Email: yulinyu@umich.edu

CURRICULUM VITAE

About

Life update! I’ll be joining the University of Arizona, College of Information Science, as a tenure-track Assistant Professor in Fall 2026. Before that, I’ll be a postdoctoral fellow with Dr. Brian Uzzi at NICO and the Kellogg School of Management at Northwestern University, and visiting Microsoft Research.

Yulin Yu is a computational social scientist studying human–AI interaction and innovation, with a focus on how disruptive technologies impact 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. As a human-centric data scientist, she analyzes large-scale digital trace data by developing and applying computational and statistical frameworks. She is a PhD candidate at the University of Michigan’s School of Information, advised by Prof.Daniel Romero. Her work centers on three main themes:

  1. Exploration and Creativity: Exploration and creativity is the foundation of innovation. (1) As science and society become increasingly data-driven, how does data change the way we conduct impactful science, and how can the creative use of datasets drive scientific innovation? (PNAS 2024); (2) How do AI transform how we explore knowledge and creative content? (ICWSM 2023)
  2. Future of work: Work habits and patterns significantly shape innovation outcomes. How do Gen-AI shape communication and work practices? How do different stages of AI development influence social networks in society and the workplace? (WWW 2023)
  3. Social Network and information diversity: Social networks and information diversity, which bring together ideas from different people and sources, drive innovation. In the AI era, how can LLMs revolutionize the diversity of information and idea diffusion? Equally important is understanding how various social factors influence social network and information diffusion and how to quantify these effects (PNAS 2022, WWW 2023, WWW 2024, EPJ DataSci 2025, CSCW 2024).

Publications

  • Does the use of unusual combinations of datasets contribute to greater scientific impact? [PNAS'24: Proceedings of the National Academy of Sciences ] [Link]
    Yulin Yu, Daniel Romero
  • Characterizing the Structure of Online Conversations Across Reddit [CSCW '24: Proceedings of the ACM on Human-Computer Interaction 2024, ] [Link]
    Yulin Yu, Julie Jiang, Paramveer Dhillon
  • Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee Departures [WWW '24: Proceedings of the ACM Web Conference 2024, ] [Link]
    David Gamba,Yulin Yu, Yuan Yuan, Grant Schoenebeck, Daniel Romero
  • Novelty in what sense? Heterogeneous relationships between novelty and popularity in music [ICWSM'23: Proceedings of the Seventeenth International AAAI Conference on Web and Social Media, IC2S2 2021, Special Recognition Award]
    Yulin Yu, Ben Cheung, Yong-Yeol Ahn, Paramveer Dhillon [Link] [Slide]
  • Large-Scale Analysis of New Employee Network Dynamics [WWW '23: Proceedings of the ACM Web Conference 2023, ] [Link] [Slide]
    Yulin Yu, Longqi Yang, Siân Lindley, Mengting Wan
  • Gendered Citation Patterns Among the Scientific Elite [ PNAS'22: Proceedings of the National Academy of Sciences 119 (40), e2206070119, 2022] [Link] [Poster]
    Kristina Lerman, Yulin Yu, Fred Morstatter, Jay Pujara
  • For more please see CURRICULUM VITAE

Honors and 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