Tsung-Ren Huang
Papers
6
Total Citations
48
H-Index
5
About
Tsung-Ren Huang is a pioneering researcher at the intersection of social robotics, cognitive science, and mental health assessment. His primary research areas include human-robot interaction, cognitive decline detection, and computational psychometrics. Huang’s major contributions lie in developing non-invasive, conversational AI systems that can evaluate cognitive and psychological states in older adults. His 2021 study on identifying mild cognitive impairment through human-robot interactions (15 citations) demonstrated how robotic platforms can serve as early screening tools for dementia risk. He further advanced this work by showing that personal resilience can be estimated from heart rate variability and paralinguistic features during robot conversations (10 citations), and that social robots can effectively evaluate attention states in aging populations (8 citations). Notably, his 2023 study on the unavoidable social contagion of false memory from robots to humans (7 citations) revealed a striking finding: robots can influence human memory as powerfully as other humans, raising important ethical considerations for AI deployment. Huang’s work uniquely combines psychological assessment with robotic interaction, creating scalable, engaging tools for mental healthcare that address the growing demands of an aging global population.
Research Focus
Key Achievements
Top Papers
- 1Identifying Mild Cognitive Impairment by Using Human–Robot Interactions15 citations · 2021
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- 3Social Robots for Evaluating Attention State in Older Adults8 citations · 2021
- 4Unavoidable social contagion of false memory from robots to humans.7 citations · 2023
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