Incoming Assistant Professor
Edwardson School of Industrial Engineering, Purdue University
Following my appointment as an Assistant Professor at Purdue University, I am excited to launch my new research group, the Interaction Design and Engineering for Augmented Life (IDEAL) Lab.
Please visit my new website to learn more about my research, teaching, and opportunities to join the group (I am actively looking for students who are passionate about human-AI teaming😊!!)
I envision the human-AI collaborations that preserve and promote the positive values unique to human society. My research seeks to understand teamwork dynamics in complex work environments, drawing on traditional cognitive engineering theories and examining how they translate into human-AI interaction. I perform user profiling and predictive modeling, with the ultimate goal of designing adaptive systems that can foster more effective teamwork.
Thanks to the incredible support I've received throughout my academic journey,
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I am grateful to mark the end of my doctoral journey with the George E. Briggs Dissertation Award, which recognizes the best doctoral dissertation in applied experimental and engineering psychology by the American Psychological Association (APA) Division 21.
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I am honored to have recently been awarded the Richard F. and Eleanor A. Towner Prize for Distinguished Academic Achievement, which is presented to an outstanding graduate student in each of the U-M College of Engineering degree programs.
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I am also named a Barbour Scholar, awarded to selected recipients of the Rackham Predoctoral Fellowship.
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I am grateful to be a recipient of the Kwanjeong Educational Foundation Study Abroad Scholarship, awarded through a nationwide selection process in South Korea.
Within the Human Factors and Ergonomics Society (HFES),
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I am happy to share that I have been awarded the Student Member with Honors Award (2025).
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In ASPIRE 2025, one of my accepted papers ("Trust in the Team as a Function of Trust in Individual Agents: Scale Validation and Modeling") received the Best Student Paper Award from the K-HFES Awards Committee.
Ph.D. Candidate, Industrial and Operations Engineering (IOE),
University of Michigan, Ann Arbor
Aug 2022 - May 2026
Dissertation Title: From Dyads to Teams: Modeling Multi-Referent Multi-Level Trust in Multi-Agent Human-AI Teams
Since joining ICRL (Interaction and Collaboration Research Lab) directed by Dr. X. Jessie Yang, I have been deeply involved in applying computational and data science methods to model human trust and behaviors in human-AI interaction and collaboration. My primary focus is on multi-agent human-autonomy interaction (HAI), which involves multiple humans and/or intelligent agents collaborating toward a shared goal, such as defense, crowdsourced evacuation, and search-and-deliver tasks. My core research questions include:
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How can team metrics (e.g., team trust, team communication effectiveness) be defined and quantified?
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How do the behaviors and attitudes of others influence an individual's behavior and attitudes?
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How can we predict the real-time trust and behavioral dynamics?
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How can we promote and encourage human prosocial and altruism behaviors in HAI?
M.S., Industrial Engineering
Seoul National University, South Korea
Mar 2020 - Feb 2022
Dissertation Title: Ergonomics Issues in Improving Kiosk Accessibility for Older Adults
B.S. (Industrial Engineering), B.F.A. (Industrial Design), B.B.A. (Business Administration)
Seoul National University, South Korea
Mar 2014 - Feb 2020
During my undergraduate and master's studies, I led and participated in numerous exciting projects that are fundamentally aimed at enhancing the user experience of products, services, and systems across various domains (e.g., self-service technology, transportation, mobile, AR/VR, etc.) through end-user data analysis and empirical research. Leveraging my unique interdisciplinary background in engineering, design, and business, I contributed to core project activities, which holistically encompass all phases of UX design: designing, prototyping, evaluating, and conducting data-driven analyses.