Yu-Han Chang

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About

Yu-Han Chang is a pioneering researcher at the intersection of cognitive science, artificial intelligence, and computational social science. Her work fundamentally bridges symbolic reasoning and human behavior modeling, with key contributions in image schema representation and networked resource games. In her landmark paper "An Image Schema Language" (2006, 23 citations), Chang introduced ISL—a formal language for encoding and manipulating image schemas that captures both symbolic and quantitative dynamic properties of objects and relationships. This work provides a critical framework for grounding abstract concepts in embodied cognition, influencing cognitive linguistics and AI knowledge representation. Chang's research also explores human decision-making in complex social systems. In "Social Welfare and Inequality in a Networked Resource Game with Human Players" (2013, 2 citations), she designed a graphical online game to study how human players interact in networked resource dilemmas. By analyzing experimental data, Chang demonstrated how social welfare and inequality emerge from individual choices, linking simulation results to real human behavior. Her interdisciplinary approach—combining formal language theory with empirical human experiments—offers powerful tools for understanding both cognitive structures and social dynamics, making her work essential for researchers in AI, cognitive science, and computational social science.