Papers
8
Total Citations
122
H-Index
5
About
Man Hao is a pioneering researcher in human-robot interaction, with a focus on developing emotionally intelligent and proactive service robots. His work bridges affective computing and robotics, particularly through speech and facial emotion recognition—his 2021 paper on speech emotion recognition using formant characteristics and phoneme type convergence has garnered 63 citations, while his 2019 work combining 2D Gabor filters and Local Binary Patterns for facial expression recognition has been cited 20 times. Hao’s major contribution lies in creating initiative service models that enable robots to anticipate human needs, such as his drinking service robot framework that uses fuzzy analytical hierarchy process and context intention inference (10 citations) to determine when users require hydration. He has also advanced emotion regulation in robots through multi-objective weighted reinforcement learning (8 citations), allowing machines to adapt their behavior to improve user well-being. His notable achievements include developing methods for recognizing sleepiness and analyzing user demand via Takagi-Sugeno fuzzy models, all aimed at making service robots more intuitive and responsive. With over 120 total citations, Hao’s work is foundational for next-generation robots that can understand and respond to human emotional and physical states.
Research Focus
Key Achievements
Top Papers
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- 3Proposal of initiative service model for service robot11 citations · 2017
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