Meng Liu [刘猛]

Ph.D. Student, Texas A&M University

mengliu [AT] tamu.edu

Bio

Howdy! I am currently a 3rd 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 résumé.

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

News

Publications [Google Scholar]

* indicates equal contribution.

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

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

AI for Science Workshop at NeurIPS, 2021

[Runner-up award of KDD Cup 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

GraphEBM: Molecular Graph Generation with Energy-Based Models

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

EBM Workshop at ICLR, 2021

Towards Deeper Graph Neural Networks

Meng Liu, Hongyang Gao, and Shuiwang Ji

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

Services

Program Committee Member & Reviewer [Selected]

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

International Conference on Machine Learning (ICML) 2021, 2022

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

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

Résumé

Here is my résumé.