Scholar
Meng Liu
Google Scholar ID: MlX5wLcAAAAJ
Research Scientist, NVIDIA
Citations & Impact
Citations
2,735
H-index
16
i10-index
20
Publications
20
Co-authors
34
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Publications:
- - GenMol: A Drug Discovery Generalist with Discrete Diffusion (ICML, 2025)
- - Molecule Generation with Fragment Retrieval Augmentation (NeurIPS, 2024)
- - DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding (Chemical Science, 2024)
- - On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods (ICLR, 2024)
- - Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm (TMLR, 2024)
- - Video Timeline Modeling for News Story Understanding (NeurIPS, 2023)
- - QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules (NeurIPS, 2023)
- - Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization (NeurIPS, 2023)
- - Graph Mixup with Soft Alignments (ICML, 2023)
- - Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models (ICLR, 2023)
- - Generating 3D Molecules for Target Protein Binding (ICML, 2022)
- - GraphFM: Improving Large-Scale GNN Training via Feature Momentum (ICML, 2022)
- - Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery (Bioinformatics, 2022)
- - Spherical Message Passing for 3D Molecular Graphs (ICLR, 2022)
Research Experience
- Interned at Google, Meta, and Fujitsu during his doctoral study.
Education
- Ph.D. in Computer Science from Texas A&M University in 2023, supervised by Prof. Shuiwang Ji; B.S. in Electronic Engineering from Tsinghua University in 2019, advised by Prof. Liangrui Peng.
Background
- Research Interests: AI-driven drug discovery; Field: Computer Science; Brief Introduction: Currently a Research Scientist at NVIDIA, focusing on AI-driven drug discovery.
