AI-Supported Group Decision Making
Designing private-vote and confidence-sharing concepts for group decisions where every perspective can be considered.
Lead researcher and experience designer Explore the researchHuman-Centered Researcher + Designer
Building AI that helps people decide better together.
I study how people make subjective decisions with AI, especially in groups. I turn those insights into supportive AI systems and frameworks for stronger collaboration and collective decision-making.
Download My ResumeGroup decisions with AI balance three voices: yours, the AI’s, and your teammate’s.
Hover to explore the different outcomes.
The outcome lives in the messy space between all three.
Explored space, design, and how people experience the built environment.
Investigated how technology can shape experience within physical environments.
Examined how interactive technologies become part of those physical experiences.
Research how people make subjective decisions with AI under social influence.
Reframed individual and group AI-supported decisions as distinct contexts with different outcomes, shifting the research toward peer pressure and purpose-built GenAI support for subjective group work. I lead experiments and surveys examining how social influence shapes users’ opinions, confidence, verification needs, and final decisions when working with GenAI.
Current Ph.D. researchExplore the researchEvaluated whether virtual reality could better prepare veterinary students for high-pressure euthanasia procedures through a between-subjects study comparing VR training with instructor-led training. Students who trained in VR reported greater confidence and achieved higher performance scores, supporting VR as a complement to traditional training.
Delivered product recommendations for the digital mortgage journey, created a reusable prompt framework for research workflows, and won Best Use of AI for Discovery & Research at a company-wide hackathon. I benchmarked Qualtrics Text iQ against ChatGPT, improving qualitative tagging accuracy and efficiency. I also identified patterns in client NPS shifts to inform product recommendations.
Evaluated which sensory cue best supports visual search in virtual reality through a 71-participant mixed-method study comparing haptic, audio, visual, and control conditions. Haptic guidance performed strongest without adding distraction, while audio guidance was the second-most effective condition.
Related case studyExplore the projectConducted user research, contributed to Unity prototyping, and tested a VR learning experience with rural students who may not otherwise consider applying to university. The experience introduced cybersecurity as one possible path and helped students recognize university opportunities that could fit their interests and lives.
Provide ongoing volunteer mentoring to students working on research, design, presentations, and interactive learning projects. Offer feedback on research decisions, prototypes, Blender production, and student publications, and have taught second-year architecture studios.