Eshed Margalit, PhD
Computational Neuroscience and AI Researcher
I research brain-like artificial neural networks for vision, create online tools for scientists, and share educational resources for programming and statistics.
Research
I'm a computational neuroscientist working at the intersection of deep learning, primate visual neuroscience, human fMRI, and cognitive neuroscience. My thesis advisors were Profs. Dan Yamins and Kalanit Grill-Spector at Stanford University. My thesis focused on building deep neural network models that better match the function, structure, and development of visual cortex.
Topographic Deep Neural Networks
Learning topographic maps in deep convolutional neural networks
Submillimeter Imaging of Human Visual Cortex
Ultra-high-resolution fMRI of human visual cortex
CNNs for Face Classification
Understanding face recognition in deep neural networks
Object Familiarity in LOC
How are objects and scenes encoded in the lateral occipital complex?
Object Recognition in Modified Line Drawings
Psychophysical analysis of object recognition under distinct kinds of noise
Web Portfolio
I create online tools that make information easier to find, store, access, and share.
Educational Resources
These are some publicly available resources I’ve developed in various teaching roles. Please feel free to use and share them!
