I am currently an assistant professor in the Department of Mathematical Sciences at the Korea Advanced Institute of Science and Technology (KAIST). Previously, I was a ML scientist at AWS AI Labs. Before that, I was a Neyman Visiting Assistant Professor in the Department of Statistics at UC Berkeley, where I was very fortunate to be supervised by Bin Yu. Prior to that, I was a Postdoctoral fellow at UC Berkeley’s Foundations of Data Analysis (FODA) Institute and Berkeley Institute for Data Science (BIDS). I obtained my PhD in Statistics at the University of Chicago where I was very fortunate to be advised by Rina Foygel Barber.
My research is centered on high-dimensional statistics and machine learning, with a focus on sparse and low rank optimization, local graph clustering, interpretable machine learning, and statistical learning under distribution shifts. I am also interested in the applications of statistical and optimization methods to diverse scientific areas such as medical imaging, population genetics, and cosmology.
Openings
- [Postdoc] We are hiring Postdoctoral Researchers to join the “Glocal Lab” project at KAIST MFRS, focusing on AI-driven drug discovery and biohealth innovation. If you are interested in applying statistics, machine learning, data science to real-world biohealth problems, check out the details and apply!
Education
The University of Chicago
Seoul National University
- M.S., Statistics, 2013 (Advisor: Byeong U. Park)
- B.S., Statistics, B.A., Economics, Minor in Mathematics, 2011
Email: haywse@kaist.ac.kr
▸ For Prospective Students: If you are looking for a thesis topic or research opportunity, check out my Google Scholar or GitHub repo to see if any of the topics might be a good fit. My current interests include statistical learning under distribution shifts (such as domain adaptation and out-of-distribution generalization), graph neural networks, and applications with generative models.
▸ If you are interested in joining the newly launched “Glocal Lab” project—a joint initiative between KAIST Mathematical Sciences and the Colleges of Pharmacy at Chungnam National University and Seoul National University—focusing on AI-driven drug discovery and biohealth innovation, please contact me. We welcome undergraduate and graduate students eager to apply statistics, machine learning, and data science to real-world biohealth problems.