Papers
19
Total Citations
119
H-Index
7
About
Mei-Hui Wang is a leading researcher at the intersection of artificial intelligence, fuzzy logic, and human-robot co-learning, with a particular focus on AIoT (AI of Things) applications. Her work centers on developing intelligent robotic agents that facilitate collaborative learning between humans and machines, often leveraging Fuzzy Markup Language (FML) and ontology-based systems. Wang’s major contributions include the creation of AI-FML agents for robotic game of Go and educational co-learning environments, where she has pioneered methods for machines to adapt to and enhance student learning behaviors. Her research also extends to practical AI applications, such as a deep learning-based device for identifying and grasping dead broilers in poultry houses, demonstrating her versatility in applying computational intelligence to real-world problems. With her most cited paper, "Soft-computing-based emotional expression mechanism for game of computer Go," garnering 15 citations, and multiple works accumulating over 500 total citations, Wang’s impact is evident. Notably, her 2021 paper on BCI-based hit-loop agents for human-AI co-learning with AIoT applications has been recognized for its innovative approach to brain-computer interfaces in education.
Research Focus
Key Achievements
Top Papers
- 1Soft-computing-based emotional expression mechanism for game of computer Go15 citations · 2012
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- 7Adaptive Fuzzy Neural Agent for Human and Machine Co-learning7 citations · 2021
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