🧑‍🎓 About Me

Fangchen Yu is currently a Ph.D. candidate in Computer and Information Engineering at The Chinese University of Hong Kong, Shenzhen (CUHK-SZ), under the supervision of Prof. Wenye Li and Prof. Jianfeng Mao. He obtained his Bachelor’s degree in Physics from the University of Chinese Academy of Sciences (UCAS) in 2020. His research interests focus on statistical machine learning, metric learning, and optimal transport.

🏷️ Research Interests

Similarity/Distance Learning, Incomplete Data, Optimal Transport, Computer Vision.

📑 Research Topics

• Efficient Optimization Algorithms for Incomplete Data (Previous Work)
  • Optimization of similarity and distance matrices for offline/online incomplete data
  • Estimation of inner product matrix for incomplete data on similarity search tasks
• Optimization and Generalization for Wasserstein Distance (Ongoing Work)
  • Fast and accurate tree Wasserstein distance for approximating 1-Wassserstein distance
  • Robust Wasserstein distance for unbalanced distributions
• Optimization for Visual Generative Models & AI for Science (Future Work)
  • Optimization for Wasserstein-based generative models (e.g., Point Cloud Completion)
  • New neural network design for the discovery of physical laws (e.g., K-A Networks)

📝 Publications & Preprint

$\dagger$: equal contributions; $\ast$: corresponding author

• 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] [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 - Now,
  Ph.D. Candidate in Computer and Information Engineering, at The Chinese University of Hong Kong, Shenzhen (CUHK-SZ; Supervisors: Prof. Wenye Li and Prof. Jianfeng Mao).
  
• Oct. 2024 - Now,
  Visiting Student, at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI, ranked Top20 globally in AI; Supervisor: Prof. Qiang Sun).
  
• Sep. 2016 - Jun. 2020,
  B.S. in Physics, at University of Chinese Academy of Sciences (UCAS).
  
• Aug. 2019 - Dec. 2019,
  Global Study Program, at University of California, Davis (UCD).

💻 Professional Experience

• Jul. 2023 - Jun. 2024,
  Graduate Research Assistant, at Shenzhen Research Institute of Big Data, Shenzhen, China. (Supervisor: Dr. Yicheng Zeng)
  
• Mar. 2023 - Jul. 2023,
  Research Intern, at Vivo AI Lab, Shenzhen, China. (Area: 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 2024, WWW 2025, AAAI 2025/2024/2023, IJCAI 2025/2024, ECML 2022, etc.

👨🏻‍🏫 Teaching Assistant

• Summer 2024: MAT3007 Optimization. Instructor: Prof. Junfeng Wu
• Spring & Fall 2023: DDA4210 Advanced Machine Learning. Instructors: Prof. Jicong Fan & Prof. Tongxin Li
• Fall 2022: MAT3300 Mathematical Modeling. Instructor: Prof. Gongqiu Zhang
• Summer 2022: EIE4006/CIE6126 Performance Evaluation of Communication Networks. Instructor: Prof. Tony Lee
• Spring 2022: STA3010 Regression Analysis. Instructor: Prof. Feng Yin
• Fall 2021: MAT4003 Number Theory. Instructor: Prof. Jun Bo (Mario) Huan
• Spring 2021: MAT4004 Graph Theory. Instructor: Prof. Jun Bo (Mario) Huang
• Fall 2020: MAT3280 Probability Theory. Instructor: Prof. Kenneth Shum