I'm an incoming Assistant Professor (January 2023) in the Brain and Cognitive Sciences & Neuroscience Departments at the University of Rochester. Previously, I was a Postdoctoral Fellow at the Princeton Neuroscience Institute, working with Jon Cohen, Ken Norman, and Nick Turk-Browne. I earned my Ph.D. in Computer Science from the Vision Lab at Stanford University, co-advised by Fei-Fei Li and Diane Beck. My academic journey started at Williams College with a B.A. in Computer Science, Mathematics, and Cognitive Science.
I'm a computational cognitive neuroscientist studying the elusive link between how the human brain learns & organizes conceptual information into categories, stories, and events, and how we use that information to understand & interact with our complex, noisy world.
05/2022. Presenting a Talk at the Vision Sciences Society (VSS) 2022 Annual Meeting: Sculpting New Visual Concepts into the Human Brain.
02/2022. New Publication in Cognitive Science: Context Matters: Recovering Human Semantic Structure from Machine-Learning Analysis of Large-Scale Text Corpora.
We show that incorporating semantic context into the training procedure of word embedding models improves prediction of empirical similarity judgments and feature ratings.
11/2021. Presenting a Poster at the Society for Neuroscience (SfN) 2021 Annual Meeting: Sculpting New Visual Concepts into the Human Brain.
05/2021. Presenting a Poster at the Vision Sciences Society (VSS) 2021 Annual Meeting: Context Matters: Recovering Human Visual and Semantic Structure from Machine-Learning Analysis of Large-Scale Text Corpora.
10/2020. New Preprint on bioRXiv: Sculpting New Visual Concepts into the Human Brain.
We decribe a new way to provide humans with visual and conceptual knowledge by directly sculpting activity patterns in their brains using fMRI, real-time neurofeedback, and machine learning!
10/2020. Presenting a Talk at the NeuroMatch 3.0 Conference: Creating Visual Categories Using Closed-Loop Real-Time fMRI Neurofeedback.
06/2020. Our team was awarded a Research Grant from the GRAMMY Museum Foundation to investigate the neural hierarchy of audio-motor integration during natural music performance.
Co-PI, $19,758 (33% share). PI: Elise Piazza, Princeton University, co-PI: Uri Hasson, Princeton University.