Welcome to Yuetian's homepage!.
Here is a copy of CV. You can also find me on Google Scholar.
Research Interest
I am broadly interested in methodology, theory and computation of high dimensional statistical problems. Specifically, currently I am interested in:
- High dimensional statistical inference
- Distribution-free inference
- Robust statistics
- Tensor learning
- Computational complexity of statistical inference
Selected Recent Works
Robustness and Stability in Statistical Inference.
- Ilias Diakonicolas*, Chao Gao*, Daniel Kane*, Yuetian Luo*"Adaptive Robust Confidence Sets in High Dimensions", 2026.
- Abhinav Chakraborty*, Yuetian Luo*, Rina Foygel Barber, "Stability and Accuracy Trade-offs in Statistical Estimation", 2026.
- Minjun Cho, Yuetian Luo, Chao Gao, "Robust Confidence Intervals for a Binomial Proportion: Local Optimality and Adaptivity", 2025.
- Yuetian Luo, Chao Gao, "Adaptive Robust Confidence Intervals", Annals of Statistics, 2026.
- Yuetian Luo, Rina Foygel Barber, "Is Algorithmic Stability Testable? A Unified Framework under Computational Constraints", 2024.
Distribution-free Inference.
Statistical-computational Trade-offs.
Tensor Learning/Non-convex Optimization.
- Yuetian Luo, Nicolás García Trillos, "Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective
", Mathematical Programming, Series A, 2026
- Yuetian Luo, Anru Zhang, "Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay ", Annals of Statistics, 2024. [Code]
- Yuetian Luo, Anru Zhang, "Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence ", Journal of Machine Learning Research, 2023. [Code]
Contact Information
Department of Statistics
Rutgers University