Yulin Yu
Scholar

Yulin Yu

Google Scholar ID: sk7Z3dYAAAAJ
University of Michigan
Computational Social ScienceInnovationCreativityImpact of AI on SocietyFuture of Work
Citations & Impact
All-time
Citations
119
 
H-index
6
 
i10-index
4
 
Publications
10
 
Co-authors
5
list available
Resume (English only)
Academic Achievements
  • Publications: PNAS 2024 - Does the use of unusual combinations of datasets contribute to greater scientific impact?; CSCW '24 - Characterizing the Structure of Online Conversations Across Reddit; WWW '24 - Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee Departures; ICWSM'23 - Novelty in what sense? Heterogeneous relationships between novelty and popularity in music; WWW '23 - Large-Scale Analysis of New Employee Network Dynamics; PNAS'22 - Gendered Citation Patterns Among the Scientific Elite. Awards: EECS RISING STAR, Massachusetts Institute of Technology, 2024; CEW+ Scholar, University of Michigan, 2024; Special Recognition Award, 7th International Conference on Computational Social Science, 2021 (Music Novelty Paper). Research Internships: PhD research intern at Microsoft Research, mentors: Dr. Scott Counts & Dr. Siddharth Suri (2025.4-2025.8); PhD research intern at Microsoft / Office of Applied Research, mentors: Dr. Mengting Wan, Dr. Longqi Yang, & Dr. Siân Lindley (2022.5-2022.8).
Research Experience
  • Future of Work: How Gen-AI shapes communication and work practices, and how different stages of AI development influence social networks in society and the workplace; Social Network and Information Diversity: In the AI era, how LLMs revolutionize the diversity of information and idea diffusion.
Education
  • Ph.D. from the University of Michigan School of Information, advised by Dr. Daniel Romero; currently visiting the Northwestern Institute on Complex Systems (NICO), working with Dr. Brian Uzzi.
Background
  • Research Interests: Human-AI interaction and innovation, with a focus on the impact of disruptive technologies on people and society. Her current research examines how big data and AI transform the ways people explore, think, and innovate across science, art, and the technology workplace.