Faculty & Research Highlights, Spring 2026

Guided by a humanity-centered approach to design,  Design Lab faculty work within creative, interdisciplinary research groups that apply rigorous design methods and expand design thinking tools to include design-doing—addressing challenges faced by people from all walks of life and across a range of environments.

In 2026, faculty research and public scholarship engaged this approach across the following areas:

✦  Human-Computer Interaction (HCI)
✦  Artificial Intelligence and the New Information Age
✦  Health and Healthcare Innovation
✦  Climate Adaptation
✦  City and Regional Futures
✦  Design Education
✦  Social Justice and Equity
✦  Design for Creativity and Media

Faculty shared this work through peer-reviewed publications, books, exhibitions, films, and public lectures, and through presentations at leading venues spanning design, computing, social science, and the humanities—including conferences such as CHI, CSCW, DIS, UIST, HCOMP, SIGCSE, as well as forums in urban studies, public health, environmental research, media arts, and policy. Faculty also curated exhibitions, authored scholarly and public-facing books, and contributed expert perspectives to regional, national, and international policy conversations.

Across these domains, Design Lab researchers applied design-doing to explore responsible technologies, cultural and environmental systems, and new models of care, governance, education, and creative practice—advancing design as both a scholarly and civic endeavor.

This spring, Design Lab faculty earned four Honorable Mentions and one Best Paper Award at the premier human-computer interaction conference, alongside a Nature Health article demonstrating how LLMs can provide safe, transparent medical guidance. Their work spans educational AI, embodied scientific practice, interface reasoning, and clinical decision support.

BEST PAPER AWARD · CHI 2026
CoBRA: Programming Cognitive Bias in Social Agents Using Classic Social Science Experiments
Xuan Liu, HaoYang Shang, Haojian Jin

Xuan Liu, HaoYang Shang, and Haojian Jin published CoBRA: Programming Cognitive Bias in Social Agents Using Classic Social Science Experiments in the Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, where it received the ACM SIGCHI Best Paper Award. CoBRA is a toolkit that measures an LLM agent's cognitive bias against validated classical social-science experiments and then regulates the agent's behavior toward a target bias, addressing the long-standing problem that natural-language descriptions of agent behavior produce inconsistent results across models.
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HONORABLE MENTION · CHI 2026
Orca: Browsing at Scale Through User-Driven and AI-Facilitated Orchestration Across Malleable Webpages
Peiling Jiang, Haijun Xia

Peiling Jiang and Haijun Xia present Orca, a prototype browser that treats webpages as malleable material rather than fixed documents locked inside tabs. Instead of handing browsing over to a fully autonomous AI agent, Orca lets people and AI jointly reshape, reorganize, and recombine content from many pages into a single dynamic workspace, aiming to support large-scale information foraging and sensemaking without sacrificing user control. Their evaluation found that this approach increased participants' appetite for exploring information and gave them more flexible control over synthesizing what they found across the web.
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BEST PAPER AWARD · DIS 2026
Exploring Fairy Cursor as a Form of AI Agent for In-the-Flow Assistance: Design Opportunities and Challenges
Yining Cao, James D. Hollan, Haijun Xia

Yining Cao, Jim Hollan, and Haijun Xia published Exploring Fairy Cursor as a Form of AI Agent for In-the-Flow Assistance: Design Opportunities and Challenges in the Proceedings of the 2026 Designing Interactive Systems Conference. The paper starts from a think-aloud study with nine participants that surfaced everyday inefficiencies in information work, then introduces Fairy Cursor -- a design probe that lets AI assistance follow the cursor itself rather than live in a separate chat window, built around three interaction primitives (Mark, Spell, and Memory) -- to examine how people balance the benefits of always-nearby help against its risk of feeling intrusive.
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JOURNAL ARTICLE · PLOS DIGITAL HEALTH
Sharing digital health data responsibly: Balancing open science with participant privacy
Camille Nebeker, Shahin Samiei, Santosh Kumar

Camille Nebeker, Shahin Samiei, and Santosh Kumar published Sharing digital health data responsibly: Balancing open science with participant privacy in PLOS Digital Health. The piece argues that current open-science mandates were written before researchers understood that raw accelerometry from wearables can function as a biometric identifier -- the WristPrint study showed a single day of motion data was enough to re-identify a person with 96% accuracy -- and lays out concrete steps for sharing wearable data without compromising participant privacy.
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FULL PAPER · INTERNET INTERVENTIONS
Exploring online and in-person mental healthcare access and app use in a cohort of people living with disability: results from the 2019 and 2020 California Health Interview Survey
William Bevens, Jeongmi Kim, Biblia Cha, Nicole A. Stadnick, Elizabeth Eikey, Margaret Schneider, Stephen M. Schueller, Dana B. Mukamel, Dara H. Sorkin

William Bevens, Jeongmi Kim, Biblia Cha, Nicole A. Stadnick, Elizabeth Eikey, Margaret Schneider, Stephen M. Schueller, Dana B. Mukamel, and Dara H. Sorkin published Exploring online and in-person mental healthcare access and app use in a cohort of people living with disability in Internet Interventions. Analyzing data from the 2019 and 2020 California Health Interview Survey, the study finds that people with disabilities use a mix of in-person visits, telehealth, and mental health apps -- and that no single channel dominates -- pointing to the need for flexible, multi-modal care systems designed from the outset for accessibility.
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