Prof. Dr. Yijui Chiu | Deep Learning | Best Innovation Award

Prof. Dr. Yijui Chiu is a distinguished professor and doctoral supervisor specializing in mechanical engineering, with research spanning vibration, rotor dynamics, digital twin technology, deep learning, biomechanics, molecular dynamics, and applications in elderly assistive devices, semiconductor wafer equipment, and renewable energy vehicles. He has demonstrated exceptional strengths in integrating theoretical, computational, and experimental approaches, evidenced by his extensive contributions to rotor system dynamics, fault detection, and coupled vibration analysis. Dr. Chiu excels in interdisciplinary research, combining machine vision, AI, and digital twin frameworks to address complex engineering challenges, including thermo-elastic rotor coupling, flexible rotor systems, and smart exoskeleton control, reflecting his deep analytical and innovative skills. His leadership in guiding 28 funded projects, both national and industry-based, has fostered cross-strait innovation collaboration and produced a prolific output of 81 publications with 723 citations and an h-index of 16, highlighting his influence in mechanical engineering and related fields. Dr. Chiu’s research skills extend to experimental mechanics, finite element analysis, intelligent system design, machine learning applications, and multi-physics modeling, enabling practical solutions for energy systems, robotics, and industrial machinery. He has also cultivated a strong record of mentorship, supervising graduate students to national awards and doctoral programs at top institutions, reflecting his commitment to academic excellence and knowledge transfer. Areas for potential growth include expanding the application of his methodologies to broader industrial digital twin implementations, integrating renewable energy systems with AI-enhanced control, and exploring more advanced human-robot interaction systems for healthcare and manufacturing. Looking forward, Dr. Chiu has significant future potential to shape smart manufacturing, predictive maintenance, and sustainable mechanical systems by leveraging his interdisciplinary expertise and collaborative networks. His innovative contributions not only advance scientific understanding but also drive practical solutions with societal, industrial, and environmental impact, making him a highly deserving candidate for awards recognizing visionary achievements in engineering research and technology development.