDF]
[Code]
[Slides]
[WebPage]. Xingrui Yu, Bo Han, Jiangchao Yao, Gang Niu, Ivor W. Tsang and Masashi Sugiyama.
How does Disagreement Help Generalization Against Label Corruption?
In International Conference on Machine Learning (ICML), 2019,
[PDF]
[Code]. Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor W. Tsang and Masashi Sugiyama.
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels.
In Advances in Neural Information Processing Systems (NeurIPS), 2018,
[PDF]
[Code]. Xingrui Yu, He Zhang, Chunbo Luo, Hairong Qi and Peng Ren.
Oil Spill Segmentation via Adversarial f-divergence Learning.
IEEE Transactions on Geoscience and Remote Sensing (TGRS), 56(9): 4973-4988, 2018,
[PDF]
[Code].
Academic Service
Reviewer of NeurIPS, ICML, ICLR, AAAI, IJCAI, ACML Reviewer of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) Reviewer of IEEE Transactions on Geoscience and Remote Sensing (TGRS) Reviewer of IEEE Transactions on Machine Learning Research (TMLR) Reviewer of Journal of Artificial Intelligence Research (JAIR) Reviewer of Pattern Recognition (PR) Reviewer of Machine Learning (MLJ)
Awards
2020 UTS AAII Best Student Paper Award 2019 ICML Travel Award 2019 Excellent Master Dissertation of Shandong Province 2018 NeurIPS Travel Award
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