I am a fourth year PhD student in a joint program between Brain and Cognitive Science and Computer Science. My research focuses on furthering probabilistic inference as a framework to understand perception, from optimality considerations of a "sampling algorithm" in the brain to analysis of electrophysiological recordings from visual cortex (see my CV).
I am primarily interested in what neurons "compute" or "represent" about the outside world, and how these representations are acquired. My medium-term research plan is to simultaneously work to understand deep neural networks - with many potential applications to machine learning - and the algorithms used for probabilistic inference in the brain. The idea that the brain could do Bayesian inference has been around for a while. The big question now is: how?
As more of a hobby, I am also very interested in philosophy of mind, both as a philosophical question and as a moral/ethical with respect to AI.
<first initial><last name>@ur.rochester.edu
I began my PhD in 2014 after spending a year working as the "Engineer in Residence" at The Harley School. I started in computer science to do research in brain-inspired AI, but over 2 years I became enough inspired by the brain that I transferred into the Brain and Cognitive Sciences program to work with Ralf Haefner on some of the big questions in neuroscience directly.
Dartmouth College is my undergraduate alma mater. I graduated in 2013 with the long-winded degree of Computer Science modified with Engineering, and a minor in Asian and Middle Eastern Language and Literature. Translation: a mixture of mostly CS with some EE, and a minor in Japanese.