My research essentially revolves around the field of numerical optimization and its applications, particularly in complex systems and data science.
My current work aims at developing efficient nonconvex optimization algorithms, with
a focus on incorporating randomness (typically within linear algebra techniques), and establishing complexity guarantees for those frameworks.
I am also highly interested in derivative-free optimization and its applications to solving simulation-based problems.