Meng Liu [刘猛]

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 research interests are deep learning and machine learning. Specifically, I am currently working on (1) deep learning on graphs and molecules, and (2) generative energy-based models.

News

09/2021

Our paper DIG: A Turnkey Library for Diving into Graph Deep Learning Research has been accepted to JMLR.

06/2021

We won a Runner-up award of KDD Cup on Open Graph Benchmark Large-Scale Challenge (OGB-LSC). More details are in Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks.

04/2021

Our paper GraphEBM: Molecular Graph Generation with Energy-Based Models has been accepted to EBM Workshop at ICLR2021!

03/2021

Our python library DIG: Dive into Graphs is released! DIG provides a unified testbed for advanced graph deep learning tasks, such as graph generation, self-supervised learning, explainability, and 3D graphs.

Publications [Google Scholar]

* indicates equal contribution.

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

Paper Code

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.

Paper Code

Documentation

GraphEBM: Molecular Graph Generation with Energy-Based Models

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

EBM Workshop at ICLR, 2021.

Paper Code

Towards Deeper Graph Neural Networks

Meng Liu, Hongyang Gao, and Shuiwang Ji

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

Paper Code

Paper collection

Non-Local Graph Neural Networks

Meng Liu*, Zhengyang Wang*, and Shuiwang Ji

Preprint, 2020.

Paper Paper collection

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*, and Shuiwang Ji

Preprint, 2020.

Paper Code Supplement

Spherical Message Passing for 3D Graph Networks

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

Preprint, 2021.

Paper Code

Services

Program Committee Member & Reviewer

Annual Conference on Neural Information Processing Systems (NeurIPS) 2021

International Conference on Machine Learning (ICML) 2021

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

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

IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

BMC Bioinformatics

NeurIPS Workshop AI4Science 2021

Résumé

My résumé is available here.

Texas A&M University Aug 2019 - now

Ph.D. Student
Advisor: Prof. Shuiwang Ji
Computer Science & Engineering
Fujitsu Research of America Summer 2021

Research Intern
Mentor: Dr. Kanji Uchino
Tsinghua University Aug 2015 - Jul 2019

B.E. Student
Advisor: Prof. Liangrui Peng
Electronic Engineering
Owlii Inc. Summer 2018

R&D Intern
Mentor: Yi Xu