Postdoctoral Researcher
I work at the intersection of computational neuroscience, human perception, and machine learning — studying how neural networks relate to the human visual system, and applying these insights to image quality, segmentation, and perceptual modeling.
Modeling perception with biologically-inspired neural architectures, including divisive normalization.
Perceptual image quality metrics and deep feature analysis for human-aligned quality assessment.
Artificial psychophysics to probe the perceptual properties of deep networks.
Measuring how well vision-language models like CLIP align with human perceptual representations.