Chaolan Lin

My research asks how humans infer meaning, trust, and reality under uncertainty, and how these cognitive mechanisms can inform the development of socially aligned and trustworthy AI and robotics. My current work is organized around three interconnected themes:

​

Theme 1. Belief revision and representational reasoning in technology-mediated contexts

Using novel experimental paradigms in video chat and augmented reality, I showed that children actively evaluate representational reliability and engage in hypothesis-driven exploration, with their epistemic actions predicting belief accuracy. This work provides mechanistic evidence that belief revision reflects structured inferential processes that extend classic theory-of-mind and appearance-reality research into modern technological contexts.

​

Theme 2. Social evaluation of artificial agents and dynamics of trust

​Through longitudinal and experimental studies of social robots and virtual agents, I showed that people’s social evaluations of artificial agents are shaped by perceived sociability, agency, and reliability, and that trust dynamically recalibrates with experience rather than remaining static. This work provides empirical evidence that trust in artificial systems is a cognitive process that evolves through interaction.​​​

​

Theme 3. Studying cognition in ecologically valid settings

I developed ecologically valid methods across human-agent, video-mediated, and mixed-reality interactions, combining multimodal behavioral measures (e.g., gaze, motion trajectories, epistemic actions) with mixed-effects and longitudinal modeling to rigorously study cognition in real-world technology contexts.