Ki Hyun Tae

Biography

I am a Ph.D. candidate at KAIST Data Intelligence Lab, advised by Professor Steven Euijong Whang. I received my bachelor's degree in Electrical Engineering from KAIST in 2018.

My research interests lie in Data-centric and Responsible AI. While model-centric AI focuses on improving the training algorithm to increase model accuracy, data-centric AI focuses on improving the data itself to increase model accuracy. Moreover, I believe that Responsible AI problems such as fairness and robustness also need to be solved in a data-centric fashion as AI is only as good as its data. To this end, my current research aims to develop fundamental solutions to realize Responsible and accurate AI from various data-centric perspectives, which include data acquisition, labeling, and cleaning.

Curriculum Vitae / Google Scholar

Email: kihyun.tae {at} kaist {dot} ac {dot} kr

Publications

Falcon: Fair Active Learning using Multi-armed Bandits [Paper]
K. Tae, H. Zhang, J. Park, K. Rong, and S. E. Whang
Accepted to 50th Int'l Conf. on Very Large Data Bases (VLDB), Aug. 2024. (Top Database conference)
iFlipper: Label Flipping for Individual Fairness [Paper / Talk / Slides / Code / Poster]
H. Zhang*, K. Tae*, J. Park, X. Chu, and S. E. Whang (*: Equally Contributed)
In Proc. 2023 ACM SIGMOD Int'l Conf. on Management of Data (SIGMOD), June 2023. (Top Database conference)
Responsible AI Challenges in End-to-end Machine Learning [Paper]
S. E. Whang, K. Tae, Y. Roh, and G. Heo
IEEE Data Engineering Bulletin, Mar. 2021.
Slice Tuner: A Selective Data Acquisition Framework for Accurate and Fair Machine Learning Models [Paper / Talk / Slides / Code]
K. Tae and S. E. Whang
In Proc. 2021 ACM SIGMOD Int'l Conf. on Management of Data (SIGMOD), June 2021. (Top Database conference)
Automated Data Slicing for Model Validation: A Big data - AI Integration Approach [Paper]
Y. Chung, T. Kraska, N. Polyzotis, K. Tae, and S. E. Whang
In IEEE Transactions on Knowledge and Data Engineering (TKDE), Dec. 2020. (Top Database journal)
Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI Integration Approach [Paper / Slides]
K. Tae, Y. Roh, Y. Oh, H. Kim, and S. E. Whang
In 3rd Int'l Workshop on Data Management for End-to-End Machine Learning, DEEM @ ACM SIGMOD, June 2019.
Slice Finder: Automated Data Slicing for Model Validation [Paper / Poster]
Y. Chung, T. Kraska, N. Polyzotis, K. Tae, and S. E. Whang
In IEEE Int'l Conf. on Data Engineering (ICDE), Apr. 2019. Short paper. (Top-3 Database conference)

Education

Integrated M.S./Ph.D. in Electrical Engineering, KAIST, Mar. 2018-Feb.2024 (Expected).
B.S. in Electrical Engineering (Cum Laude), KAIST, Mar. 2014-Feb. 2018.
Korea Science Academy, Mar. 2011-Feb. 2014.

Talks

Flipper: Label Flipping for Individual Fairness
Conference talk, ACM SIGMOD 2023, June 2023.
Slice Tuner: A Selective Data Acquisition Framework for Accurate and Fair Machine Learning Models
Conference talk, ACM SIGMOD 2023 (Virtual), June 2021.
Responsible AI Techniques for Model Training and Data Collection
TechTalk, Tensorflow Team @ Google Korea, Feb. 2020.
Data Cleaning for Accurate, Fair, and Robust Models: A Big Data - AI Integration Approach
Conference talk, DEEM @ ACM SIGMOD 2019, June 2019.

Honors

Research Breakthroughs, KAIST, Mar. 2023.
- Among 15 top biannual research achievements in KAIST College of Engineering
Best TA Award, KAIST EE, Oct. 2019.
Graduation with Honors (Cum Laude), KAIST, Feb. 2018.

Experience

Teaching Assistant, KAIST
- Foundation of Big Data Analytics (EE412)
  Fall 2019, Fall 2021
- Database and Big Data Systems (EE488/EE477)
  Spring 2019 (Head TA), Spring 2021
- Co-op Internship Individual Study
  Winter 2018, Summer 2019, Winter 2020
- Data Structures and Algorithms For Electrical Engineering (EE205)
  Fall 2020 (Head TA)
- Programming Structure For Electrical Engineering (EE209)
  Spring 2020
- Undergraduate Research Program (URP)
  Spring 2018 - Fall 2018
- Introduction to Programming (CS101)
  Fall 2017
Undergraduate Researcher, Semiconductor System Lab, KAIST
- Stereo matching using deep learning, and weight quantization for deep learning
  Mar. 2017 - July 2017
Cu-op Research Intern, K-healthware
- Online detection algorithm for cardiac arrhythmias using signal processing
  Winter 2016
Undergraduate Researcher, Cho's Circuits & Systems Lab, KAIST
- Acoustic communication, transmitting image data over a frequency of 17 kHz
  Feb. 2016 - June 2016

Domestic Patents

Method and Apparatus for Creating Labeling Model with Data Programming
S.E.Whang, K. Tae, Y. Roh, G. Heo
10-2342495-0000, granted Dec. 2021.