Data Intelligence Lab

Welcome to the Data Intelligence Lab!

Mission statement: to push the boundaries of data intelligence research and train the next leaders from KAIST

Our research focuses on Big data - AI integration. We believe the 4th industrial revolution is upon us where manufacturing becomes automated, and smart factories and IoT devices produce massive amounts of data. As a result, there is a strong need for researchers with expertise in Big data and AI to analyze and manage this data. We work closely with the industry (Google AI, Google Cloud, SK Telecom, and SK Hynix).

We are looking for experienced Post-docs and highly-motivated Masters and PhD students. If you are interested in joining the DI Lab, please read this first. Here is a list of recommended courses and a lab fair poster designed by my students.


  • [2019/3] Welcoming our new students Seonghyeon Hwang and Dayun Lee!
  • [2019/2] Committee member for the KAIST AI Graduate School (first of its kind in Korea, press 1, press 2, press 3)
  • [2019/1] Data Validation for Machine Learning paper accepted to SysML 2019 (new conference, first proceedings)
  • [2018/12] Recipient of a Google Cloud Platform (GCP) Education Grant (first in Korea)
  • [2018/11] A Survey on Data Collection for Machine Learning submitted (first paper with my students)!
  • [2018/9] Recipient of Google AI Focused Research Award (first in Asia, press)
  • [2018/8] Welcoming our new student Byungkyu Lee!
  • [2018/8] Slice Finder: Automated Data Slicing for Model Validation paper accepted to IEEE ICDE 2019 (Top-3 conference in Databases)
  • [2018/8] Proud to be supported by the NRF through the AI ERC program for 6 years (KAIST MARS AI Integrated Research Center)
  • [2018/7] Proud to be supported by SK Telecom (Large-scale image-based data labeling for component defect classification)
  • [2018/6] Invited talk and panel at the AI with Google Conference (homepage, press 1, press 2, slides) with Jeff Dean
  • [2018/6] Welcoming our new student Yuji Roh!
  • [2018/5] Data Lifecycle Challenges in Production Machine Learning: A Survey paper accepted to ACM SIGMOD Record (SCIE)
  • [2018/3] Interview (in Korean) with the KAIST EE Newsletter
  • [2018/2] Welcoming our first students Geon Heo and Ki Hyun Tae!