Yilun Kuang

Yilun Kuang is a Ph.D. student in data science at NYU’s Center for Data Science, where he is advised by Andrew Gordon Wilson. He is currently a fourth-year undergraduate in honors mathematics and computer science at NYU. He is a research assistant at the Center for Computational Neuroscience, working with SueYeon Chung and Eero Simoncelli on manifold geometry/efficient coding inspired self-supervised learning.

His research interests lie in probabilistic generative modeling, Bayesian deep learning, self-supervised representation learning, NeuroAI and AI for science, Gaussian process and neural tangent kernel, and representational geometry.