Hi! I am a PhD student at MIT EECS, advised by Prof. Aleksander Mądry.
I work on machine learning, focusing on problems related to robustness.
I received a BS in Computer Science from Cornell University in 2014, where I was fortunate to work with Prof. Ramin Zabih and Prof. Bobby Kleinberg.
Previously at MIT, I worked on understanding statistical-computational tradeoffs in high-dimensional statistics with Prof. Guy Bresler for my SM thesis.
In the past, I have interned at Waymo, Dropbox, and Google.
On Distinctive Properties of Universal Perturbations
Sung Min Park, Kuo-An Wei, Kai Xiao, Jerry Li, Aleksander Mądry
On the Equivalence of Sparse Statistical Problems
Sung Min Park
SM thesis 2016
Structured learning of sum-of-submodular higher order energy functions
Alexander Fix, Thorsten Joachims, Sung Min Park, Ramin Zabih
Fourier Theoretic Probabilistic Inference over Permutations
Cornell, Spring 2014
Analysis of pipage method for k-max coverage
Cornell, Fall 2012
Fast Forward Computer Vision (FFCV)
I grew up in Seoul and Singapore, where I attended SAS.
From 2016-18, I served in the Republic of Korea Army.