The highest activity a human being can attain is learning for understanding, because to understand is to be free. – Baruch Spinoza

I am Yutong Xie (谢雨桐), a Ph.D. student at the School of Information, University of Michigan, advised by Prof. Qiaozhu Mei in the Foreseer Group. Prior to this, I received my Bachelor’s degree from Shanghai Jiao Tong University as a member of the ACM Class, advised by Prof. Yong Yu and Prof. Weinan Zhang.

My research interests lie in machine learning methods for both explicitly and implicitly structured data (e.g., graphs, networks and texts) as well as their applications to natural and social science problems like drug discovery.

Email: yutxie AT umich DOT edu
Links: GitHub, Google Scholar


University of Michigan, Sep. 2020 – Present
Ph.D. in Information Science

Shanghai Jiao Tong University, Sep. 2016 – Jun. 2020
B.Eng. in Computer Science (Zhiyuan Honors Degree)


Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection
Ting Long*, Yutong Xie*, Xianyu Chen, Weinan Zhang, Qingxiang Cao, Yong Yu.
AAAI Conference on Artificial Intelligence (AAAI), 2022.

MARS: Markov Molecular Sampling for Multi-objective Drug Discovery
Yutong Xie, Chence Shi, Hao Zhou, Yuwei Yang, Weinan Zhang, Yong Yu, Lei Li.
International Conference on Learning Representations (ICLR), 2021.
Spotlight presentation (top 5%).
[code] [video] [video (ZH)]

Visual Rhythm Prediction with Feature-Aligned Network
Yutong Xie, Haiyang Wang, Zihao Xu, Yan Hao.
IAPR International Conference on Machine Vision Applications Conference (MVA), 2019.

(* = equal contribution)

Work Experience

ByteDance AI Lab, Feb. 2020 – Sep. 2020
Research intern, advised by Dr. Lei Li and Dr. Hao Zhou.