Shreya Saxena is broadly interested in the neural control of coordinated, complex movements. She did her Masters’ in the Department of Biomedical Engineering at Johns Hopkins University, working with Sridevi V. Sarma, looking at the role of the basal ganglia in health and Parkinson’s Disease, as well as the effects of Deep Brain Stimulation on these neurons. She then did her PhD in Electrical Engineering at the Massachusetts Institute of Technology with Munther Dahleh, studying the closed-loop control of fast movements from a control theory standpoint. She is currently a Swiss National Science Foundation postdoctoral research fellow at the Center for Theoretical Neuroscience at the Zuckerman Mind Brain Behavior Institute at Columbia University, working with Liam Paninski, John Cunningham, and Mark Churchland. Her work is on the interface between machine learning, data science and neuroscience. She is currently exploring how global cortical activity leads to a variety of task-related as well as spontaneous movements, and investigating how population activity in the motor cortex flexibly controls movements at different speeds.
I am a control theorist broadly interested in understanding how neural activity leads to complex motor behavior. How do populations of neurons coordinate their activity to carry out skilled and spontaneous movements? Recent technological advances allow us to simultaneously record from large populations of neurons. Concurrently, new developments in machine learning have enabled very efficient ways of representing this data. I am interested in (a) fundamental research addressing the reach and limitations of the sensorimotor control system, and (b) developing computational techniques with experimental collaborators to better understand the neural control of movement.