Yifan Sun

Yifan Sun
Yifan Sun
Assistant Professor

Department of Computer Science
Room TBA
Stony Brook, NY 11794-2424

ysun [at] cs.stonybrook.edu


Convex and nonconvex optimization for machine learning and scientific computing


Yifan Sun received her PhD in Electrical Engineering from UCLA in 2015, with research focusing on convex optimization and semidefinite programming. She then worked at Technicolor Research and Innovation, focusing on machine learning and data science applications. More recently, she was a postdoctorate researcher at the University of British Columbia in Vancouver, Canada and L’Institut National de Recherche en Informatique et Automatique (INRIA) in Paris, France.


Yifan Sun’s research focuses on large-scale optimization algorithms that arise in machine learning and scientific computing applications. This domain often includes problems that are often nonsmooth and nonconvex, in the context of heavy computation and memory requirements that must be curtailed through sampling and distribution. The research has three main themes: leveraging foundational concepts to provide intuition across applications and heuristics, developing and improving algorithms to adapt to modern day needs and resources, and giving theoretical guarantees on best- and worst-case behavior for the resulting methods.

Teaching Summary

CSE 512 (Fall 2020)