I am a 3rd year PhD student in School of Information at University of Michigan, where I am advised by Prof.Daniel Romero. My research interest is broadly in computational social science and information diffusion. I apply data science methods including causal inference, network analysis, natural language processing, and machine learning, to measure, understand, and promote creativity and innovation in various domains, such as science, art, and organization.


  • Gendered Citation Patterns Among the Scientific Elite [Proceedings of the National Academy of Sciences (PNAS) 119 (40), e2206070119, 2022, Link]
    Kristina Lerman, Yulin Yu, Fred Morstatter, Jay Pujara
  • Large-Scale Analysis of New Employee Network Dynamics [WWW 2023 (upcoming)]
    Yulin Yu, Longqi Yang, Siân Lindley, Mengting Wan
  • Novelty in what sense? Heterogeneous relationships between novelty and popularity in music [ICWSM 2023 (upcoming), IC2S2 2021, Special Recognition Award]
    Yulin Yu, Ben Cheung, Yong-Yeol Ahn, Paramveer Dhillon [arXiv]
  • For more please see CURRICULUM VITAE

Honors and Awards

  • Special Recognition Award , 7th International Conference on Computational Social Science, 2021 (Music Novelty Paper)

    Research Internship