Research
Research Interests
- Statistical Network Analysis
- High-dimensional Statistics
- Spectral Methods
- Mathematical Data Science
- Nonparametric Statistics
- Nonconvex Optimization
Prospective PhD students, please read this.
Representative Papers
- A High-Dimensional Statistical Theory for Convex and Nonconvex Matrix Sensing
Joshua Agterberg and René Vidal, 2025.
[arXiv]. - Statistical Inference for Low-Rank Tensors: Heteroskedasticity, Subgaussianity, and Applications
Joshua Agterberg and Anru Zhang, 2025,
Annals of Statistics, Accepted.
[arXiv]. - Distributional Theory and Statistical Inference for Linear Functions of Eigenvectors with Small Eigengaps
Joshua Agterberg, 2023.
[arXiv]. - Joint Spectral Clustering in Multilayer Degree-Corrected Stochastic Blockmodels
Joshua Agterberg, Zachary Lubberts, and Jesús Arroyo,
Journal of the American Statistical Association, 2025.
[arXiv]. - Estimating Higher-Order Mixed Memberships via the $\ell_{2,\infty}$ Tensor Perturbation Bound
Joshua Agterberg and Anru Zhang,
Journal of the American Statistical Association, 2025.
[arXiv][Publisher Site].
Honors and Awards
- Summer 2022 Acheson J. Duncan for the Advancement of Research in Statistics Travel Award
- Spring 2022 MINDS Data Science Fellowship
- 2021-Present Applied Mathematics and Statistics Teaching Fellow
- Summer 2021 Best Presentation Award for JSM Student Competition in Nonparametric Statistics
- Spring 2021 IMS Hannan Graduate Student Travel Award
- Spring 2021 Finalist for JSM Student Competition in Nonparametric Statistics
- Spring 2021 MINDS Data Science Fellowship
- 2019-Present Charles and Catherine Counselman Fellowship
- 2020-2021 Applied Mathematics and Statistics Apprentice Teaching Fellow
- Spring 2020 MINDS Data Science Fellowship