About me

I am an Assistant Researcher at IDEA. Prior to that, I received my master’s degree from Tsinghua University in 2023, co-advised by Xi Xiao and Shu-Tao Xia. My research interests focus on, but are not limited to graph/hypergraph neural networks and machine learning. These days I am interested in diffusion/flow models, AI4Science, and drug discovery. Feel free to contact me if you are interested in my research.

Publications

Check the full list here.

• SubGDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning
  Jiying Zhang, Zijing Liu, Yu Wang, Feng Bin, Yu Li
  Conference on Neural Information Processing Systems (NeurIPS) 2024 [paper] [code]

• Efficient Antibody Structure Refinement Using Energy-Guided SE(3) Flow Matching
  Jiying Zhang, Zijing Liu, Shengyuan Bai, He Cao, Yu Li, Lei Zhang
  IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2024 regular paper [paper]

• Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport
  Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian
  IJCAI 2022 (International Joint Conferences on Artificial Intelligence Organization 2022). [paper] [code]

• Hypergraph Convolutional Networks via Equivalency Between Hypergraphs and Undirected Graphs
  Jiying Zhang, Fuyang Li, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, Yatao Bian
  ICML 2022 Workshop (Topology, Algebra, and Geometry in Machine Learning). [paper] [code]

• Learnable Hypergraph Laplacian for Hypergraph Learning
  Jiying Zhang, Yuzhao Chen, Xi Xiao, Runiu Lu, Shu-Tao Xia
  ICASSP 2022 (2022 IEEE International Conference on Acoustics, Speech and Signal Processing) [paper] [code]

• GraphTTA: Test Time Adaptation on Graph Neural Networks
  Guanzi Chen*, Jiying Zhang*, Xi Xiao, Yang Li (* equal contribution)
  ICML 2022 Workshop on Principles of Distribution Shift. [paper]

• A Simple Hypergraph Kernel Convolution Based on Discounted Markov Diffusion Process
  Fuyang Li*, Jiying Zhang*, Xi Xiao, Bin Zhang, Dijun Luo (* equal contribution)
  NeurIPS 2022 Workshop (New Frontiers in Graph Learning). [paper]

• Diversified Multiscale Graph Learning with Graph Self-Correction
  Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong
  ICLR 2022 Workshop on Geometrical and Topological Representation Learning.[paper]

• A Unified Random Walk, Its Induced Laplacians and Spectral Convolutions for Deep Hypergraph Learning
  Jiying Zhang, Fuyang Li, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, Yatao Bian
  TPAMI Under Review

Research Experience

IDEA (2023.07-present)

• Assistant Researcher

Tencent AI Lab (2021.02 - 2022.08) (The Tencent Rhino-bird Elite Talent Program)

• Research Intern, Machine Learning Group, Tencent AI Lab, Shenzhen, China
• Work with: Yatao Bian, Yu Rong

Tencent AI Lab (2019.11- 2020.06)

• Research Intern, Machine Learning Group, Tencent AI Lab, Shenzhen, China
• Work with: Tingyang Xu

Services

• Conference Reviewing: NeurIPS-2024, NeurIPS-2023, NeurIPS 2023 Workshop Diffusion, NeurIPS-2022, ICML-2022, ICML-2023, ICML-2024, ICLR-2024, ICLR-2025, CVPR-2024, ACMMM-2024, AAAI-2024, BIBM-2024, ICASSP-2023,2024.
• Journal Reviewing: TPAMI.