I am interested in how brains control movement, and how these principles can be used to control robots. Through this process I build robots which help biologists to ask questions that would be impossible to ask on non-synthetic animals. The real payoff of understanding biological movement and sensing lies not in just the morphology of animals, but in the ways they collect, represent, and use information.

My lab is working on technology to improve prosthetic limbs. We are building smarter control methods, sensory feedback systems, and more! I am a research scientist with the VA Center for Limb Loss and MoBility , one of the biggest amputation and prosthetic limb research organizations in the world. We work closely with University of Washington, where I am an affiliate assistant professor of mechanical engineering.

I was a Postdoctoral Researcher in the Daniel lab at the University of Washington. I worked with inertial maneuvering in robotic and insect flight, model-predictive reinforcement learning, and multimodal sensing and control, as in prosthetic sensory replacement and gesture-based computer interface. Check out manduca sexta , the coolest moth in the world.

I did my doctoral work in the Neurobotics Lab with Yoky Matsuoka. I was able to really push the boundaries of autonomous control of the ACT Hand, a biomechanically accurate tendon-driven robot hand. The idea is to combine concepts from neuroscience and biomechanics with classic control theory and machine learning. Through this process we developed theoretical tools for understanding how neural systems tackle the "Curse of Dimensionality" and the "Problem of Model Mismatch."

Before graduate school I worked with an Enercorp venture wind farm in Morocco and engineering SONAR and detection software for the U.S. Navy carrier fleet in " torpedo town " - keyport, WA. At Rice University I helped develop Connexions online educational content system, and an educational web game (reconstructors.rice.edu). I created a variety of projects involving signal processing and machine vision.