Taewan Kim

About me

Research

Publications

CV


Ph.D. Candidate / HCI, Design

Department of Industrial Design, KAIST
Bldg. N25, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
taewan@kaist.ac.kr, @twkim24(twitter)

๐Ÿ‘‹ Hi there

I'm Taewan Kim, a Ph.D. student in the Department of Industrial Design at the KAIST, advised by Prof. Hwajung Hong. Currently I'm a member of DxD Lab. Prior to entering KAIST, I received M.E in Creative Design Engineering from the UNIST where I was advised by Prof. Hwajung Hong. I also hold a B.S in Industrial Design from Handong University.

As an HCI researcher with a background in industrial design, my primary research focuses on designing everyday Human-Ai Interactions (HAI) with a Human-centered design approach. Currently, I am working on investigating the design of HAI in the Mental-wellbeing domain. Recently, I investigated exploiting prediction algorithms and explainability that facilitate self-reflection for the mental-wellbeing (Accepted to CHI 2022). I also developed a social bot displaying depressive symptoms and disclosing vulnerable experiences to investigate the role of virtual agents as care receivers for mental health (Accepted to CHI 2020).

Based on my strength in qualitative user research and human-centered design, I create artifacts, methodologies, and frameworks to inspire meaningful and positive algorithmic experiences for HCI researchers and practitioners.

๐Ÿ“ฐ News
Feb, 2022: Our two CHI2022 papers have been conditionally accepted! ๐ŸŽ‰
Jan, 2022: A paper Prof. Jennifer G. Kim led, and I co-authored was accepted to CSCW2022! ๐ŸŽŠ
Sep, 2021: I moved to Daejeon for starting a Ph.D. course in ID KAIST. ๐Ÿšš
โ–ถSee all updates


๐Ÿ—‚ Research

Prediction for Retrospection: Integrating Algorithmic Stress Prediction into Personal Informatics Systems for Mental Health

In this study, we developed MindScope, an algorithm-assisted stress management system that determines user stress levels and explains how the stress level was computed based on the user's everyday activities captured by a smartphone. We discuss the implications of exploiting prediction algorithms and explainability that facilitate retrospection.
ACM CHI 2022


Understanding University Studentsโ€™ Experiences, Perceptions, and Attitudes Toward Peers Displaying Mental Health-related Problems on Social Network Sites

Grapefruit slice atop a pile of other slices

In this paper, we investigate how students recognize, perceive, and react to peers who display mental health related challenges on SNSs in South Korea, where young adults are the age group that is most at risk for suicide. We discuss design implications for SNSs that would help platforms facilitate support exchanges among peers.
JMIR Mental Health 2021


Designing Social Bot as a Care-Receiver to Promote Mental Health and Reduce Stigma

Grapefruit slice atop a pile of other slices

In this study, we proposed a Facebook-based social bot displaying depressive symptoms and disclosing vulnerable experiences that allows users to practice providing reactions online. We investigated how 55 college students interacted with the social bot for three weeks and how these support-giving experiences affected their mental health and stigma.
CHI2020 paper


Understanding algorithmic user experience of symptom checker

Grapefruit slice atop a pile of other slices

An algorithm-based symptom checker is a service that predicts and informs the expected disease name based on the symptoms entered by users and informs the user of actions to be taken afterward. In this study, we conduct an empirical study defining challenges that prevent user trust toward algorithm-based symptom checkers.
CHI2021 Workshop position paper


Calm Station: An Interactive Perpetual Desk Object that Reduces Digital Distractions

Grapefruit slice atop a pile of other slices

In this work, we present Calm Station, an interactive desk object which generate dynamic motions of a metal marble on a wooden tray. Calm Station is designed to convey daily notifications with abstract, poetic movements.
DIS2018 Demo, Video


FamCom: A Communication Service Enhancing Conversation Quality Between Elders Residing in Care Hospital and Their Family Member

Grapefruit slice atop a pile of other slices

FamCom is a service which aids a patient in care hospital to feel more intimate with family members by improving the quality of conversation.
CHI2015 Student Design Competition, Video



๐Ÿ“š Publications

Journal Articles / Conference Papers (Peer-Reviewed)

The Workplace Playbook VR: Exploring the Design Space of Virtual Reality to Foster Understanding and Support of Autistic People in the Workplace
Jennifer G. Kim, Taewan Kim, Sungin Kim, Soyeon Jang, Stephanie Lee, Heejung Yoo, Kyungsik Han, and Hwajung Hong
ACM CSCW 2022 (To Appear)

Prediction for Retrospection: Integrating Algorithmic Stress Prediction into Personal Informatics Systems for College Students' Mental Health
Taewan Kim, Haesoo Kim, Hayeon Lee, Hwarang Goh, Shakhboz Abdigapporov, Mingon Jeong, Hyunsung Cho, Kyungsik Han, Youngtae Noh, Sung-Ju Lee and Hwajung Hong
ACM CHI 2022 - DOI, PDF

Sad or just jealous? Using Experience Sampling to Understand and Detect Negative Affective Experiences on Instagram
Mintra Ruensuk, Taewan Kim, Hwajung Hong, and Ian Oakley
ACM CHI 2022 - DOI, PDF

Understanding University Studentsโ€™ Experiences, Perceptions, and Attitudes Toward Peers Displaying Mental Health-related Problems on Social Network Sites: Online Survey and Interview Study
Taewan Kim, and Hwajung Hong
JMIR Mental Health 2021 - DOI, PDF

In Helping a Vulnerable Bot, You Help Yourself: Designing a Social Bot as a Care-Receiver to Promote Mental Health and Reduce Stigma
Taewan Kim, Mintra Ruensuk, and Hwajung Hong
ACM CHI 2020 - DOI, PDF

Design Constraints and Their Influence upon Design Outcome
Taewan Kim, James Andrew Self, and Hwajung Hong
Archives of Design Research 2018 - DOI, PDF


Extended Abstracts, Position Paper, Poster (Lightly Peer-Reviewed)

Leveraging challenges of an algorithm-based symptom checker on user trust through explainable AI
Youjin Hwang, Taewan Kim, Junhan Kim, Joonhwan Lee, and Hwajung Hong
ACM CHI 2021 Workshop on Realizing AI in Healthcare: Challenges Appearing in the Wild - PDF

์งˆ๋ณ‘์˜ ์ž๊ฐ€ ์ง„๋‹จ์„ ์œ„ํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜ ๊ธฐ๋ฐ˜ ์ฆ์ƒ ํ™•์ธ ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์˜ ์‚ฌ์šฉ์ž ๊ฒฝํ—˜์— ๊ด€ํ•œ ํƒ์ƒ‰์  ์—ฐ๊ตฌ (An exploratory study on the algorithm user experience of a symptom checker application for self-diagnosis)
Taewan Kim, Youjin Hwang, Junhan Kim, Joonhwan Lee, and Hwajung Hong
The Proceedings of HCI KOREA 2021 - PDF

Studying Students Experiencing Mental Health Problems
Taewan Kim, and Hwajung Hong
CSCW 2018 Workshop on Conducting Research with Stigmatized Populations - PDF

Calm Station: An Interactive Perpetual Desk Object that Reduces Digital Distractions
Taewan Kim, Young-Woo Park, and Hwajung Hong
ACM DIS 2017 DEMO - DOI, PDF, Video

FamCom: A Communication Service Enhancing Conversation Quality Between Elders Residing in Care Hospital and Their Family Member
Mingu Kanng, Taewan Kim, Youngjae Kim, and Junghwan Ahn
ACM CHI 2015 Student Design Competition - DOI, PDF, Video