Yutong Xie   谢雨桐

I am a Ph.D. student in the School of Information at the University of Michigan. I currently work with Prof. Qiaozhu Mei as a member of the Foreseer Research Group. Prior to this, I received my Bachelor's degree from Shanghai Jiao Tong University as a member of the ACM Honors Class, where I was advised by Prof. Yong Yu and Prof. Weinan Zhang.

I am enthusiastic about exploring the potential of AI for science and AI for creativity. My focus is on using AI to tackle complex computational tasks in scientific research and creative endeavors, which can often be framed as machine learning problems such as prediction, optimization, and generation. I am also interested in examining how AI would collaborate with domain experts such as scientists and artists, and how we can promote such collaborations.

  For more information, please check my curriculum vitae.
  yutxie AT umich DOT edu, yutongxie98 AT gmail DOT com
  Google Scholar, Semantic Scholar, Github, Twitter, LinkedIn

NEW! Our paper on text-to-image prompt analysis was accepted by WWW 2023 on the Creative Web Track!
NEW! Our paper on chemical space exploration measures was accepted by ICLR 2023!

Selected Publications

For the full publication list, please refer to my Google Scholar profile.

A Prompt Log Analysis of Text-to-Image Generation Systems
Yutong Xie*, Zhaoying Pan*, Jinge Ma*, Jie Luo, Qiaozhu Mei.
The ACM Web Conference (WWW), 2023 (The Creative Web Track).

How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules
Yutong Xie, Ziqiao Xu, Jiaqi Ma, Qiaozhu Mei.
International Conference on Learning Representations (ICLR), 2023.
[Code] [SlidesLive] [Slides] [Poster]

Multi-View Graph Representation for Programming Language Processing: An Investigation into Algorithm Detection
Ting Long*, Yutong Xie*, Xianyu Chen, Weinan Zhang, Qinxiang Cao, Yong Yu.
AAAI Conference on Artificial Intelligence (AAAI), 2022 (acceptance rate 15%).
[Code] [Slides] [Poster]

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] [SlidesLive] [Slides] [Poster] [AI Time] [WeChat Article]

* = equal contribution