Shu-Jung Han

Information Science Ph.D. Student at Cornell University
Mixed-Method UX & HCI

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I am a third-year Ph.D. student in Information Science at Cornell University, advised by Susan Fussell.

My research focuses on understanding the social-psychological impact of AI-mediated communication and human-AI interaction. I aim to uncover the complexities of human engagement with AI in social contexts and explore ways to foster meaningful and ethical human-AI collaboration.

Through mixed methods, I study how AI reshapes interpersonal dynamics and community interactions in online settings. Currently, I focus on investigating visual-based generative AI and its influence on online interpersonal communication at both individual and community levels.

Previously, I was fortunate to work with Yihsiu Chen at National Chengchi University, where I deepened my interest and expertise in UX and HCI research.

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Experience

  1. 2022 – present

    Cornell University

    PhD Student in Information Science

  2. 2020 – 2020

    104 Corporation

    UX Research Intern

  3. 2018 – 2022

    National Chengchi University

    M.S. in Digital Content and Technologies, College of Communication

  4. 2017 – 2017

    CommonWealth Education Media and Publishing

    Journalism Intern

  5. 2014 – 2018

    National Chiao Tung University

    B.A. in Communication and Technology

Publications

Understanding User Perceptions and the Role of AI Image Generators in Image Creation Workflows

Shu-Jung Han and Susan Fussell

CHI 2025new

We investigated the impact of AI image generators on image creation workflows, decision-making, and user perceptions. By conducting in-depth interviews and think-aloud tasks with 26 end users, our results indicated that functional goals drive cross-tool integration for desired outcomes. Additionally, the recreational use of AI image generators affects the social implications of image sharing.

  Abstract   Paper (coming soon)   Video (coming soon)

The Effects of AI-Based Agent’s Social Roles and Performance on Trust in Human-Agent Interaction

Shu-Jung Han, Shih-Yi Chien, Yihsiu Chen

National Chengchi University, Seoul National University, and University of Tokyo Joint Symposium 2021

Proceedings of 7th Annual Conference of Taiwan Association of Computer-Human Interaction 2021

Our study investigated whether perceiving AI-based agents as social entities, specifically through assigned social roles, influences human trust and human-agent interaction. We conducted a 3x2 between-subjects experiment with a collaborative task. Our findings revealed that perceived social roles and agent performance impact trust, but high social status was found to mitigate the negative effect of poor agent performance on trust.

  Abstract   Paper   Link

Projects

High School Students’ Career Planning: Insights for AI-Driven Job-Matching Solutions

UX Research Intern at 104 Corporation, Taiwan

  Details
  • Executed exploratory research on high school students’ career planning processes to identify potential user needs and market opportunities for job-matching services at 104, Taiwan’s largest online job-matching platform.
  • Conducted 10+ in-depth interviews and analyzed qualitative data to develop user journey maps, uncovering key journey stages and pain points.
  • Collaborated with UX researchers, product design teams, and internal stakeholders to transform research insights into applicable design solutions and integrated AI techniques into human resources applications.

Social Identity and Groups in Human-AI Collaboration

Graduate Research Assitant, worked with Prof. Yihsiu Chen at NCCU, Prof. Chien-Wen (Tina) Yuan at NTU, and Prof. Gary Hsieh at UW

  Details
  • Conducted an interdisciplinary research project investigating the effects of ingroup and outgroup dynamics on human-AI collaboration.
  • Designed, organized, and managed an experimental platform supporting the human-AI collaboration study used by 700+ participants in online and lab settings.
  • Worked with engineering graduate RAs to develop the experiment system, conducted experiments, and analyzed the quantitative data using a series of ANOVA and ANCOVA tests.

AI-Based Agent’s Social Roles and Performance on Trust in Human-Agent Interaction

Graduate Research Assitant at NCCU, advised by Prof. Yihsiu Chen

  Details
  • Investigated the effect of social roles on trust in human-agent interaction (AI-based agent), driven by the tendency of humans to perceive AI agents as social entities in collaborative tasks.
  • Designed lab experiments and developed a full-stack website to stimulate scenarios for behavioral data collection.
  • Conducted in-person lab experiments with 100+ participants, followed by surveys and semi-structured interviews to examine trust dynamics, and analyzed data using SPSS with a series of ANOVA tests.

Built-In Advertising on Mobile User Experience

Graduate Research Assitant at NCCU, advised by Prof. Yihsiu Chen and collaborated with FIH Mobile Ltd.

  Details
  • Proposed a UX research project to understand the effects of built-in advertising on mobile user experience.
  • Conducted eye-tracking experiments, interviews, surveys, and qualitative and quantitative data analysis to investigate users’ behaviors and attitudes toward advertisements with varying placements and design goals.
  • Collaborated with the FIH Mobile design team and delivered findings on balancing advertising effectiveness and UX.

Humanoid Robot and Healthcare in Human-Robot Interaction

Graduate Research Assitant at NCCU, advised by Prof. Shih-Yi Chien

  Details
  • Led a research team consisting of engineering graduate RAs to conduct exploratory research on applications of humanoid robots (e.g., Pepper) in healthcare settings.
  • Proposed research plan, conducted contextual inquiry, and collaborated with long-term care nursing homes to integrate humanoid robots into elderly healthcare services.