University of Michigan School of Information
Yutong Xie
Research Areas
Biography
I am a Ph.D. candidate in the School of Information at the University of Michigan, where I 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
have a general research interest in exploring the potential of AI to support and drive innovation, with a specific focus on its applications in both scientific research (AI for science) and creative processes (AI for creativity). My research encompasses three key aspects: identifying the innovation space ("What to innovate"), devising computational methodologies for innovative breakthroughs ("How to innovate"), and establishing robust criteria for evaluating these innovations ("How to evaluate"). A significant part of my work involves examining the synergistic relationship between AI and human intelligence in the innovation landscape. Additionally, I am keenly interested in the application and enhancement of large language models, particularly in the context of fostering effective human-AI collaboration for innovative endeavors.
Pronouns
she/her
Areas of interest
AI for Science, AI for Creativity, AI Behavioral Science, Large Language Models
Honors & Awards
Barbour Scholarship, 2024;
D. E. Shaw Research Graduate and Postdoctoral Women’s Fellowship, 2023;
UMSI Outstanding Graduate Student Instructor Award Nominee, University of Michigan, 2022;
Ph.D. Pre-candidacy Paper Passed with Distinction, University of Michigan, 2021;
Best Innovation Award, Bytedance AI Lab Computational Intelligence Tech Day, 2020
Education
University of Michigan, Ann Arbor, MI, USA Sep. 2020 – Present
Ph.D. Candidate in Information Science;
Shanghai Jiao Tong University, Shanghai, China Sep. 2016 – Jun. 2020
B.Eng. in Computer Science (Zhiyuan Honors Degree)