Meng Liu [刘猛]

Research Scientist, NVIDIA

mengliu [AT] tamu.edu, menliu [AT] nvidia.com

Bio

I am a Research Scientist at NVIDIA, focusing on AI-driven drug discovery. Prior to that, I received my Ph.D. degree in Computer Science from Texas A&M University in 2023, under the supervision of Prof. Shuiwang Ji. During my doctoral study, I've interned at Google, Meta, and Fujitsu. I earned my bachelor's degree in Electronic Engineering from Tsinghua University in 2019, advised by Prof. Liangrui Peng.

Publications [Google Scholar]

(* indicates equal contribution and † indicates equal Advising.)

GenMol: A Drug Discovery Generalist with Discrete Diffusion

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Weili Nie†, and Arash Vahdat†

International Conference on Machine Learning (ICML), 2025

Paper

Molecule Generation with Fragment Retrieval Augmentation

Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Arash Vahdat†, and Weili Nie†

Advances in Neural Information Processing Systems (NeurIPS), 2024

Paper Code

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

Haitao Lin*, Yufei Huang*, Odin Zhang*, Siqi Ma, Meng Liu, Xuanjing Li, Lirong Wu, Shuiwang Ji, Tingjun Hou, and Stan Z. Li

Chemical Science, 2024

Paper Code

On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods

Montgomery Bohde*, Meng Liu*, Alexandra Saxton, and Shuiwang Ji

International Conference on Learning Representations (ICLR), 2024

Spotlight

Paper

Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm

Meng Liu, Haiyang Yu, and Shuiwang Ji

Transactions on Machine Learning Research (TMLR), 2024

Paper Paper collection

Video Timeline Modeling for News Story Understanding

Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, and Boqing Gong

Advances in Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 2023

Spotlight

Paper Code

QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules

Haiyang Yu*, Meng Liu*, Youzhi Luo, Alex Strasser, Xiaofeng Qian†, Xiaoning Qian†, and Shuiwang Ji†

Advances in Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 2023

Paper Code

Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization

Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, and Shuiwang Ji

Advances in Neural Information Processing Systems (NeurIPS), 2023

Paper Code

Graph Mixup with Soft Alignments

Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji†, and Na Zou†

International Conference on Machine Learning (ICML), 2023

Paper Code

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

Meng Liu, Haoran Liu, and Shuiwang Ji

International Conference on Learning Representations (ICLR), 2023

Paper Code

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 (2.1% acceptance rate)

Paper Code Video

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

Paper Code

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

Paper Code Supplement

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

Paper Code

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

Meng Liu and Shuiwang Ji

SIAM International Conference on Data Mining (SDM), 2022

Paper Code Supplement

Non-Local Graph Neural Networks

Meng Liu*, Zhengyang Wang*, and Shuiwang Ji

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

Paper Code Paper collection

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

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

Vitæ

Here is my CV[PDF].

Meng Liu
based on the templates by Martin Saveski and Paul J. Wright