🧑‍🎓 About Me

I am a Ph.D. candidate in Computer and Information Engineering at The Chinese University of Hong Kong, Shenzhen (CUHK-SZ), under the supervision of Prof. Jianfeng Mao and Prof. Wenye Li. I obtained the Bachelor’s degree in Physics from the University of Chinese Academy of Sciences (UCAS) in 2020.

I have a broad interest in machine learning with a particular interest in AI for Science, (Multimodal) Large Language Model, and Statistics for AI.

🏷️ Research Interests

AI for Science, (Multimodal) Large Language Model, Statistics for AI.

📑 Research Topics

• Efficient Similarity and Distance Learning (Previous Work)
  • Optimize similarity matrices for offline and online incomplete data (Published in NeurIPS, WWW, and UAI)
  • Estimate distance matrices for incomplete data in similarity search tasks (Published in AAAI, ECAI, and ECML)
  • Develop an accurate tree-Wasserstein distance for approximating the 1-Wasserstein distance (Published in ICML)
• Physical Reasoning for (Multimodal) Large Language Models (Ongoing Work)
  • Develop a new benchmark to evaluate the physical reasoning abilities of (M)LLMs
  • Design a novel framework to enhance the physical reasoning abilities of (M)LLMs

📝 Publications & Preprint

$\dagger$: Equal contributions; $\ast$: Corresponding authors

• P1: Mastering Physics Olympiads with Reinforcement Learning
  Jiacheng Chen^$\dagger$, Qianjia Cheng^$\dagger$, Fangchen Yu^$\dagger$, Haiyuan Wan, Yuchen Zhang, Shenghe Zheng, Junchi Yao, Qingyang Zhang, Haonan He, Yun Luo, Yufeng Zhao, Futing Wang, Li Sheng, Chengxing Xie, Yuxin Zuo, Yizhuo Li, Wenxuan Zeng, Yulun Wu, Rui Huang, Dongzhan Zhou, Kai Chen, Yu Qiao, Lei Bai^$\ast$, Yu Cheng^$\ast$, Ning Ding^$\ast$, Bowen Zhou^$\ast$, Peng Ye^$\ast$, Ganqu Cui^$\ast$
  [Paper] [Website] [GitHub] [HuggingFace] [bibtex]

• SCI-Verifier: Scientific Verifier with Thinking
  Shenghe Zheng^$\dagger$, Chenyu Huang^$\dagger$, Fangchen Yu, Junchi Yao, Jingqi Ye, Tao Chen, Yun Luo, Ning Ding, Lei Bai, Ganqu Cui, Peng Ye^$\ast$
  [Paper] [GitHub] [HuggingFace] [bibtex]

• PhysicsMinions: Winning Gold Medals in the Latest Physics Olympiads with a Coevolutionary Multimodal Multi-agent System
  Fangchen Yu^$\dagger$, Junchi Yao^$\dagger$, Ziyi Wang, Haiyuan Wan, Youling Huang, Bo Zhang, Shuyue Hu, Dongzhan Zhou, Ning Ding, Ganqu Cui, Lei Bai, Wanli Ouyang, Peng Ye^$\ast$
  [Paper] [bibtex]

• HiPhO: How Far Are MLLMs from Humans in the Latest High School Physics Olympiad Benchmark?
  Fangchen Yu^$\dagger$, Haiyuan Wan^$\dagger$, Qianjia Cheng^$\dagger$, Yuchen Zhang, Jiacheng Chen, Fujun Han, Yulun Wu, Junchi Yao, Ruilizhen Hu, Ning Ding, Yu Cheng, Tao Chen, Lei Bai, Dongzhan Zhou^$\ast$, Yun Luo^$\ast$, Ganqu Cui^$\ast$, Peng Ye^$\ast$
  [Paper] [Website] [GitHub] [HuggingFace] [bibtex]

• UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance
  Fangchen Yu, Yanzhen Chen, Jiaxing Wei, Jianfeng Mao, Wenye Li^$\ast$, Qiang Sun^$\ast$
  [Paper] [Code] [Poster] [bibtex]

• A Theory-Driven Approach to Inner Product Matrix Estimation for Incomplete Data: An Eigenvalue Perspective
  Fangchen Yu^{$\dagger \ast$}, Yicheng Zeng^{$\dagger \ast$}, Jianfeng Mao, Wenye Li
  [Paper] [Code] [Poster] [bibtex]

• Balancing the Trade-Off Between Global and Personalized Performance in Federated Learning
  Zibin Pan, Chi Li, Fangchen Yu, Shuyi Wang, Xiaoying Tang^$\ast$, Junhua Zhao^$\ast$
  [Paper] [bibtex]

• KAE: Kolmogorov-Arnold Auto-Encoder for Representation Learning
  Fangchen Yu, Ruilizhen Hu, Yidong Lin, Yuqi Ma, Zhenghao Huang, Wenye Li^$\ast$
  [Paper] [Code] [bibtex]

• FedLF: Layer-wise Fair Federated Learning
  Zibin Pan, Chi Li, Fangchen Yu, Shuyi Wang, Haijin Wang, Xiaoying Tang^$\ast$, Junhua Zhao^$\ast$
  [Paper] [Code] [Poster] [bibtex]
  

• DocReal: Robust Document Dewarping of Real-Life Images via Attention-Enhanced Control Point Prediction
  Fangchen Yu (internship), Yina Xie, Lei Wu, Yafei Wen, Guozhi Wang, Shuai Ren, Xiaoxin Chen, Jianfeng Mao, Wenye Li^$\ast$
  [Paper] [Code] [Poster] [bibtex]
  

• Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning
  Fangchen Yu, Runze Zhao, Zhan Shi, Yiwen Lu, Jicong Fan, Yicheng Zeng, Jianfeng Mao, Wenye Li^$\ast$
  [Paper] [Code] [Video] [PPT] [Poster] [bibtex]
  

• Online Estimation of Similarity Matrices with Incomplete Data
  Fangchen Yu, Yicheng Zeng, Jianfeng Mao, Wenye Li^$\ast$
  [Paper] [Code] [Poster] [bibtex]
  

• Highly-Efficient Robinson-Foulds Distance Estimation with Matrix Correction
  Fangchen Yu, Rui Bao, Jianfeng Mao, Wenye Li^$\ast$
  [Paper] [Code] [Poster] [bibtex]
  

• From Incompleteness to Unity: A Framework for Multi-view Clustering with Missing Values
  Fangchen Yu, Zhan Shi, Yuqi Ma, Jianfeng Mao, Wenye Li^$\ast$
  [Paper] [bibtex]

• Metric Nearness Made Practical
  Wenye Li, Fangchen Yu, Zichen Ma
  [Paper] [Code] [Poster] [bibtex]
  

• Calibrating Distance Metrics Under Uncertainty
  Wenye Li^$\ast$, Fangchen Yu
  [Paper] [bibtex]

• Learning Sparse Binary Code for Maximum Inner Product Search
  Changyi Ma, Fangchen Yu, Yueyao Yu, Wenye Li^$\ast$
  [Paper] [bibtex] (Best Short Paper Finalist)

🏫 Educations

• Sep. 2020 - *,
  *Ph.D. Candidate in Computer and Information Engineering, at The Chinese University of Hong Kong, Shenzhen (CUHK-SZ; Supervisors: Prof. Jianfeng Mao and Prof. Wenye Li).
  

• Sep. 2016 - Jun. 2020,
  B.S. in Physics, at University of Chinese Academy of Sciences (UCAS).
  

• Oct. 2024 - Apr. 2025,
  Visiting Student, at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI, ranked Top10 globally in AI; Supervisor: Prof. Qiang Sun).
  
• Aug. 2019 - Dec. 2019,
  Global Study Program, at University of California, Davis (UCD).

💻 Internships

• Jun. 2025 - *,
  *Research Intern, at Shanghai AI Lab, Shanghai, China. (Supervisor: Dr. Peng Ye)
  
• Sep. 2020 - Aug. 2024,
  Graduate Research Assistant, at Shenzhen Research Institute of Big Data, Shenzhen, China. (Supervisors: Prof. Wenye Li and Prof. Yicheng Zeng)
  
• Mar. 2023 - Jul. 2023,
  Research Intern, at Vivo AI Lab, Shenzhen, China. (Group: Visual Understanding and Generation)

🎖 Honors and Awards

• 2023, PhD Fellowship, Shenzhen Research Institute of Big Data
• 2022, PhD Fellowship, Shenzhen Research Institute of Big Data
• 2022, Outstanding Teaching Assistant Award, The Chinese University of Hong Kong, Shenzhen
• 2021, Outstanding Teaching Assistent Award, The Chinese University of Hong Kong, Shenzhen
• 2021, PhD Fellowship, Shenzhen Research Institute of Big Data
• 2020, PhD Fellowship, Shenzhen Research Institute of Big Data
• 2019, Class III Scholarship, University of Chinese Academy of Sciences
• 2017, Merit Student, University of Chinese Academy of Sciences

👨🏻‍💻 Academic Service

• Program Committee Member:
  ICML 2025, ICLR 2025, NeurIPS 2025/2024, WWW 2025, AAAI 2025/2024/2023, IJCAI 2025/2024, ECML 2022, etc.

👨🏻‍🏫 Teaching Assistant

• MAT3007 Optimization. Instructor: Prof. Junfeng Wu. Summer 2024.
• DDA4210 Advanced Machine Learning. Instructors: Prof. Jicong Fan & Prof. Tongxin Li. Spring & Fall 2023.
• MAT3300 Mathematical Modeling. Instructor: Prof. Gongqiu Zhang. Fall 2022.
• EIE4006 Performance Evaluation of Communication Networks. Instructor: Prof. Tony Lee. Summer 2022.
• STA3010 Regression Analysis. Instructor: Prof. Feng Yin. Spring 2022.
• MAT4003 Number Theory. Instructor: Prof. Jun Bo (Mario) Huan. Fall 2021.
• MAT4004 Graph Theory. Instructor: Prof. Jun Bo (Mario) Huang. Spring 2021.
• MAT3280 Probability Theory. Instructor: Prof. Kenneth Shum. Fall 2020.

Last Update: 2025-11-30