I’m working on a variety of topics, loosely collected under the heading of finding or creating useful structure in neural representations
And growing out of my earlier work on Bayesian inference in the brain, a separate line of my recent work asks
My undergrad was at Dartmouth College, where I mostly did Computer Science and Engineering, but sparked an interest in the connection between AI and neuroscience. This led me in 2014 to a PhD program in Computer Science at the University of Rochester, where I quickly discovered that making “brain inspired AI” means first understanding “brains.” I transferred to the Brain and Cognitive Science department in 2015, where I did my main PhD work on Bayesian Inference in low-level visual perception, graduating in fall 2020.
By the end of my PhD, I saw some serious flaws in the Bayesian framework as a tool for understanding (and building) neural computation. This has led down three paths in my postdoc work: