Hongmei Zhao

Peking University, China-Japan Friendship Hospital

Papers

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About

Hongmei Zhao is a researcher whose work bridges computer vision and biomedical robotics, with a focus on intelligent systems for safety and healthcare. Her early, highly cited research tackled the challenging problem of robust abandoned object detection, introducing a novel online learning framework that not only identified suspicious items but also analyzed their “logic owner”—a critical advancement over prior methods that lacked contextual reasoning. This work, published in 2013, has garnered 12 citations and laid a foundation for more context-aware surveillance systems. More recently, Zhao has ventured into assistive robotics, pioneering the use of ultrasound imaging to evaluate and model diaphragm displacement in real time. This innovative approach, presented in 2024, directly addresses a gap in respiratory assistive robot design by enabling quantitative assessment of a device’s impact on diaphragm mobility—a key metric for patient outcomes. By combining machine learning with biomechanical sensing, Zhao’s work exemplifies a cross-disciplinary drive to create safer public spaces and more effective medical devices. Her evolving portfolio, from detection algorithms to wearable robotic evaluation, marks her as a versatile contributor to both intelligent vision and human-centered robotics.