Qiyao Peng is a Ph.D. candidate in Communication at UC Santa Barbara, working at the intersection of media psychology, health communication, and computational social science. Her research asks what makes persuasive content work, and for whom, in a media environment being remade by generative AI; she models emotion in persuasive video with computational methods, traces audience attention and persuasion resistance with eye-tracking and neural measures, and tests how AI personalization changes what audiences believe and do.
Qiyao treats generative AI as three things at once: a research instrument, an object of audience judgment, and a collaborator in message production. Drawing on theories of emotion, persuasion, and media effects, she examines how emotional dynamics, multimodal message features, and AI personalization shape audience attention, psychological reactance, and behavioral intentions.
Her methodological expertise spans experimental design, LLM annotation, natural language processing, computer vision, eye-tracking, and neurophysiological measurement. She applies these approaches to health promotion and substance use prevention, with support from NIH- and NSF-funded projects.
Her work advances video as data and image as data as methodological contributions to communication research, making the emotional arc of persuasive media a measurable, designable variable and helping build a science of credibility for synthetic content. Recognized with awards from AEJMC, NCA, and SRNT, her research aims to provide data-driven guidance for designing effective health messages in the AI era.
B.A. Honors (2017), The University of Nottingham Ningbo China, International Communication Studies
M.A. (2019), University of Southern California, Communication Management