Howdy! I am currently a Ph.D. candidate in the Department of Computer Science & Engineering, Texas A&M University, advised by Prof. Shuiwang Ji. 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. I am currently working on the following directions and their intersections.
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Xuan Zhang*, Limei Wang*, Jacob Helwig*, Youzhi Luo*, Cong Fu*, Yaochen Xie*, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, YuQing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess Smidt, Shuiwang Ji
DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
Haitao Lin*, Yufei Huang*, Meng Liu, Xuanjing Li, Shuiwang Ji, and Stan Z. Li
Empowering GNNs via Edge-Aware Weisfeiler-Lehman Algorithm
Meng Liu, Haiyang Yu, and Shuiwang Ji
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
Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 2023
Spotlight
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules
Haiyang Yu*, Meng Liu*, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, and Shuiwang Ji
Neural Information Processing Systems (NeurIPS), Track on Datasets and Benchmarks, 2023
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization
Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji
Neural Information Processing Systems (NeurIPS), 2023
Graph Mixup with Soft Alignments
Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, and Na Zou
International Conference on Machine Learning (ICML), 2023
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models
Meng Liu, Haoran Liu, and Shuiwang Ji
International Conference on Learning Representations (ICLR), 2023
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 (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
AI4Science Workshop at NeurIPS, 2021
Awardee of KDD Cup 2021 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
International Conference on Machine Learning (ICML) 2022
Annual Conference on Neural Information Processing Systems (NeurIPS) 2021, 2022 (Award), 2023
NeurIPS Track Datasets and Benchmarks 2022, 2023
International Conference on Machine Learning (ICML) 2021, 2022 (Award), 2023
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2021, 2022
International Conference on Learning Representation (ICLR) 2020, 2021, 2022, 2023, 2024
International Conference on Computer Vision (ICCV) 2023
IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022, 2023
European Conference on Computer Vision (ECCV) 2022
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023
SIAM International Conference on Data Mining (SDM) 2022
Journal of Machine Learning Research (JMLR)
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
Transactions on Machine Learning Research (TMLR)
Neurocomputing
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
BMC Bioinformatics
Here is my CV[PDF].