Researcher on Responsible & Safe AI.
Love to learn new things.
Love to play the violin.
I am a Ph.D. candidate at the Data Intelligence Lab of KAIST EE. I am extremely fortunate to have been advised by Prof. Steven Euijong Whang during my PhD journey. I am also a recipient of the Microsoft Research PhD Fellowship 2022.
My main research area is Responsible & Safe AI, which includes fairness, robustness, interpretability, and transparency. I believe that these aspects will be indispensable in future machine learning systems. Among these aspects, I am especially interested in building fair and robust AI frameworks that do not have demographic disparities and generalize well in new data distributions. To this end, I currently focus on 1) lowering the barrier to fair AI development, 2) ensuring fairness amid data distribution shifts, and 3) improving model fairness and robustness in large-scale scenarios (e.g., using large foundation models).
I was a research intern at Google DeepMind in 2023 and NVIDIA Research in 2022, working with wonderful mentors.
I am in the industrial job market! Please feel free to contact me for any potential opportunities.
Responsible & Safe AI
Responsible AI Challenges in End-to-end Machine Learning [Paper]
S. E. Whang, K. Tae, Y. Roh, and G. Heo
IEEE Data Engineering Bulletin 2021
Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI Integration Approach [Paper]
K. Tae, Y. Roh, Y. Oh, H. Kim, and S. E. Whang
DEEM @ ACM SIGMOD 2019
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective [Paper]
S. E. Whang, Y. Roh, H. Song, and J. Lee
VLDB Journal 2023 (Early Access from 2022)
Inspector Gadget: A Data Programming-Based Labeling System for Industrial Images [Paper]
G. Heo, Y. Roh, S. Hwang, D. Lee, and S. E. Whang
A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective [Paper]
Y. Roh, G. Heo, and S. E. Whang
IEEE TKDE 2021 (Early Access from 2019)
Ph.D. (Integrated with Master) in Electrical Engineering, KAIST | Sept. 2019 - Feb. 2024 (Expected)
Master in Electrical Engineering, KAIST | Sept. 2018 - Aug. 2019
B.S. in Electrical Engineering & Minor in Intellectual Property, KAIST | Feb. 2014 - Aug. 2018 (Summa Cum Laude )
Korea Science Academy | Feb. 2011 - Feb. 2014
Microsoft Research PhD Fellowship | 2022
Best Research Achievement Award, KAIST EE | Spring 2022
Research Breakthroughs, KAIST | Spring 2021
The Qualcomm Innovation Fellowship | Dec. 2020
Best TA Award, KAIST | Jun. 2020
Department Honors (Top-3) Scholarship, KAIST | Spring 2017
Dean's List, KAIST | Spring 2016
National Science & Engineering Scholarship | Spring 2016 - Spring 2018
Machine Learning Fairness and its Convergence with Robustness
Tutorial @ IEEE BigComp Conference | Feb. 2023
Machine Learning Robustness, Fairness, and their Convergence
Tutorial @ ACM SIGKDD Conference | Aug. 2021
Responsible AI Techniques for Model Training
TechTalk to the TensorFlow team @ Google Korea | Feb. 2020