About Me

Hi, my name is Inha Cha. I'm a Ph.D. student at Georgia Tech working with Dr. Richmond Wong! I'm working in the fields of Human-Computer Interaction (HCI), Design, and Science and Technology Studies (STS).

My research includes:

  • exploring the sociotechnical dynamics that shape AI adoption, resistance, and deliberation in professional settings.
  • rethinking underlying assumptions and prevailing norms in ML development and exploring alternatives.
  • reflecting on what we study in HCI and how we study it.

Before joining Georgia Tech, I worked as an AI product UX designer at Upstage. I completed my master's degree in the Dept. of Industrial Design at KAIST. I did my undergrad in Aesthetics and Information Science at Seoul National University.

Recent News

🩷 First-authored paper accepted to CHI 2025! Looking forward to reconnecting with familiar faces and meeting new ones in Japan! [Jan 2025]

🔥 Recognized by Georgia Tech's Center for Teaching and Learning Thanks-a-Teacher Award for excellence in teaching and impact on student learning in CS 8001 [Dec 2024]

🎉 Awarded a $5,000 Seed Grant from AIAI as PI for the project "AI non-use toolkits for design and creative professionals" [Nov 2024]

Publications

Please see my Google Scholar page for the most up-to-date publications.

Tensions Between Sovereignty and Interdependence: Challenges in Enacting Sociotechnical Imaginaries of Local Foundation Model Development in South Korea
In Review

Understanding Socio-technical Factors Configuring AI Non-Use in UX Work Practices
Inha Cha and Richmond Wong
ACM Conference on Human Factors in Computing System 2025 (To appear)(CHI 2025)
pdf

Discovering Factor Level Preferences to Improve Human-Model Alignment
Juhyun Oh, Eunsu Kim, Jiseon Kim, Wenda Xu, Inha Cha, William Yang Wang, Alice Oh
arxiv

Ethics Pathways: A Design Activity for Reflecting on Ethical Engagement in HCI Research
Inha Cha*, Ajit Pillai*, Richmond Wong
ACM Conference on Designing Interactive Systems 2024 (DIS 2024)
pdf | resource

Investigating the Potential of Group Recommendation Systems As a Medium of Social Interactions: A Case of Experiences Between Two Users
Daehyun Kwak, Soobin Park, Inha Cha, Hankyung Kim, Youn-kyung Lim
ACM Conference on Human Factors in Computing Systems 2024 (CHI 2024)
pdf

Unlocking the Tacit Knowledge of Data Work in Machine Learning
Inha Cha*, Juhyun Oh*, Cheul Young Park*, Jiyoon Han, Hwalsuk Lee
ACM Conference on Human Factors in Computing Systems 2023 (CHI LBW 2023)
pdf

Exploring the Use of a Voice-based Conversational Agent to Empower Adolescents with Autism Spectrum Disorder
Inha Cha, Sung-In Kim, Hwajung Hong, Heejeong Yoo, Youn-kyung Lim
ACM Conference on Human Factors in Computing Systems 2021 (CHI 2021)
pdf

Toward Becoming a Better Self: Understanding Self-Tracking Experiences of Adolescents with Autism Spectrum Disorder Using Custom Trackers
Sung-In Kim, Eunkyung Jo, Myeonghan Ryu, Inha Cha, Young-Ho Kim, Heejung Yoo, Hwajung Hong
EAI International Conference on Pervasive Computing Technologies for Healthcare 2019 (Pervasive Health 2019)
pdf

A Study for Specializing a Chatbot-based Self-Management Program for Adolescents with Autism Spectrum Disorder
Sung-In Kim, Myeonghan Ryu, Eunkyung Jo, Inha Cha, Young-Ho Kim, Heejung Yoo, Hwajung Hong
Proceedings of HCI KOREA 2019 (HCI Korea 2019)
pdf

Service

Reviewer   ACM DIS (2023, 2024, 2025), ACM CHI (2022, 2024, 2025), ACM CHI LBW (2024, 2025)

* 4 Special Recognitions for Outstanding Reviews from ACM CHI

Volunteer   ACM FAccT (2022), ACM DIS (2021, 2024)