About

I am a Ph.D. candidate in Electrical and Computer Engineering at the University of California, Santa Barbara, advised by Prof. Mahnoosh Alizadeh. My research focuses on safe learning and control with energy systems applications. This includes work on online optimization, bandit learning and adaptive control, as well as applications to pricing design in the electric grid.

I am also grateful to have done an internship at Mitsubishi Electric Research Laboratories (MERL) in summer 2025, where I worked on stochastic model predictive control with deep forecasting models for energy systems.

My publications are listed here and my CV is here.

Selected Papers

• S. Hutchinson, N. Jiang, and M. Alizadeh, “Rate-Optimal Regret for the Safe Learning-based Control of the Constrained Linear Quadratic Regulator,” arXiv, 2026, [paper] [slides]
• S. Hutchinson and M. Alizadeh, “Constrained Online Convex Optimization with Polyak Feasibility Steps,” International Conference on Machine Learning (ICML), 2025. [paper] [poster] [video]
• S. Hutchinson, B. Turan, and M. Alizadeh, “Directional Optimism for Safe Linear Bandits,” International Conference on Artificial Intelligence and Statistics (AISTATS), 2024. [paper] [poster]