Ziang Xiao is an assistant professor in the Johns Hopkins University’s Department of Computer Science. His research is motivated by the fundamental question of understanding humans at scale—e.g., how can we conduct robust and generalizable studies about human behavior?
The goal of his work is to enhance human-AI interaction to expand our knowledge of ourselves. Through this research, Xiao aims to create a more connected research community and democratize novel technologies to operationalize intuitions and curiosities about how we think and behave. His current research focuses on three exciting topics: AI for social science, human-centered model evaluation, and information seeking. Broadly, Xiao’s work lies at the intersection of human computer interaction, natural language processing, and social and personality psychology.
He completed his PhD in computer science at the University of Illinois Urbana-Champaign. Before joining Johns Hopkins, Xiao was a postdoctoral researcher in the Fairness, Accountability, Transparency, and Ethics group at Microsoft Research Montréal.
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A research team including Ziang Xiao has found that popular large language models like GPT-4 cannot yet accurately simulate the real world.
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Winning projects, chosen from a record 286 proposals, include 148 individuals from across the university.
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A Johns Hopkins-led team found that chatbots reinforce our biases, providing insight into how AI could widen the public divide on controversial issues.