I am a third-year Ph.D. student at Eindhoven University of Technology, under the supervision of Mykola Pechenizkiy and Meng Fang. I am also very fortunate to work closely with Prof. Yali Du at King’s College London, and Prof. Biwei Huang at University of California San Diego. I was a research intern at Microsoft Research Asia, mentored by Dr. Lu Wang. Prior to joining TU/e, I was a master student in the Visual, Sensing and Intelligent System Laboratory, Shandong University (SDU), supervised by Prof. Wei Zhang. I also obtained my bachelor's degree from Shandong University.
My current research interests lie in causal reinforcement learning, multi-agent reinforcement learning, LLMs and embodied AI.
Education
- B.S. in Automation, Shandong University, 2015 - 2019
- M.S. in Control Science and Engineering, Shandong University, 2019 - 2022
- Ph.D in Computer Science, Eindhoven University of Technology, 2026 (expected)
News
- Oct 2024, two papers accecpted by NeurIPS 2024 CRL workshop.
- Oct 2024, invited talk at Women in AI & Robotics Reading Group.
- Dec 2023, one papers accecpted by AAAI 2024.
- Oct 2023, invited talk at RLChina.
- Sep 2023, two papers accecpted by NeurIPS 2023.
Publication
*: Equal contribution, ✉: Corresponding author[1] Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach. Yudi Zhang, Yali Du, Biwei Huang, Ziyan Wang, Jun Wang, Meng Fang, Mykola Pechenizkiy. Advances in Neural Information Processing Systems (NeurIPS), 2023.
[Project], [Paper]
[2] COOM: A Game Benchmark for Continual Reinforcement Learning. Tristan Tomilin, Meng Fang, Yudi Zhang, Mykola Pechenizkiy. Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track (NeurIPS D&B), 2023.
[Paper] [Code]
[3] Large Language Models are Neurosymbolic Reasoners. Meng Fang*, Shilong Deng*, Yudi Zhang*, Zijing Shi, Ling Chen, Mykola Pechenizkiy, Jun Wang. Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024.
[Paper]
[4] RSPT: Reconstruct Surroundings and Predict Trajectories for Generalizable Active Object Tracking. Fangwei Zhong*, Xiao Bi*, Yudi Zhang, Wei Zhang, Yizhou Wang. Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 (Oral).
[Project], [Paper]
Workshops & Preprint:
[5] CAST: A causality-inspired spatial-temporal return decomposition approach for multi-agent reinforcement learning. Yudi Zhang, Yali Du, Biwei Huang, Meng Fang, Mykola Pechenizkiy. In Proceedings of the NeurIPS 2024 Causal Representation Learning Workshop.
[6] MACCA: Offline multi-agent reinforcement learning with causal credit assignment. Ziyan Wang, Yali Du, Yudi Zhang, Meng Fang, Biwei Huang. In Proceedings of the NeurIPS 2024 Causal Representation Learning Workshop.
[Paper]
[7] RuAG: Learned-rule-augmented Generation for Large Language Models. Yudi Zhang*, Pei Xiao*, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, Qingwei Lin, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
Award
- NeurIPS 2023 Travel Award
- Outstanding Graduates of Shandong Province (2019)
- Competitions: Second Prize in the Chinese Graduate Mathematical Modeling Competition (2019), First Prize in the National Electronic Design Competition, Shandong Province (2017), International Aquatic Robot Competition Champion (2018, 2019)
- Scholarships: Shandong University first-class scholarship, Shandong University outstanding students special scholarship, etc.
Service
- Journal Reviewer: IEEE Transactions on Artificial Intelligence.
- Conference Reviewer: AAMAS 2024, ICML 2024, NeurIPS 2024, AAAI 2025, ICLR 2025, AISTATS 2025.
- Teaching Assistant: Generative AI in OxML 2024, 2IIG0 Data Mining and Machine Learning.
- Supervised MSc students: Schipper Olivier, Beuningen Niels van.