Going beyond human-level dynamic motion control
Seeking to advance how humans and robots learn to guide the physical interactive behavior of one another
Studying computational systems that solve sensory and motor problems
Focusing on optimizing human performance interaction through mechatronic design and control
Developing algorithms to safely solve problems that robots and other learners encounter in real-world interactive settings.
Conducting foundational artificial intelligence (AI) research, with emphases on AI safety and reinforcement learning (RL), and particularly the intersection of these two areas.
Harnessing innovations from Nursing and Engineering to promote change in health and healthcare delivery
Using experimental, theoretical and numerical tools to understand different Fluid-Structure Interaction phenomena
Using a comprehensive approach to study human locomotion, integrating neurophysiology, biomechanics and energetics.