His research focuses on development of new data-driven learning and inference algorithms for autonomous perception and decision-making in complex cyber-physical systems with emphasis on health monitoring, decision frameworks, multi-agent systems, cyber-physical security and human-machine interaction for a large variety of application areas including building energy systems, plant science and agriculture, design and manufacturing and transportation systems. The nature of his research is inherently multi-disciplinary involving machine learning, information theory, theory of computation, dynamical systems, topology and statistical mechanics.