Shu-Jung Han

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

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I am a fourth-year Ph.D. student in Information Science at Cornell University, concentrating on Human-Computer Interaction (HCI) and Computer-Supported Cooperative Work (CSCW) research, advised by Susan Fussell. My research focuses on understanding people’s sensemaking and decision-making with AI-powered tools and AI content. I investigate the social psychological factors that affect AI adoption and collaborative patterns.

Currently, my work focuses on visual-based generative AI and its influence on online interpersonal communication at both individual and group levels. Through mixed-methods research approaches, I aim to optimize AI-mediated communication and human-AI collaboration while sustaining meaningful human connections.

Previously, I was fortunate to work primarily with Yihsiu Chen and was co-advised by Shih-Yi Chien 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 how AI image generators influence creation workflows, decision-making, and user perceptions through interviews and think-aloud tasks with 26 end users. Results indicated that functional goals guide cross-tool integration, and recreational use affects the social implications of image sharing.

  Abstract   Paper   Video

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

We researched how perceived social roles of AI agents influence trust and collaboration. Through a 3×2 between-subjects experiment, our findings revealed that perceived social roles and agent performance impact trust, but a high social status role was found to mitigate the negative effect of poor agent performance on trust.

  Abstract   Paper   Link

Selected Projects

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

UX Research Intern at 104 Corporation, Taiwan

  Details
  • Executed an exploratory research study on high school students’ career planning decisions, identifying user needs, journey, and market gaps in career planning services for 104 job-matching platform.
  • Conducted 10+ in-depth interviews and synthesized qualitative insights into user personas and journey maps that guided design decisions and business strategies.
  • 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.
  • Conducted online experiments, analyzed the quantitative data using a series of ANOVA and ANCOVA tests, and collaborated with engineering graduate RAs to develop the experiment system.

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.