avatar

Liang Wang

Hi! I am Liang Wang, a fourth-year PhD student at Institute of Automation, Chinese Academy of Sciences (CASIA). I am a member of NLPR and advised by Liang Wang, Shu Wu, and Qiang Liu. Previously, I received a B.E. in Software Engineering from Tongji University.
Email: liang.wang[at]cripac.ia.ac.cn

Google Scholar / Github / CV[PDF]

Research Interests

AI for Science Graph Machine Learning Data Mining

News
Education
PhD (selected for the PhD honors program)
    at Institute of Automation, Chinese Academy of Sciences
2021 - 2026 (Expected)

    Major: Pattern Recognition and Intelligent Systems

Bachelor
    at Tongji University
2017 - 2021

    Major: Software Engineering

Selected Publications
(Full Publication List)
AI for Science
  • MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra
    Liang Wang, Shaozhen Liu, Yu Rong, Deli Zhao, Qiang Liu, Shu Wu, Liang Wang
    ICLR 2025
    [Paper] [Code]
  • Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction
    Liang Wang, Qiang Liu, Shaozhen Liu, Xin Sun, Shu Wu, Liang Wang
    NeurIPS 2024
    [Paper] [Code] [Poster]
Graph Machine Learning
  • Rethinking Graph Masked Autoencoders through Alignment and Uniformity
    Liang Wang*, Xiang Tao*, Qiang Liu, Shu Wu, Liang Wang
    AAAI 2024
    [Paper] [Code] [Poster]
  • DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization
    Xin Sun, Liang Wang, Qiang Liu, Shu Wu, Zilei Wang, Liang Wang
    KDD 2024
    [Paper]
  • GSLB: The Graph Structure Learning Benchmark
    Zhixun Li, Liang Wang, Xin Sun, Yifan Luo, Yanqiao Zhu, Dingshuo Chen, Yingtao Luo, Xiangxin Zhou, Qiang Liu, Shu Wu, Liang Wang, Jeffrey Xu Yu
    NeurIPS 2023
    [Paper] [Code]
Data Mining
  • S2DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion
    Tengfei Ma, Yujie Chen, Liang Wang, Xuan Lin, Bosheng Song, Xiangxiang Zeng
    AAAI 2025 (Oral)
    [Paper]
  • Bi-Level Graph Structure Learning for Next POI Recommendation
    Liang Wang, Shu Wu, Qiang Liu, Yanqiao Zhu, Xiang Tao, Mengdi Zhang, Liang Wang
    IEEE Transactions on Knowledge and Data Engineering 2024
    [Paper]
  • Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection
    Xiang Tao, Liang Wang, Qiang Liu, Shu Wu, Liang Wang
    WWW 2024
    [Paper]
Projects
PyGCL

An easy-to-use library for graph contrastive learning with PyTorch. It implements a wide variety of contrastive objectives, data augmentations, contrasting modes and other utilities useful for implementing and evaluating contrastive learning on graphs.

GSLB

An open-source library built for easy implementation and evaluation of graph structure learning model family. It offers a versatile control of graph dataset loading, structure learners, structure processors, and a bunch of reproduced models.

Services
Conference Reviewer
  • Conference on Neural Information Processing Systems (NeurIPS), 2024, 2025
  • International Conference on Learning Representations (ICLR), 2025
  • International Conference on Machine Learning (ICML), 2025
  • ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024, 2025
  • International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Journal Reviewer
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)