Machine Learning and Computer Vision: Deep Learning | Statistical Physics | Stochastic Processes | Reinforcement Learning | Partial Differential Equations | Distributed Algorithms;Robotics and Control: Urban Autonomous Navigation | Formal Verification | Motion PlanningI am interested in the areas of machine learning, robotics and computer vision. My ambition is to bring the dream of cybernetics closer to reality, towards Embodied Intelligence. The ability to perceive and control the environment is the hallmark of such intelligence and their interplay is the core of my research. In a nutshell, I would like to build embodied autonomous agents that are intelligent not just in the sense of a chess-playing program but also intelligent in the sense of a dog. This research is highly multi-disciplinary: it draws from optimization, statistical physics, partial differential equations and stochastic processes, as also, stochastic control, motion planning and formal verification methods. It involves both experimental and theoretical work; pushing the envelope of science and achieving broad societal impact requires both. I focus on applications in home robotics, personal healthcare and autonomous driving.See more information at http:/www.pratikac.info