About

I am a Ph.D. candidate (ABD) in the STEM-designated Communication program at the University of California, Santa Barbara, expected to graduate in June 2027 and on the academic job market for the 2026–2027 cycle. I am advised by Dr. Jiaying Liu in the Communication, Health, and Emerging Media (CHARM) Lab; my dissertation committee additionally includes Dr. Robin Nabi (UCSB) and Dr. Yingdan Lu (Northwestern).

I study how generative AI is reshaping persuasion — both how persuasive messages, campaigns, and tools get designed and who they manage to reach. My approach is computational at every level: I treat AI as three things at once — an object of study (AI-generated media as content), a methodological tool (LLM annotation and other multimodal computational methods as research instruments), and an intervention (AI-tailored messages and chatbots as persuasive tools).

My empirical work is anchored in health communication — especially anti-vaping and tobacco-related campaigns — but the theoretical questions and multimodal computational methods I develop travel readily to adjacent strategic communication contexts: political, corporate, and public-interest messaging. Methodologically, I specialize in multimodal computational analysis of communication content — including large language model annotation, natural language processing, computer vision, and interpretable machine learning — combined with experimental design and neurophysiological measures (fMRI, eye-tracking).

Selected Current Work

• Diss.
  Multimodal Emotional Appeals in Anti-Vaping Videos — A Computational Approach to Fear–Hope Flow and Message Effectiveness. Multimodal computational analysis (visual, auditory, linguistic) with LLM-assisted annotation — tracking how fear and hope move across a video frame by frame to predict which messages persuade and which lose their viewer.
• 2026
  AwardGenerative AI for personalized — and equitable — health messaging. Experiments on whether AI-tailored anti-vaping messages work differently across socioeconomic and value-based subgroups. 2026 AEJMC Mass Communication and Society Division Student Research Award.
• 2026
  Identifying the “recipe” of effective anti-vaping messages Interpretable machine learning to identify the cognitive, social, and emotional profiles that drive effectiveness. With Dr. Jiaying Liu; manuscript targeted for American Journal of Preventive Medicine.
• 2025/26
  Visual realism and misinformation potential of AI-generated images. With collaborators at UC Davis and Northwestern. Proceedings of CHI Extended Abstracts, 2025; Computational Communication Research, 2026.
• Ongoing
  Anti-vaping AI chatbot intervention In development with the CHARM Lab. Building on my earlier study of how audiences perceive AI-generated content (Hong, Peng, & Williams, New Media & Society, 2020).

→ See Research for the full research agenda, publications, and ongoing projects.

Affiliations & Background

Beyond UCSB, I collaborate with the Computational Multimodal Communication Lab (PIs: Prof. Cuihua Shen, Prof. Yilang Peng, Prof. Yingdan Lu) and the Computational Media and Politics Lab at Northwestern (PI: Prof. Yingdan Lu). I am also a trainee in the NIH/FDA CTP-funded Tobacco Regulatory Science Research Community. Before academia, I led brand and marketing at a Beijing-based financial-IT firm and earned my M.A. from USC Annenberg.

Research Interests

Recent

• Aug2026
  AwardSelected for the AEJMC Mass Communication and Society Division Student Research Award.
• Jul2026
  Two presentations at the Summer 2026 NIH Tobacco Regulatory Science (TRS) Meeting, Washington, D.C.
• Jun2026
  Invited talk at the Affect, Ambivalence, and Adjustment Lab, Singapore University of Social Sciences.
• Jun2026
  Four papers presented at the 76th ICA Annual Conference, Cape Town.
• Jun2026
  FundingAwarded a Center for AI and Society Grant, UCSB — $8,000.
• Jun2026
  AwardAwarded the Social Impact Award, Department of Communication, UCSB.
• Apr2026
  Rathje et al. (Nature registered report on social media reduction) covered in The Washington Post.

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