current research tracks 01 - Geometry Studying submanifolds of stabilizing policies for constrained optimal control problems using the Riemannian geometry inherent to the structure of these problems. 02 - Inference Estimating latent variables in dynamical systems is a fundamental challenge in data-driven decision-making, particularly when noise characteristics are unknown. 03 - Risk A novel approach to long-term risk-sensitive control in stochastic systems through the so-called ergodic-risk criteria 04 - Multi-agent Large-scale distributed policy learning for networked systems utlizing algebraic structures and game theory 05 - Stabilization A geoemtric approach to fundamental characterization of system-theoretic limitations in online learning and control
