Yike (Cassandra) Shi is a Ph.D. student in Computer Science advised by Professor Hua Shen in the BiAlign Lab. She earned her B.S. in Computer Science from Carnegie Mellon University’s School of Computer Science, with a concentration in Machine Learning. Her research spans human–AI interaction, AI alignment, and safety, combining empirical studies of human–AI interaction with machine learning methods to identify and mitigate harmful AI behavior. She aims to build AI systems that expand human capabilities while supporting safe use in everyday life.
Publications
- Shi, Yike, Qing Xiao, Qing (Diane) Hu, Hong Shen, and Hua Shen. “The Siren Song of LLMs: How Users Perceive and Respond to Dark Patterns in Large Language Models.” CHI, 2026. Best Paper Honorable Mention🏆.
- Yang, Chenyang, Yike Shi, Qianou Ma, Michael Xieyang Liu, Christian Kästner, and Tongshuang Wu. “What Prompts Don’t Say: Understanding and Managing Underspecification in LLM Prompts.” Findings of ACL, 2026.
- Shen, Hua, et al. “Human-AI Interaction Alignment: Designing, Evaluating, and Evolving Value-Centered AI for Reciprocal Human-AI Futures.” CHI, 2026.
Research Interests
- Human–Computer Interaction
- Human–AI Interaction
- AI Safety and Human–AI Alignment