PhD Candidate at East China University of Science and Technology, China
Dr. Yibang Zhou is a robotics researcher and doctoral candidate at East China University of Science and Technology, where his research focuses on multimodal reinforcement learning, imitation learning, and continual learning in robotic systems. He previously worked as an embedded software development engineer at Analog Devices Inc. (ADI), where he led the development of Bluetooth communication algorithms for wireless battery management systems and optimized DSP compilers. During his master’s studies under Professor Lanzhu Zhang, he specialized in deep learning algorithms for robotic visual recognition and pose estimation. Dr. Zhou holds a bachelor’s degree in process equipment and control engineering from Liaoning Shihua University. His notable publications include work on EAGA-Net for grasping detection and visual–force fusion methods for threaded fastener assembly in robotic applications.
Professional Profile:
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Summary of Suitability for Research for Best Researcher Award
Dr. Yibang Zhou exhibits remarkable potential as an emerging researcher in robotics and artificial intelligence, especially in areas like multimodal reinforcement learning, imitation learning, and continual learning. His trajectory reflects a strong fusion of theoretical innovation and industrial application.
🎓 Education
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🧠 Ph.D. (Pursuing) – East China University of Science and Technology, China
Focus: Multimodal Reinforcement Learning, Imitation Learning, and Continual Learning in Robotics
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🎓 M.Eng. – East China University of Science and Technology
Research under Prof. Zhang Lanzhu on deep learning algorithms for robotic visual recognition and pose estimation
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🏫 B.Eng. – Liaoning Shihua University
Major: Process Equipment and Control Engineering
💼 Work Experience
🏆 Achievements & Recognition
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🧪 Developed EAGA-Net, an adaptable deep learning framework for robotic grasp detection
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🤖 Pioneered robotic visual and force-based assembly methods in advanced manufacturing
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📈 Contributed to cutting-edge research in imitation learning and continuous learning for robotics
🌟 Key Highlights
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🔬 Research-driven innovator in robotic perception and intelligent systems
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📡 Practical engineering experience in real-time embedded systems and signal processing
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📊 Bridges academic AI research with real-world embedded system development
📚Publication Top Notes
EAGA-Net: a novel simulation-based grasping detection dataset and network with efficient adaptability of gripper attribute
Visual identification and pose estimation algorithms of nut tightening robot system
Research on Assembly Method of Threaded Fasteners Based on Visual and Force Information