DYNAMICS AND DECISION MAKING LAB AT THE UNIVERSITY OF PITTSBURGH
We work on problems in dynamics, control, and machine learning for cyber-physical systems. Our theoretical core and skills include intelligent and learning-based mechatronics, nonlinear dynamics, machine learning, and control systems design.
Our current application areas: MEMS sensor and actuator development for difficult environments, such as those with compromising acoustic interference (inertial sensors) or extreme temperatures (for nuclear application). We also look at fundamental problems in nonlinear systems and control as they pertain to resonant sensors, networks of nonlinear systems, and neurocomputing/neuromorphic computing.
Finally, we have been exploring using machine learning, nonlinear dynamics, and mechatronics approaches to improving cybersecurity for additive manufacturing process.
We focus on improving performance and providing resilient operation (with respect to both environmental factors and attack), as well as expanding the theories behind our methods.