Papers
60
Total Citations
1,275
H-Index
17
About
Jinhua She is a distinguished researcher whose work spans human-robot interaction, intelligent emotion recognition, control engineering, and underactuated robotic systems. She has made pioneering contributions to the development of sophisticated machine learning architectures designed to enable robots to understand and respond to human emotional states. Her most celebrated work includes a deep sparse autoencoder network for facial emotion recognition (198 citations) and a two-layer fuzzy multiple random forest framework for speech emotion recognition (193 citations), both of which have significantly advanced affective computing in human-robot interaction contexts. She further extended this research through innovative fuzzy support vector regression models, enabling dynamic, real-time emotional intention understanding in multi-robot systems. Beyond emotion-aware robotics, She has contributed meaningfully to mobile robot control, demonstrating robust adaptive tracking techniques, and to underactuated robotic systems, where her energy-based and posture-combined control strategies for gymnast and Pendubot robots have garnered notable scholarly attention. Her early work on Internet-based control engineering education (65 citations) also reflects a commitment to accessible, technology-enhanced learning. Collectively, her publications have accumulated hundreds of citations, underscoring her broad and lasting influence across intelligent robotics, control theory, and engineering education.
Research Focus
Key Achievements
Top Papers
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- 3Robust adaptive tracking control of wheeled mobile robot106 citations · 2016
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- 5Internet-Based Teaching and Experiment System for Control Engineering Course65 citations · 2008
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- 10New analytical results of energy-based swing-up control for the Pendubot35 citations · 2013