Xuan Wang is a Ph.D. student in Engineering Education at the University of Georgia, working under the supervision of Dr. Rachel Figard in the ACCESS Lab. He holds a B.Eng. in Traffic Equipment and Control Engineering from Beijing University of Technology and an M.Eng. in Transport Planning and Engineering from the University of Leeds, UK.

Xuan’s research sits at the intersection of computational methods and engineering education. He currently contributes to the EngineerTok project, which examines how Generation Z students encounter and make sense of engineering through TikTok content, drawing on the Theory of Memorable Messages and Social Cognitive Career Theory. His work applies Natural Language Processing techniques, including sentiment analysis, hashtag segmentation, and topic modeling, to large-scale social media datasets. More broadly, he is interested in how technology and social media mediate the development of engineering identity and in the ethical integration of AI tools into engineering education.

Having studied and lived in China, the United Kingdom, and the United States, Xuan brings a cross-cultural perspective to questions about how engineering is taught, learned, and perceived across different educational systems and cultural contexts.