About Me

I'm Yubai Yuan, an assistant professor in Statistics at Penn State University. I received my PhD degree in Department of Statistics at University of Illinois Urbana-Champaign in 2020, under the supervision of Prof. Annie Qu [link]. From 2020 to 2022, I was postdoc scholar in the Department of Statistics at UC Irvine, advised by Prof. Annie Qu. My current research focuses on complex network analysis, information diffusion and cascade, hypergraph modeling, and optimal-transport-based data integration .

My research interests are community detection, link prediction, meidation analysis and causal inference, and active learning. I am recruiting students in statistics and related fields. Please email me Email if you are interested about the above areas.

Publications and papers under review

  • Yuan, Y. & Qu, A. (2021) Community detection with dependent connectivity. Annals of Statistics, 49(4), 2378-2428. [link] 2019 ASA Student Paper Competition Award from Statistical Learning and Data Science Section
  • Yuan, Y. & Qu, A. (2021) High-order joint embedding for multi-level link prediction. Journal of American Statistical Association, accepted. [link]
  • Deng, Y.*, Yuan, Y.*, H, Fu., & Qu, A. (2021) Query-augmented active metric learning. Journal of American Statistical Association, accepted. (* co-first author) [link] 2021 ICSA Student Paper Award
  • Bi, X., Tang, X., Yuan, Y., Zhang, Y., & Qu, A. (2021). Tensors in statistics. Annual Review of Statistics and Its Application, 8, 345-368. [link]
  • Yuan, Y., Deng, Y., Zhang, Y., & Qu, A. (2020). Deep learning from a statistical perspective. Stat, 9(1), e294. [link]
  • Allison, S., Hamilton, K., Yuan, Y., & Hague, G.(2020) Assessment of progressive muscle relaxation (PMR) as a stress-reducing technique for first-year veterinary students. Journal of Veterinary Medical Education, 47(6), 737-744.
  • Yuan, Y., & Qu, A. De-confounding causal inference via latent multiple mediators. Journal of American Statistical Association, accepted.
  • Xu, Q., Yuan, Y., Wang J., & Qu, A. Crowdsourcing utilizing subgroup structure of latent factor modeling. (2023+) Journal of American Statistical Association, accepted. 2022 ASA Student Paper Competition Award from Statistical Learning and Data Science Section
  • Zhang, J., Yuan, Y., & Qu, A. A tensor factorization recommender system with dependency. (2022) Electronic Journal of Statistics, 16, 2175-2205.
  • Li, D., Yuan, Y., Zhang X., & Qu, A. Joint modeling of change-point identification and dependent dynamic community detection. (2022+) Statistica Sinica, Accepted.
  • Yuan, Y., Shahbaba, B., Fortin, N., Nie, Q., & Qu, A. Optimal Transport for Latent Integration with An Application to Heterogeneous Neuronal Activity Data. Journal of American Statistical Association, Invited resubmission.

    • Under review

  • Yuan, Y., Xu, Q., Agaz, W., Janelle, D., Wang, C., Donglasa, J., Burgan, S., Graham, Z., Derek, W., Monica, U., & Qu, A. Differentially Expressed Heterogeneous Overdispersion Genes Testing for Count Data.

    • Teaching

    STAT 200: Statistical Analysis, Instructor

    University of Illinois at Urbana-Champaign
    Spring, 2019

    STAT 425: Applied Regression and Design, Teaching Assistant

    University of Illinois at Urbana-Champaign
    Fall, 2017

    STAT 578: Statistical Learning in Data Science, Teaching Assistant

    University of Illinois at Urbana-Champaign
    Spring, 2018

    STAT 414: Introduction to Probability, Instructor

    Penn State University
    Fall, 2022