Conlain Kelly
Ph.D. Student

Research Areas:
Statistical Continuum Mechanics; Materials Informatics; Generative AI; Scientific Machine Learning


Advisor: Surya Kalidindi

Conlain completed their undergraduate studies at the University of Wisconsin — Madison, pursuing a double major in Applied Math, Engineering, & Physics and Computer Science. They are currently a Ph.D. candidate in Computational Science and Engineering at Georgia Tech. Their research focuses on hybrid physics-centric data-driven models for statistical continuum mechanics and materials design. More broadly, they are interested in the intersection of deep learning and traditional numerical methods, as well as decision-making under uncertainty.