Our research centers around the physics and engineering of human behavior, neural activity, and psychological patterns, aiming to unravel the mysteries of psychiatric disorders. The inherent challenge is to observe a minor fraction of the trajectory of the select measurable variables (e.g., an emotional state) and extrapolate inferences about the entire trajectory of all pertinent state variables. Leveraging cutting-edge techniques from complexity science, network control theory, machine learning, and artificial intelligence, we strive to quantify, predict, and control these dynamics. Our computational models are informed by rich datasets, ranging from mind-wandering experiments to neuroimaging. In the same direction, we are innovating machine learning to better model complex systems, exploring control strategies for the human brain, applying our findings to neuropsychiatric care, delving into memory processes that shape spontaneous thoughts.

Key areas of research: Physics of Behavior, Machine Learning, Neuroscience, Statistical Physics of Complex Systems, Network Control Theory