Meng Liu [刘猛]

Ph.D. Student, Texas A&M University

mengliu [AT] tamu.edu

Bio

Howdy! I am currently a 4th-year Ph.D. student in the Department of Computer Science & Engineering, Texas A&M University. My advisor is Prof. Shuiwang Ji, who leads the Data Integration, Visualization, and Exploration (DIVE) Laboratory. I obtained my bachelor’s degree from the Department of Electronic Engineering, Tsinghua University in 2019, advised by Prof. Liangrui Peng. Here is my CV.

My research interests are deep learning and machine learning. Specifically, I am currently working on (1) geometric deep learning, (2) AI for science, and (3) generative modeling.

News

Publications [Google Scholar]

* indicates equal contribution.

2023

Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models

Meng Liu, Haoran Liu, and Shuiwang Ji

International Conference on Learning Representations (ICLR), 2023

2022

Generating 3D Molecules for Target Protein Binding

Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, and Shuiwang Ji

International Conference on Machine Learning (ICML), 2022

Oral/Long Presentation (118/5630=2.1% acceptance rate)

GraphFM: Improving Large-Scale GNN Training via Feature Momentum

Haiyang Yu*, Limei Wang*, Bokun Wang*, Meng Liu, Tianbao Yang, and Shuiwang Ji

International Conference on Machine Learning (ICML), 2022

Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery

Zhengyang Wang*, Meng Liu*, Youzhi Luo*, Zhao Xu*, Yaochen Xie*, Limei Wang*, Lei Cai*, Qi Qi, Zhuoning Yuan, Tianbao Yang, and Shuiwang Ji

Bioinformatics, 2022

Rank #1 on AI Cures open challenge for COVID-19

Spherical Message Passing for 3D Molecular Graphs

Yi Liu*, Limei Wang*, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, and Shuiwang Ji

International Conference on Learning Representations (ICLR), 2022

Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences

Meng Liu and Shuiwang Ji

SIAM International Conference on Data Mining (SDM), 2022

2021

Non-Local Graph Neural Networks

Meng Liu*, Zhengyang Wang*, and Shuiwang Ji

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks

Meng Liu*, Cong Fu*, Xuan Zhang, Limei Wang, Yaochen Xie, Hao Yuan, Youzhi Luo, Zhao Xu, Shenglong Xu, and Shuiwang Ji

AI4Science Workshop at NeurIPS, 2021

Awardee of KDD Cup 2021 on OGB-LSC

DIG: A Turnkey Library for Diving into Graph Deep Learning Research

Meng Liu*, Youzhi Luo*, Limei Wang*, Yaochen Xie*, Hao Yuan*, Shurui Gui*, Haiyang Yu*, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, and Shuiwang Ji

Journal of Machine Learning Research (JMLR), 2021

Join the DIG slack community!

GraphEBM: Molecular Graph Generation with Energy-Based Models

Meng Liu, Keqiang Yan, Bora Oztekin, and Shuiwang Ji

EBM Workshop at ICLR, 2021

2020

Towards Deeper Graph Neural Networks

Meng Liu, Hongyang Gao, and Shuiwang Ji

ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2020

Preprint

DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding

Haitao Lin*, Yufei Huang*, Meng Liu, Xuanjing Li, Shuiwang Ji, and Stan Z. Li

Your Neighbors Are Communicating: Towards Powerful and Scalable Graph Neural Networks

Meng Liu, Haiyang Yu, and Shuiwang Ji

Services

Session Chair

International Conference on Machine Learning (ICML) 2022

Program Committee Member & Reviewer [Selected]

Annual Conference on Neural Information Processing Systems (NeurIPS) 2021, 2022 (Award)

NeurIPS Track Datasets and Benchmarks 2022

International Conference on Machine Learning (ICML) 2021, 2022 (Award), 2023

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2021, 2022

International Conference on Learning Representation (ICLR) 2020, 2021, 2022, 2023

International Conference on Computer Vision (ICCV) 2023

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022, 2023

European Conference on Computer Vision (ECCV) 2022

IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023

SIAM International Conference on Data Mining (SDM) 2022

Journal of Machine Learning Research (JMLR)

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

Transactions on Machine Learning Research (TMLR)

Neurocomputing

IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

BMC Bioinformatics

Vitæ

Here is my CV[PDF].

  • Texas A&M University Aug 2019 - now
    Ph.D. Student
    Advisor: Prof. Shuiwang Ji
    Computer Science & Engineering
  • Google Fall 2022
    Research Intern
    Mentor: Zheyun Feng, Boqing Gong
  • Meta AI Summer 2022
    Research Intern
    Mentor: Xing Wang
  • Fujitsu Research of America Summer 2021
    Research Intern
    Mentor: Kanji Uchino
  • Tsinghua University Aug 2015 - Jul 2019
    B.E. Student
    Advisor: Prof. Liangrui Peng
    Electronic Engineering
  • Owlii Summer 2018
    R&D Intern
    Mentor: Yi Xu