My current research focuses on computational optimization models for processors capable of operating at multiple speeds. The goal is to minimize the average energy consumption of a system, assuming only a priori knowledge of the system's state—specifically, an estimate of the workload to be executed and the deadline for completing the task.

Unlike conventional approaches, the objective is not to complete tasks as quickly as possible, but rather to minimize average energy consumption. This paradigm shift fundamentally alters the study of these systems. In particular, traditional tools like index-based policies prove ineffective for analyzing optimal policies.

More broadly, I am interested in related fields such as stochastic optimization, Markov decision processes, queueing systems, and probability theory in general.