Human–Computer Interaction at Scale
The KAIST Interaction Lab (KIXLAB) is a human-computer interaction research group in the School of Computing at KAIST.
We build interactive systems that support interaction at scale.
We often take an interdisciplinary approach to our research,
by connecting computer science with learning science and social science,
and aim to deploy our systems to real users.
Keywords: crowdsourcing, human computation, interactive data analysis, online education, civic engagement, information discovery.
Building online crowdsourcing platform to collect contextual, emotional, and intentional labels on dialog videos
Building data-driven personas in smart space by analyzing interactions at scale
Mining and Analyzing Diverse Processes in Cooking Recipes
Language Learning Interface for Development of Pragmatic Competence through Learnersourcing Video Annotation
Our paper wins a Best Student Paper Honorable Mention at IUI 2018
Three CHI 2018 late-breaking work (LBW) papers accepted
Three late breaking work papers to CHI 2018 have been accepted: civic engagement, data-driven personality detection, and learnersourcing.
KIXLAB presents 10 posters at the HCI@KAIST Workshop
At the annual HCI@KAIST Workshop, KIXLAB members share 10 of their latest research projects.
ConceptScape wins an Honourable Mention Award for CHI 2018
The ConceptScape paper by Ching Liu, Juho Kim, and Hao-Chuan Wang wins an Honourable Mention Award for CHI2018.
Interns & visiting Ph.D. students!
KIXLAB welcomes five winter undergrad interns: Jiyoun Ha, Hyoungwook Jin, Tae Soo Kim, Hyunjong Lee, and Seayeon Lee.
We also have two visiting Ph.D. students: Ray Hong from the University of Washington, USA, and Maria De Las Mercedes Huertas Miguelanez from the University of Trento, Italy.
RecipeScape website is up!
The project website for RecipeScape is live now! It’s an interactive tool for analyzing cooking instructions at scale.
CHI2018: 7 papers conditionally accepted
We’re happy to share that seven papers from KIXLAB and collaborators have been conditionally accepted to CHI2018.
IUI2018: one paper conditionally accepted
A paper is conditionally accepted to IUI2018: Two Tools are Better Than One: Tool Diversity as a Means of Improving Aggregate Crowd Performance led by Jeanyoung Song.
Exprgram selected as best paper runner-up @ GroupSight 2017 Workshop
Exprgram: A Video-based Language Learning Interface Powered by Learnersourced Video Annotations. by Kyungje Jo, John Joonyoung Chung, and Juho Kim is selected as a best paper runner-up at the GroupSight 2017 Workshop on Human Computation for Image and Video Analysis @ HCOMP 2017.
Exprgram wins grand prix for URP (Undergraduate Research Program) project
Kyungje Jo, an undergrad intern, wins a grand-prix for his URP (Undergraduate Research Program) project: Learning Diverse Expressions through Video Mining.
Summer 2017 Undergraduate Research Internship
We are looking for a few undergraduate research interns to join KIXLAB this summer. You can find the details on Prof. Juho Kim’s website.
New lab members
We are happy to welcome new members to our lab. Eunyoung Ko, Jonghyuk Jung, Hyungwoo Kim and Hyunwoo Kim are joining our team.
CS374 Intro to HCI started
This semester, a new course is being offered by Prof. Juho Kim from KIXLAB, Intro to HCI (CS374). Information about the class can be found on the course website.
We’ve started the year with a number of publications accepted to CHI, CSCW and other venues. You can find our latest contributions on our new publications page.
Spring 2017 Undergraduate Research Internship
We are looking for a few undergraduate research interns to join KIXLAB this spring. You can find the details on Prof. Juho Kim’s website.
CS492 Crowdsourcing course finished
In Fall 2016, Prof. Juho Kim from KIXLAB taught CS492: Crowdsourcing. Information about the class and students project gallery can be found on the course website.
The new KAIST Interaction Lab has officially opened. We are kicking off with one Ph.D. student and five summer undergrad interns.