Prof. Dr. Li-Hong Juang | Robotics | Best Researcher Award
Prof. Dr. Li-Hong Juang , Nanjing university of information science and technology, China
Dr. Li-Hong Juang πΉπΌ is a distinguished professor at Nanjing University of Information Science and Technology, specializing in artificial intelligence π€, robotics, and computer vision π₯. With a Ph.D. in Electrical Engineering from Leicester University, UK π, Dr. Juang has over two decades of academic and industry experience, contributing to cutting-edge advancements in humanoid robotics and intelligent automation βοΈ. He has published extensively in high-impact journals π and continues to inspire innovation through his research in smart systems. Beyond academia, Dr. Juang enjoys playing badminton πΈ and actively fosters collaboration in global AI initiatives π.
Professional Profile
Suitability
Dr. Li-Hong Juang stands out as an ideal candidate for the Best Researcher Award due to his extensive contributions to artificial intelligence π€, robotics π€, and computer vision π₯. With over two decades of combined academic and industrial experience, Dr. Juang has demonstrated exceptional leadership and innovation in humanoid robotics and intelligent automation βοΈ. His prolific publication record in high-impact journals π and his global reputation as a thought leader in AI research further solidify his credentials for this prestigious honor.
Education & Experience
- π B.S. in Civil Engineering: National Chiao Tung University, Taiwan (1987β1990)
- π M.S. in Applied Mechanics: National Taiwan University, Taiwan (1991β1993)
- π Ph.D. in Electrical Engineering: Leicester University, UK (2003β2006)
- π Senior Engineer: Han-Shin Aeronautic Industry Development Co., Ltd., Taiwan (1999β2002)
- π¨βπ« Assistant Professor: National Chung-Hsing University, Taiwan (2006β2010)
- π¨βπ¬ Associate Professor: Universiti Teknologi Malaysia, Malaysia (2010β2012)
- π¨βπ« Professor: Shantou University, China (2012β2015)
- π Chair Professor: National HuaQiao University, China (2015β2018)
- π‘ Distinguished Professor: Xiamen University of Technology, China (2018β2022)
- π€ Professor: Nanjing University of Information Science and Technology, China (2023βPresent)
Professional Development
Dr. Li-Hong Juang has consistently advanced in his career through academic excellence and groundbreaking research π§ . His experience spans leadership roles across prestigious institutions in Taiwan, Malaysia, and China π. As a Chair and Distinguished Professor, he led interdisciplinary teams to innovate in humanoid robotics π€ and control systems βοΈ. Beyond teaching, Dr. Juang has played a pivotal role in integrating artificial intelligence into practical applications π―, including smart automation. His professional development reflects a commitment to lifelong learning π and fostering global collaboration π€ to address emerging technological challenges π.
Research Focus
Dr. Juangβs research centers on robotics π€, artificial intelligence π§ , and computer vision π₯, with a specific focus on humanoid robotics and intelligent control systems βοΈ. His innovative work includes creating visual navigation systems for robots, developing robust control mechanisms for motion stability, and enabling AI-driven decision-making in automation π. He integrates advanced algorithms π’ to optimize robotics applications, bridging theoretical knowledge with real-world solutions π. His research significantly impacts smart systems and paves the way for the next generation of intelligent machines π‘. Dr. Juangβs passion lies in solving complex problems through technology-driven solutions π.
Awards & Honors
- π Best Research Paper Award, Multimedia Tools and Applications (2023)
- π Excellence in Robotics Innovation, National Robotics Society, Taiwan (2020)
- π₯ Distinguished Scholar Award, Xiamen University of Technology, China (2019)
- π Outstanding Contribution to AI Research, IEEE Access (2018)
- ποΈ Best Teaching Excellence Award, Universiti Teknologi Malaysia (2011)
Publication Top notes
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βοΈ βHumanoid robots play chess using visual controlβ β Multimedia Tools and Applications , cited by 7 π.
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π€ βHumanoid robot runs up-down stairs using zero-moment with supporting polygons controlβ β Multimedia Tools and Applications , cited by 2 π.
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π§ βHumanoid robot runs maze mode using depth-first traversal algorithmβ β Multimedia Tools and Applications , cited by 2 π.
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ποΈ βHumanoid robot fetching objects using monocular vision unitβ β Multimedia Tools and Applications (2023), cited by 3 π.
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π¨ βMulti-target objects and complex color recognition model based on humanoid robotβ β Multimedia Tools and Applications , cited by 2 π.