Scholar
Liviu Aolaritei
Google Scholar ID: 2SdmamoAAAAJ
UC Berkeley
Citations & Impact
Citations
208
H-index
8
i10-index
8
Publications
16
Co-authors
9
list available
Contact
No contact links provided.
Publications
Resume (English only)
Academic Achievements
- Paper 'Wasserstein Distributionally Robust Estimation in High Dimensions: Performance Analysis and Optimal Hyperparameter Tuning' accepted by Mathematical Programming (2025), with S. Shafiee and F. Dörfler.
- Paper 'Nash Equilibria, Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization' accepted by Operations Research (2025), with S. Shafiee, F. Dörfler, and D. Kuhn.
- Paper 'Distributional Uncertainty Propagation via Optimal Transport' accepted by IEEE Transactions on Automatic Control (2025), with N. Lanzetti, H. Chen, and F. Dörfler.
- Paper 'Revisiting mean estimation over ℓp balls: Is the MLE optimal?' under review at The Annals of Statistics (2025), with M.I. Jordan, R. Pathak, and A. Ulichney.
- Paper 'Minimum Volume Conformal Sets for Multivariate Regression' under major revision at Journal of the American Statistical Association (Theory and Methods) (2025), with S. Braun, M.I. Jordan, and F. Bach.
- Paper 'Hedging Against Black Swans in Day-Ahead Energy Markets' under review at Power Systems Computation Conference (PSCC) (2025), with B. Bangoura, S. Bolognani, N. Lanzetti, and F. Dörfler.
Background
- Currently a postdoctoral researcher in the Department of Electrical Engineering and Computer Science at UC Berkeley, hosted by Michael I. Jordan.
- Research lies at the intersection of optimization, statistics, and computation, addressing optimal decision-making under uncertainty.
- Focuses on complex forms of uncertainty such as distribution shifts, rare events (black swans), and graph-structured correlations.
- Theoretical work is inspired by fundamental engineering challenges in machine learning, power systems, energy markets, and transportation, where uncertainty critically affects decision-making and system resilience.
- PhD work primarily focused on the foundations of distributionally robust optimization with applications in high-dimensional estimation, automatic control, and energy markets.
- Earlier PhD research addressed stability and robustness of nonlinear systems, applied to renewable-integrated power systems.
