Dr. Hannuo Tian | Industrial Engineering | Best Researcher Award
Graduate Research Assistant | Guangdong University of Technology | China
Dr. Hannuo Tian is a Graduate Research Assistant at Guangdong University of Technology, specializing in human-centered design, industrial engineering, and data-driven consumer research. His academic work focuses on quantifying the cognitive and affective dimensions of user experience with designed artifacts by integrating psychological theories such as the Theory of Consumption Values and the Technology Acceptance Model with advanced statistical modeling and innovative research instruments. He has contributed significantly to the evaluation of digital media, AI-generated models, online packaging, and the development of integrated hardware/software systems, including an AI-powered eye-tracking terminal that captures objective behavioral data in complex real-world contexts. Dr. Hannuo Tian has completed four research projects, published two peer-reviewed journal papers, and is currently pursuing two patents that reflect his emphasis on applied innovation. His research demonstrates that naturalistic virtual models with imperfections enhance consumer engagement and purchase intention, while his machine learning model for packaging evaluation has achieved a remarkable 93% accuracy in predicting consumer satisfaction. Beyond academia, he has collaborated with the Chaozhou Phoenix Dancong Tea Museum to design innovative tea packaging and create a reproducible marketing model. Through his multidisciplinary approach, Dr. Hannuo Tian aims to advance predictive frameworks and practical methodologies that bridge subjective perception with objective, data-driven insights.
Profile : ORCID
Featured Publications
Xu, L., Zou, Y., Tian, H., Childs, P. R. N., Tang, X., & Xu, J. (2025). Cognitive and affective reactions to virtual facial representations in cosmetic advertising: A comparison of idealized and naturalistic features. Electronics, 14(18), 3677.
Tian, H., Chen, K., Chen, Z., Chen, K., Wei, H., An, Y., & Zhang, Q. (2024). Research on evaluating consumer satisfaction with online tea-can packaging design model based on a logistic regression approach. In Proceedings of the International Symposium on Big Data and Artificial Intelligence (ISBDAI), 174-179. ACM.