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. My résumé is available here.
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
My résumé is available here.
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Texas A&M University Aug 2019 - now
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Meta Summer 2022Research Intern
Mentor: Xing Wang -
Fujitsu Research of America Summer 2021Research Intern
Mentor: Kanji Uchino -
Tsinghua University Aug 2015 - Jul 2019
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Owlii Summer 2018R&D Intern
Mentor: Yi Xu