Yuxin Ma

Hi! I am a PhD student at the Department of Applied Mathematics and Statistics at Johns Hopkins University, where I am fortunate to be advised by Professor Soledad Villar. My research interests lie at the intersection of mathematics and deep learning. I am exploring how to incorporate mathematical ideas into the design of new deep learning algorithms, while also investigating how deep learning can aid in solving challenging mathematical problems. Currently, my focus is on Graph Neural Networks and Equivariant Neural Networks.

Previously, I completed an MMath and BA Hons degree in Mathematics at the University of Cambridge where I was mentored by Professor Benedikt Löwe. During my master’s studies, I focused on Statistics and completed an essay on Topological Data Analysis, advised by Professor Sir John Aston and Professor Jacob Rasmussen.

While this website is currently very empty, I am planning to gradually build it up during my PhD years. Stay tuned!