I'm a research scientist at NAVER Clova AI Research (CLAIR), working on machine learning and its applications. Prior to working at NAVER, I worked as a research engineer at advanced recommendation team (ART) in Kakao from 2016 to 2018.
I received a master's degree in Electrical Engineering from Korea Advanced Institute of Science and Technology (KAIST) in 2016. During the master's degree, I researched on a scalable algorithm for robust subspace clustering. Before my master's study, I worked at IUM-SOCIUS in 2012 as a software engineering internship. I also did a research internship at Networked and Distributed Computing System Lab in KAIST and NAVER Labs during summer 2013 and fall 2015, respectively.
My research goal is to understand unexpected and less interpretable behaviors of machine learning (ML) models and to solve the problems in both practical and provable manners. In particular, I believe that it is important to solve four main research topics: (i) Understanding machine learning models by explainable ML, (ii) Building generalizable models to different biases, corruptions, or domains, (iii) Developing probabilistic machines with well-calibrated uncertainty measurement, (iv) Overcoming insufficient labeled data points by learning with minimal human supervision.
(C: peer-reviewed conference, W: peer-reviewed workshop, A: arxiv preprint, O: others)
(∗authors contributed equally)
See also at my Google Scholar.
Distributed at 2019 Hangul's day (한글날), [Full font list]
Deployed in Jan. 2019
Feb. 2016 - Feb. 2018
Deployed in 2017
Deployed in 2017
Aug. 2015 - Dec. 2015
Jun. 2012 - Jan. 2013