• MS in Computer Science, 2020

    University of Colorado, Boulder

  • BS in Computer Science, 2018

    University of Colorado, Boulder

Project Lead

Rather than predicting perceptual distortions, one needs to solve the inverse problem: What is the best stimulus to generate a desired visual percept?

Understanding the visual system in health and disease is a key issue for neuroscience and neuroengineering applications such as visual prostheses.


We systematically incorporated neuroscience-derived architectural components into CNNs to identify a set of mechanisms and architectures that comprehensively explain neural activity in V1.

We present explainable artificial intelligence (XAI) models fit on a large longitudinal dataset that can predict perceptual thresholds on individual Argus II electrodes over time.