Yulin Yu is a 4th year PhD student in School of Information at University of Michigan, advised by Prof.Daniel Romero. Her research leaveges big data, AI, and network science to investigate the drivers of innovation across a range of contexts. Yulin’s current work focuses on understanding how scientific innovation can advance through the novel use of ‘big data’ and how we can automate innovation via predicting the need or use of novel datasets. Her contributions to innovation-related research extend to the effect of organizational dynamics on precursors to innovation (WWW 2023, WWW 2024), gender differences in research recognition (PNAS 2022), and the relationship between novelty and popularity in music (ICWSM 2023).


  • Gendered Citation Patterns Among the Scientific Elite [Proceedings of the National Academy of Sciences (PNAS) 119 (40), e2206070119, 2022] [Link] [Poster]
    Kristina Lerman, Yulin Yu, Fred Morstatter, Jay Pujara
  • 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
  • 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]
  • 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