Ph.D. Student | HKUST CSE | Relaxed System Lab

fdingad@connect.ust.hk

Github

I work on machine learning, with an emphasis on probabilistic methods and generative models, e.g. discrete diffusion language models.

Education

• Ph.D. Student in Computer Science, the Hong Kong University of Science and Technology (HKUST), 2024 - 🙈
• M.Eng. in Computer Science, Shanghai Jiao Tong University (SJTU), 2021 - 2024
• B.Eng. in Computer Science, Shanghai Jiao Tong University (SJTU), 2017 - 2021

Publications

• Beyond Masks: Efficient, Flexible Diffusion Language Models via Deletion-Insertion Processes
  Fangyu Ding*, Ding Ding*, Sijin Chen*, Kaibo Wang, Peng Xu, Zijin Feng, Haoli Bai, Kai Han, Youliang Yan, Binhang Yuan, Jiacheng Sun
  International Conference on Learning Representations (ICLR), 2026.
• Improving Subgraph Extraction for Graph Invariant Learning via Graph Sinkhorn Attention
  Junchi Yan, Fangyu Ding (Correspondence), Jiawei Sun, Zhaoping Hu, Yunyi Zhou, Lei Zhu
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2026.
• C-NTPP: Learning Cluster-Aware Neural Temporal Point Process
  Fangyu Ding, Junchi Yan, Haiyang Wang
  AAAI Conference on Artificial Intelligence (AAAI), 2023.

Blogs

• Discrete Diffusion from the VAE Perspective
  

Teaching

• HKUST COMP 4611 Design and Analysis of Computer Architectures, Spring 2025

Experiences

• Huawei AI Lab, Hong Kong, 2025.6 - 🦄
• UCloud, Shanghai, 2024.4 - 2024.7
• AntGroup, Hangzhou, 2022.10 - 2023.6
• Alibaba Damo Academy, Hangzhou, 2021.7 - 2021.9

Awards

• Huawei PhD Fellowship
• HKUST Postgraduate Scheme
• SJTU Postgraduate Scholarship
• SJTU Undergraduate Scholarship

Academic Service

• Reviewer: International Conference on Machine Learning (ICML)