Yuxin Ma

Hi! I am a second year PhD student at the Department of Applied Mathematics and Statistics at Johns Hopkins University, where I am fortunate to be advised by Soledad Villar and Tim Kunisky. My research interests lie at the intersection of mathematics and deep learning. I aim to develop a better understanding of neural networks using a variety of mathematical tools, while also investigate how deep learning can aid in solving challenging mathematical problems. Check out the about me page to learn more!

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