Aya Shirai

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Total Citations

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About

Aya Shirai is a pioneering researcher at the intersection of robotics, deep learning, and human-machine interaction. Her work focuses on creating intelligent systems that seamlessly interpret biological signals—from muscle activity to brainwaves—for practical robotic applications. In her highly cited 2021 paper on deep learning for gesture recognition using surface EMG data (12 citations), Shirai developed a novel mapping technique that enables myoelectric prosthetic hands to interpret muscle signals with unprecedented accuracy, directly improving the quality of life for amputees. That same year, she applied deep learning to environmental sustainability, proposing a robot manipulator system for automated recycling of printed circuit boards (11 citations), addressing Japan’s critical need for domestic metal recovery. Most recently, in 2023, she advanced brain-machine interfaces by optimizing EEG channels for wireless robot interaction within the Internet of Robotic Things (7 citations), dramatically improving recognition rates while reducing computational overhead. Her work consistently bridges the gap between biological signal processing and autonomous robotic control, with applications spanning assistive technology, sustainable manufacturing, and next-generation IoT systems.