I am an assistant professor in the Department of Computer Science at RIT, with additional appointments in the Cognitive Science PhD Program and the Center for Vision Science.

I want to understand how the brain works and use that understanding to create more capable machine learning and AI systems. My interests have bounced back and forth over the years between computer science, neuroscience, AI, machine learning, and philosophy of mind.

Here's a bit about how I got where I am now:

• 2013: BA in Computer Science and Engineering at Dartmouth College. Near the end of undergrad I became deeply interested in the idea of building intelligent systems inspired by how the brain works.

• 2014–2015: Started a PhD in Computer Science at the University of Rochester. Eventually realized that building "brain inspired" AI means we first need to understand brains.

• 2015–2020: PhD in Brain and Cognitive Science at the University of Rochester in the lab of Ralf Haefner. Studied visual perception theory through the lens of Bayesian inference. Designed experiments with human psychophysics and monkey electrophysiology to probe the role of prior expectations in visual perception.

• 2020–2023: Postdoc at the University of Pennsylvania in Konrad Kording's lab. Studied deep neural networks and structure in the kinds of internal representations they develop.

• 2023: Joined RIT as an Assistant Professor.