Control, Robotics, and Dynamical Systems  

This broad subject-area is supported by a strong faculty for theoretical studies in Intelligent Control, Adaptation and Learning, and Physical Modeling, as well as linking such studies to advances in related areas of Communications, Computing, Information Theory, and Signal Processing. Mathematical abstraction and data-driven approaches are investigated to address fundamental problems pertinent to creating resilient technological systems such as smart electric grids, cooperating robots, human-equivalent learning programs, secure autonomous mobility etc. The work incorporates multi-disciplinary scientific threads, from mathematics and physics to neuroscience and biological inspiration for technological realizations. 

Faculty in this area of research include: