Research in our group is focused on the following areas:

1. Control of cyber-physical systems

   • We develop control techniques using theoretical tools, simulation-based numerical experiments, machine learning techniques for complex cyber-physical systems operating in uncertain and unknown environments.

   • Current research is focused on developing learning autopilot for aircraft and multicopters that can learn using measured data in real-time, expands the operational envelope, and reduce failure in the event of sudden dynamic changes in the environment.

   • Applications include Autonomous vehicles, industrial robots, and autopilots.

2. Learning in Complex systems

   • We develop computationally efficient, data-driven, learning-based techniques for estimating states and parameters of complex dynamic systems such as atmospheric and flow models.

   • Current research is focused on developing computationally inexpensive methods that will improve prediction accuracy and enable the implementation of complex control systems in real-time to improve system performance.