I am a Research Scientist at NAVER AI Lab at NAVER Cloud, leading the Human-Computer Interaction (HCI) Research Group. I design, develop, and evaluate Personal Informatics (PI) technologies that empower people to better learn about themselves and make positive changes in their behaviors and thoughts. Recently, I have investigated how we can leverage (generative) AIs for PI systems to acknowledge and account for the lifelong challenges of marginalized populations.
Research Approaches
Understand. To deeply comprehend user needs and expert practice, I conduct formative interviews and focus groups with domain experts and target populations.
Design. Based on lessons learned from the formative study, I create engaging user experiences through hands-on design of visual interfaces, information architecture, and interaction patterns.
Implement. I develop high-fidelity working prototypes that translate the designs into functional systems. I code across platforms using appropriate technologies to create robust implementations that support real-world evaluations.
Evaluate. I evaluate the working prototypes through mixed-methods approaches including lab studies and in-the-wild deployments. My analysis combines qualitative techniques (thematic analysis) with quantitative measures to provide comprehensive insights into user experiences and system effectiveness.
For my permanent e-mail address, please check my CV.
Selected Awards
Academic Service
- ACing - ACM CHI '25 (Health), ACM CSCW '24 (Jan), ACM CHI '24 (Health), IEEE PacificVis '23
Miscellaneous Facts
๐ซถ My MyersโBriggs Type Indicator (MBTI) is ENFJ (Extraversion-iNtuition-Feeling-Judging).
๐จโ๐ฉโ๐ฆ I am going to be a dad soon I'm a dad of one boy.
Autiverse: Eliciting Autistic Adolescents' Daily Narratives through AI-guided Multimodal Journaling
Migyeong Yang,
Kyungah Lee,
Jinyoung Han,
SoHyun Park,
and Young-Ho Kim
Nonarchival preprint (full paper)
AutiHero: Leveraging Generative AI in Social Narratives to Engage Parents in Story-Driven Behavioral Guidance for Autistic Children
Jungeun Lee,
Kyungah Lee,
Inseok Hwang,
SoHyun Park,
and Young-Ho Kim
Nonarchival preprint (full paper)
LingoQ: Bridging the Gap between ESL Learning and Work through AI-Generated Work-Related Quizzes
Yeonsun Yang,
Sang Won Lee,
Jean Y. Song,
Sangdoo Yun,
and Young-Ho Kim
Nonarchival preprint (full paper)
PlanFitting: Personalized Exercise Planning with Large Language Model-driven Conversational Agent
Donghoon Shin,
Gary Hsieh,
and Young-Ho Kim
ACM CUI 2025 (full paper)
AACessTalk: Fostering Communication between Minimally Verbal Autistic Children and Parents with Contextual Guidance and Card Recommendation
Dasom Choi,
SoHyun Park,
Kyungah Lee,
Hwajung Hong,
and Young-Ho Kim
ACM CHI 2025 (full paper)
ELMI: Interactive and Intelligent Sign Language Translation of Lyrics for Song Signing
Suhyeon Yoo,
Khai N. Truong,
and Young-Ho Kim
ACM CHI 2025 (full paper)
ExploreSelf: Fostering User-driven Exploration and Reflection on Personal Challenges with Adaptive Guidance by Large Language Models
Inhwa Song,
SoHyun Park,
Sachin R. Pendse,
Jessica Lee Schleider,
Munmun De Choudhury,
and Young-Ho Kim
ACM CHI 2025 (full paper)
ChaCha: Leveraging Large Language Models to Prompt Children to Share Their Emotions about Personal Events
Woosuk Seo,
Chanmo Yang,
and Young-Ho Kim
ACM CHI 2024 (full paper)
MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling
Taewan Kim,
Seolyeong Bae,
Hyun Ah Kim,
Su-woo Lee,
Hwajung Hong,
Chanmo Yang*,
and Young-Ho Kim*
(*co-corresponding)ACM CHI 2024 (full paper)
Understanding the Impact of Long-Term Memory on Self-Disclosure with Large Language Model-Driven Chatbots for Public Health Intervention
Eunkyung Jo,
Yuin Jeong,
SoHyun Park,
Daniel A. Epstein,
and Young-Ho Kim
ACM CHI 2024 (full paper)
Leveraging Large Language Models to Power Chatbots for Collecting User Self-Reported Data
Jing Wei,
Sungdong Kim,
Hyunhoon Jung,
and Young-Ho Kim
PACM HCI (CSCW 2024) (full paper)
Understanding the Benefits and Challenges of Deploying Conversational AI Leveraging Large Language Models for Public Health Intervention
Eunkyung Jo,
Daniel A. Epstein,
Hyunhoon Jung,
and Young-Ho Kim
ACM CHI 2023 (full paper)
Leveraging Pre-Trained Language Models to Streamline Natural Language Interaction for Self-Tracking
Young-Ho Kim,
Sungdong Kim,
Minsuk Chang,
and Sang-Woo Lee
NAACL 2022 Workshop on "Bridging HCI and NLP" (short paper)
MyMove: Facilitating Older Adults to Collect In-Situ Activity Labels on a Smartwatch with Speech
Young-Ho Kim,
Diana Chou,
Bongshin Lee,
Margaret Danilovich,
Amanda Lazar,
David E. Conroy,
Hernisa Kacorri,
and Eun Kyoung Choe
ACM CHI 2022 (full paper)
Data@Hand: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction
Young-Ho Kim,
Bongshin Lee,
Arjun Srinivasan,
and Eun Kyoung Choe
ACM CHI 2021 (full paper)
Understanding Personal Productivity: How Knowledge Workers Define, Evaluate, and Reflect on Their Productivity
Young-Ho Kim,
Eun Kyoung Choe,
Bongshin Lee,
and Jinwook Seo
ACM CHI 2019 (full paper)
OmniTrack: A Flexible Self-Tracking Approach Leveraging Semi-Automated Tracking
Young-Ho Kim,
Jae Ho Jeon,
Bongshin Lee,
Eun Kyoung Choe,
and Jinwook Seo
PACM IMWUT (UbiComp 2017) (journal article)
TimeAware: Leveraging Framing Effects to Enhance Personal Productivity
Young-Ho Kim,
Jae Ho Jeon,
Eun Kyoung Choe,
Bongshin Lee,
KwonHyun Kim,
and Jinwook Seo
ACM CHI 2016 (full paper)
