Shanshan Feng

Inception Institute of Artificial Intelligence

Papers

Total Citations

H-Index

About

Shanshan Feng is a pioneering researcher in human-robot interaction, with a specialized focus on the perceptual and cognitive aspects of robot design. Her key research areas include humanoid robot aesthetics, eye-tracking methodology, and the psychological impact of robot appearance on user engagement. Feng’s most notable contribution is her innovative work on evaluating humanoid robot design through global eye-tracking metrics, as demonstrated in her 2020 paper, which has garnered 3 citations. This study broke new ground by establishing that first impressions of robot appearance critically shape subsequent human-robot interactions, and she developed a quantitative framework using eye-tracking to assess design effectiveness. By integrating behavioral metrics with design evaluation, Feng has provided a rigorous, data-driven approach to optimizing robot aesthetics for improved user acceptance and trust. Her work is particularly impactful for students and researchers in robotics and human factors, offering a replicable methodology to test design hypotheses. Feng’s achievements highlight her as a key figure in bridging engineering design with cognitive science, advancing how we understand and improve the initial moments of human-robot encounters.