Yusong Wang

I received my B.S. in the Special Class for the Gifted Young (SCGY) program at Xi'an Jiaotong University, majoring in Automation. Currently, I am a third-year Ph.D. candidate jointly trained at Microsoft Research Asia and Institute of Artificial Intelligence and Robotics in Xi'an Jiaotong University, under the supervision of Dr. Bin Shao and Academician of Chinese Academy of Engineering, Dr. Nanning Zheng.

I served as a research intern at Microsoft Research AI4Science supervised by Dr. Bin Shao from July 2020.

Email: yusowa0716 [at] gmail [dot] com

CV / Github / Google Scholar

Research Interests

I'm primarily interested in AI4Science, particularly in machine learning force fields. Recently, I've developed a strong interest in Generative AI as well. I'm dedicated to using generative models to explore new solutions in science, including potential energy surface sampling, protein-ligand docking, etc. Representative papers are highlighted.

News

[Sep. 2024] New!! One paper was accepted at NeurIPS 2024.

Selected Publications

	Neural P³M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs Yusong Wang, Chaoran Cheng, Shaoning Li, Yuxuan Ren, Bin Shao, Ge Liu, Pheng-Ann Heng, Nanning Zheng, 38th Conference on Neural Information Processing Systems* (NeurIPS 2024) Molecule representation learning; Long-range interaction modeling; Geometric GNNs [Paper]
	Improving AlphaFlow for Efficient Protein Ensembles Generation Shaoning Li, Mingyu Li, Yusong Wang, Xinheng He, Nanning Zheng, Jian Zhang, Pheng-Ann Heng, 41st International Conference on Machine Learning (ICML 2024 AI4Science workshop) Protein ensembles generation; Flow matching; AlphaFold [Paper]
	Highly accurate carbohydrate-binding site prediction with DeepGlycanSite Xinheng He, Lifen Zhao, Yinping Tian, Rui Li, Qinyu Chu, Zhiyong Gu, Mingyue Zheng, Yusong Wang, Shaoning Li, Hualiang Jiang, Yi Jiang, Liuqing Wen, Dingyan Wang, Xi Cheng, Nature Communications (NC 2024) Binding sites predictoin; Carbohydrates [Paper]
	F³low: Frame-to-Frame Coarse-grained Molecular Dynamics with SE(3) Guided Flow Matching Shaoning Li, Yusong Wang, Mingyu Li, Jian Zhang, Bin Shao, Nanning Zheng, Jian Tang 12th International Conference on Learning Representations* (ICLR 2024 GEM workshop) Coarse-grained protein dynamics; SE(3) Flow matching [Paper]
	Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran Wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu 12th International Conference on Learning Representations (ICLR 2024) Machine learning force fields; Equivariant graph neural networks; Long-range Interaction [Paper] [Code]
	Geometric Transformer with Interatomic Positional Encoding Yusong Wang, Shaoning Li, Tong Wang, Bin Shao, Nanning Zheng, Tie-Yan Liu 37th Conference on Neural Information Processing Systems (NeurIPS 2023) Molecule representation learning; Transformers; Positional encoding [Paper] [Code]
	Enhancing geometric representations for molecules with equivariant vector-scalar interactive message passing Yusong Wang, Tong Wang, Shaoning Li, Xinheng He, Mingyu Li, Zun Wang, Nanning Zheng, Bin Shao, Tie-Yan Liu Nature Communications* (NC 2024) Molecular dynamics; Machine learning force fields; Equivariant graph neural networks Editor's Highlights in AI and Bio [Paper] [Code] [Blog]
	Improved drug-target interaction prediction with intermolecular graph transformer Siyuan Liu, Yusong Wang, Yifan Deng, Liang He, Bin Shao, Jian Yin, Nanning Zheng, Tie-Yan Liu, Tong Wang Briefings in Bioinformatics (Brief. Bioinformatics 2022) Protein-ligand docking; Graph Transformer [Paper] [Code]