Lifeng Fan

Papers

Total Citations

H-Index

About

Lifeng Fan is a researcher whose work sits at the compelling intersection of cognitive science, artificial intelligence, and human-robot interaction. His research focuses on socio-cognitive modeling, particularly the computational representation of human mental states and their influence on collaborative systems. Fan's most notable contribution centers on developing frameworks that enable robots to reason about human false beliefs — a foundational concept in Theory of Mind — bridging classical cognitive science with modern AI. In his influential 2020 paper, "Joint Inference of States, Robot Knowledge, and Human (False-)Beliefs," he proposes an elegant graphical model using parse graphs to unify the representation of object states, robot knowledge, and human belief systems, allowing machines to better anticipate and respond to human cognitive perspectives during interaction. This work, accumulating 18 citations, represents a meaningful step toward building socially intelligent robots capable of understanding not just what humans know, but what they mistakenly believe. Fan's contributions are particularly valuable for students and researchers exploring human-aware AI, cognitive robotics, and the computational modeling of social intelligence — areas increasingly critical as AI systems are deployed in collaborative, real-world environments alongside people.