Hi!
I’m Dongdong Zhu, a PhD student in the Department of Communication at the University of California, Davis, supervised by Dr. Soojong Kim. My research examines bias, stereotypes, morality of AI, and their impact on human’s behavior, primarily through computational methods and experiments.
Before UC Davis, I completed my research master’s in Communication Science at the University of Amsterdam, a master’s at the London School of Economics and Political Science, and my bachelor’s at Renmin University of China. Before pursuing my Research Master’s, I worked as a global marketing specialist for more than three years, gaining professional experience in international marketing and communication.
Research Interests
- Bias and stereotypes in generative AI and large language models
- Morality and value alignment in AI systems
- AI persuasion and its effects on human attitudes and behavior
Selected Publications
- Kim, S., Kim, H., Kim, K., & Zhu, D. (2026). Algorithmic Portrayals of Mental Health Stigma: Quantifying the Gap Between AI Estimations and Human Perceptions Across Gender Groups. Social Science & Medicine. [Under Revision]
Honors & Awards
- Top Faculty Conference Paper Award, 109th Annual AEJMC Conference (2026)
- Small Grant, Department of Communication, UC Davis ($1,000, 2026)
- Thesis Grant, Digital Communication Methods Lab, University of Amsterdam (€500, 2025)
News
Recent
- 2026.06 Received the Top Faculty Conference Paper Award at the 109th AEJMC Annual Conference, New Orleans, for Algorithmic Portrayals of Mental Health Stigma (with Kim, Kim, Kim).
- 2026.06 Presented two papers at ICA 2026 in Cape Town, South Africa.
- 2026.05 Served as Panel Chair, “Governance, Extremism, and Regulatory Questions,” Comm Horizons 2026, Davis, CA.
- 2026.05 Presented two papers at Comm Horizons 2026 in Davis, CA.
Past
- 2026.02 Presented A Mirror of Reality? Visual Representations of Female Politicians in the EU Across Search Engines and Generative AI at CSS Escape 2026, Davis, CA.
- 2026.02 Presented Whose Morality? Uncovering Ideological Asymmetries in How Large Language Models Judge Political Arguments at CSS Escape 2026, Davis, CA.
- 2026.02 Presented Banned from Detecting Shadowbans (with Khanna, Ausloos, Leerssen) at Etmaal van de Communicatiewetenschap, Arnhem, Netherlands.
- 2025.11 Serving as Reviewer, 76th ICA Annual Conference.
- 2025.06 Presented TikTok News and (the Illusion of) Knowledge at the 75th ICA Annual Conference, Denver, USA.
- 2024.06 Presented Are Housewives Getting Depressed? A Machine Learning Study Based on YouTube at the 74th ICA Regional Hub, Beijing, China.