Data Science Institute

My research advances along two fronts: understanding neural processing during active sensing, and developing new neural engineering for neurostimulation and control. The approach combines basic scientific investigation in animals engaged in sensory tasks, with engineering approaches including closed-loop intervention. Tools include electrophysiological, behavioral, optogenetic, and theoretical methods applied to the rodent whisker system, a highly refined tactile sensory system. Augmenting experiments with real-time neural feedback forms a powerful paradigm uniting study of brain machine interfaces, with an emphasis on sensory neural prosthetics, and the active sensing loop. By tackling these fundamental questions in sensory systems neuroscience, my lab seeks new approaches to neurocontrol problems with biomedical relevance, including restoration of damaged systems through stimulating neuroprosthetics.

How does your research, teaching, or other work relate to data or computational science?

In addition to my own research on inference of dynamical systems models from neuroscience data, as part of my position in the Carney Institute I work collaboratively with any institute affiliated scientists on quantitative aspects of their research, including questions about analysis methods, high performance computing, data management, and research design.