(Learning) Visual Representations
Visual stimuli elicit action potentials in the retina, that propagate to the brain, where further action potentials are elicited. What is the nature of this visual representation? In other words, what is the correspondence between patterns of action potentials in the brain, and the stimuli that caused them? Moreover, how are these representations learned through experience? Finally (how) can we "upload" the brain's visual representations into computers, to make better artificial intelligence systems? These are the central themes of my research program.
In parallel with our core research program, described above, we work on applications of machine learning to make new medical technologies. One example is our work on adaptive deep brain stimulation (DBS) treatments for Parkinsonís disease patients.