Cyberphysical and Control Learning Systems
Cyber-physical systems (CPS) are engineering systems of tightly connected cyber- and physical components, including sensing, computation, control, networking, physical dynamics and the operating environment. Model-based optimization and control and data-driven learning solutions such as reinforcement learning produce intelligent decisions for CPS. CPS transform the way to approach engineering systems and have found broad applications that include but not limited to autonomy, robotics, intelligent transportation systems, smart grids, smart home/health/community, infrastructure health monitoring, and smart disaster response.
Dr. Frank L. Lewis. Feedback control systems (nonlinear process, adaptive, optimal, intelligent, and robust), cooperative multi-agent systems, robotics.
Dr. Yan Wan(Dynamic Networks and Control). Decentralized control; large-scale dynamical networks; stochastic networks; uncertainty quantification; learning control and graphical games; cyber-physical systems; air traffic management; UAV traffic management; sensor/robot/UAV networking; autonomous driving
Dr. Ramtin Madani. Electrical power systems, microgrids, power conversion and control, energy storage.
Dr. Sungyong Jung. (Integrated Sensing Circuits and Systems). Sensing embedded systems, analog and mixed signal integrated circuit design, radio frequency integrated circuit design, VLSI system design, chemical and bio sensing.
Dr. Ioannis D. Schizas. Machine learning, statistical signal processing, data analytics, optimization.
Dr. Diana Huffaker
Professor and Chair
Dr. Jonathan Bredow
Professor & Associate Chair
Dr. Sungyong Jung
Associate Professor & Associate Chair