Short bio
2022 - Now
Tech Leader
NAVER AI Lab
2021 - Now
Research Scientist
NAVER AI Lab
2019 - 2021
Postdoc
Univ. of Maryland
2012 - 2019
PhD (CS)
Seoul Nat'l Univ.
2007 - 2011
BFA (Design)
Seoul Nat'l Univ.
Research internsMore
News
2022.11
Invited talk at Soongsil Univ. CS (In-person)
2022.11
Invited talk at SEOULTECH AI Colloquium (In-person)
2022.11
Invited talk at KAIST CS Dept. (In-person)
2022.10
Serving as a program committee at PacificVis 2023.
2022.7
Sharing our work on a large-language-model-based NLP for self-tracking at NAACL Workshop on HCI+NLP
2022.5
Attending CHI 2022 remotely.
2022.4
Invited talk at UNIST, Design Dept. (Virtual)
I am a Research Scientist and Tech Leader at . As a Human-Computer Interaction researcher, I do research at the intersection of Ubiquitous Computing, Personal Health Informatics, and Personal Data Visualization. Combining my multidisciplinary knowledge in Computer Science and Visual Communication Design, I design and develop computing systems for self-tracking that empower people in the loop of human-data interaction.
I am a recipient of Korea International Postdoc Fellowship supported by National Research Foundation of Korea in 2019, and a Best of CHI Honorable Mention award at ACM CHI 2021.
At NAVER AI Lab, we are actively expanding our research endeavors in the field of HCI and Personal Health Informatics. Please do not hesitate to email me for research collaboration and inquiries about research internship at NAVER AI Lab!
Research Topics
Flexible Human-Data Interaction in Personal Informatics
Personal informatics systems require signficant human efforts in both collecting and exploring the data,
becuase the self-tracking process involves the user's personal context information, which is not recorded in the data.
I explore ways to support such human-data interaction processes in flexible and less-structured manners,
to lower the barriers of lay individuals to novel self-tracking tools.
Personal Informatics ⨯ AI & NLP
Recent advance in Machine Learning and Natural Language Processing technologies opens exciting opportunities in the field of Personal Informatics.
For example, conversational agents equipped with large language models are used to capture various human behavioral information from natural language dialogs.
I am interested in building AI-powered Personal Informatics systems and understanding how should we deal with AI technologies to effectively and ethically handle self-tracking data.
Selected PublicationAll Publication
Leveraging Pre-Trained Language Models to Streamline Natural Language Interaction for Self-Tracking
MyMove: Facilitating Older Adults to Collect In-Situ Activity Labels on a Smartwatch with Speech
Honorable Mention Award
Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction
Understanding Personal Productivity: How Knowledge Workers Define, Evaluate, and Reflect on Their Productivity
OmniTrack: A Flexible Self-Tracking Approach Leveraging Semi-Automated Tracking
TimeAware: Leveraging Framing Effects to Enhance Personal Productivity
Acknowledgment