• Physics-Inspired Geometric Pretraining for Molecule Representation
    Tutorial, AAAI, Vancouver, Canada, 20th Feb, 2024
    [Link] [Website]

  • AI for Molecule Discovery with Multi-Modal Knowledge
    Ph.D. Defense, Mila-UdeM, 20th July, 2023
    [Slides] [Paper]

  • 将深度学习与分子学习结合：从拓扑、几何和文本角度进行解析
    知乎文章 & blog, 25th June, 2023

  • Molecule Representation Learning and Discovery: A Perspective from Topology, Geometry, and Textual Description
    University of California, Berkeley, 16th March, 2023

  • ProteinDT: A Text-guided Protein Design Framework
    NRC NLP seminar, 10th March, 2023

  • Molecule Representation Learning and Discovery: A Perspective from Topology, Geometry, and Textual Description
    M2D2, 14th Feb, 2023

  • GraphCG: Unsupervised Discovery of Steerable Factors in Graphs
    LOG, Meetup @ Mila, 12th Dec, 2022
    [Slides]

  • Self-Supervised Pretraining with 3D Molecular Geometry
    Huawei, 18th July, 2022
    [Slides]

  • Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
    AI Times, 31st March, 2022
    [Slides]

  • Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
    Graph Reading Group, Mila, 24th Feb, 2022
    [Slides]

  • Pre-training Molecular Graph Representation with 3D Geometry – Rethinking Self-Supervised Learning on Structured Data
    NLP Reading Group, University of Oxford, 11th Feb, 2022
    [Slides]

  • Molecular Representation Learning with Limited Data
    Predoc-3 Presentation, Mila-UdeM, 9th Dec, 2021
    [Slides]