Welcome to Mobility Systems Control (MSC) Laboratory

Our lab is methodology-first and grounded in applied control: we emphasize methods that can be implemented, executed, and empirically evaluated under real operating constraints. Our primary application domain is automotive and transportation systems, spanning vehicle motion and powertrain control through traffic level optimization. Data driven and machine learning techniques are used as tools within that control framework, mainly for prediction and for handling uncertainty. Designs are evaluated through multi-resolution modeling, simulation, and hardware-in-the-loop (HIL) experiments.
Research Interests:

Real-time optimal control

Automated and connected mobility

Modeling and prediction of vehicle and traffic systems

Simulation and evaluation using hardware-in-the-loop (HIL) and digital twins