My research study lies at the intersection of two exciting fields: control theory and machine learning. More specifically, I use control theory to properly define dynamics of robots, and leverage on machine learning to endow them with the ability to perform a wide variety of tasks in complex unstructured environments. Guaranteed stability, adaptivity, reactivity, robustness, and compliancy are the five features that I always seek in my research.

My research interest includes:
- Whole-Body Robot Control under Uncertainty
- Realtime Adaptive Motion Generation
- Compliant Control
- Variable Impedance control
- Robot Learning
- Imitation Learning
- Bi-Manual Haptic Teleoperation
- Dynamical Systems
- Movement Primitives