Shihao Wu 吴世豪

About Me

Hi! I am a fifth-year PhD student in Statistics at the University of Michigan, jointly supervised by Professor Ji Zhu and Professor Gongjun Xu. Prior to that, I received my Bachelor's degree in Data Science from Fudan University in 2021. 

I am interested in and working on statistical problems that emerge from the need to analyze large-scale, complex-structured datasets. My research topics include (hyper)graph network analysis, latent space models, generative modeling for structured data, and high-dimensional statistics. 

I am on the job market for 2025-2026.

Selected Awards and Honors

• 2025-2026 Rackham Predoctoral Fellowship, Rackham Graduate School, University of Michigan

• 2024 AERA Outstanding Reviewer Award, American Educational Research Association

• 2024-2025 Rackham International Student Fellowship, Rackham Graduate School, University of Michigan

• 2024 IMS ICSDS Student Travel Award, Institute of Mathematical Statistics

• 2024 IMPS Graduate Research Competition Award, Psychometric Society
  "Expanding the Scope of Data Sources in Psychometric Research by Embedding Individual Records using Generative AI" with Chengyu Cui, Bo Meng, Jing Ouyang, and Zhiwei Xu. Selected as top 3 teams to present at IMPS 2024 and ranked top 1 after the presentation. Team Lead: Shihao Wu; Presenter: Jing Ouyang

• 2024 IMS Hannan Graduate Student Travel Award, Institute of Mathematical Statistics

• 2024 Student Paper Award, Statistical Learning and Data Science Section, American Statistical Association
  ''A general latent embedding approach for modeling high-dimensional hyperlinks'' with Gongjun Xu and Ji Zhu

• 2022 Best Poster Presentation Award, UMichSML
  ''Supervised homogeneity fusion: a combinatorial approach'' with Wen Wang, Ziwei Zhu, Ling Zhou, and Peter X.K. Song

• 2021-2022 Outstanding First Year Ph.D. Student, Department of Statistics, University of Michigan