Atlas Kazemian


I’m a cognitive science researcher interested in understanding how brains and machines encode and process information. Humans possess the ability to seamlessly make sense of auditory and visual data, despite the noisy and ambiguous nature of the world. We also represent this information in a way that enables efficient learning and generalization in new situations. My passion lies in understanding these abilities, and developing AI that can more closely emulate them.

Currently, I am a research assistant at the Department of Cognitive Science at Johns Hopkins University, where I’m working with my advisor Dr. Michael Bonner to reverse engineer the representations and algorithms of human visual cognition through computational modeling. In Fall 2024, I will be starting my PhD at Stanford, where I will be co-advised by Dr. Laura Gwilliams and Dr. Dan Yamins.

Prior to this, I received my bachelor’s degree in Integrated Engineering from the University of British Columbia.

Here is my CV!


[Apr 2024]     I am honored to be named a Stanford School of Humanities and Sciences Dean’s Scholar!
[Apr 2024]     I’m honored to have been awarded the Stanford EDGE Fellowship in support of my graduate studies and research!
[Apr 2024]     I will be starting my PhD in the Fall at Stanford University co-advised by Laura Gwilliams and Dan Yamins.
[Aug 2023]     Our lab will be leading a tutorial session on a high dimensional view of computational neuroscience at CCN 2023. Check out our tutorial website!
[Aug 2023]     I will be presenting my research on learning-free high dimensional models of visual cortex as a poster presentation at CCN 2023.