me

Youngtak Sohn

Division of Applied Mathematics, Brown University
youngtak dot sohn at brown dot edu

I am an Assistant Professor in the Division of Applied Mathematics at Brown University. I work in probability theory and its interactions with mathematical statistics, theoretical computer science, and statistical physics. My current research interests includes high-dimensional statistics, random constraint satisfaction problems, statistical inference on random graphs, and spin glass theory. Here is my CV and Google Scholar page.

Previously, I was a postdoctoral researcher in the Mathematics Department at MIT, where I worked with Elchanan Mossel and Nike Sun as a member of NSF/Simons program Collaborations on Theoretical Foundations of Deep Learning . I received my PhD in Statistics advised by Amir Dembo from Stanford University. I received my BSc from Seoul National University.

Publications and preprints

Recorded talks

  • "Exact phase transitions for stochastic block models and reconstruction on trees" (20 mins) [Youtube]
    Symposium on Theory of Computing (STOC), Jun 2023
  • "Local geometry of NAE-SAT solutions in the condensation regime" (50 mins) [Youtube]
    UT Austin, Graduate Mini-School in Groups, Dynamics, and Probability, May 2023
  • "One-step replica symmetry breaking of random regular NAE-SAT" (20 mins) [Youtube]
    Foundations of Computer Science (FOCS), Feb 2021

    Teaching