Applied Mathematics

Youngtak Sohn works in probability theory with an emphasis on its interactions with mathematical statistics, theoretical computer science, and statistical physics. His interests include spin glass theory, random constraint satisfaction problems, analysis of stochastic networks, and mathematical foundations of deep learning. He completed BSc in mathematics from Seoul National University in 2016 and PhD in statistics from Stanford University in 2021. He held a postdoctoral position at MIT Mathematics, and joined the faculty of the Division of Applied Mathematics at Brown University in July 2024.