Anna successfully passes her candidacy exam

Anna’s research lies at the intersection of game theory, machine learning, and engineering design. She develops Bayesian optimization and multi-fidelity surrogate modeling techniques for computationally expensive engineering problems, with a particular focus on systems involving multiple interacting decision-makers.

Her work investigates how equilibrium solutions can be efficiently identified in constrained black-box systems and how strategic interactions influence overall system performance. By combining machine learning methods with game-theoretic analysis, she aims to develop scalable approaches for the design of complex engineering systems.

We warmly congratulate Anna on this important milestone and wish her continued success in her research.