Chien-I Chang | Robotics | Research Excellence Award

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Mr. Chien-I Chang | Robotics | Research Excellence Award

National Chiayi University | Taiwan

Mr. Chien-I Chang is a robotics researcher whose work integrates intelligent systems, autonomous control, and applied computer science to advance next-generation robotic technologies. His research centers on designing adaptive robotic platforms capable of operating in dynamic, unstructured, or human-interactive environments, with a strong emphasis on sensor fusion, machine perception, and real-time decision-making. He has extensive experience developing autonomous navigation algorithms, robotic manipulation systems, and embedded architectures optimized for efficiency, stability, and scalability. His work bridges theoretical modeling with practical engineering, resulting in robotics solutions that are deployable across industrial, educational, and service-oriented settings. Through continuous exploration of mechatronic integration, computer vision, and learning-based control, he aims to enhance robot autonomy and expand practical use cases in daily life. His professional experience includes leading innovative robotics projects, mentoring teams in advanced robotic development, and transforming research outcomes into functional systems with societal impact. He is particularly interested in scalable and modular robotic designs that lower entry barriers for automation and support real-world problem solving. His research philosophy focuses on combining rigorous scientific inquiry with hands-on experimentation to accelerate the evolution of intelligent robotics. Through his academic pursuits and ongoing contributions to the robotics industry, he remains committed to advancing the performance, reliability, and accessibility of robotic technologies while fostering innovation that benefits education, industry, and broader communities.

Profile: Scopus

Featured Publication

Chang, C.-I., (2025). A low-cost autonomous outdoor robot with stabilized controller and deep-learning integrated GPS navigator under end-to-end implementation. Journal of the Chinese Institute of Engineers / Transactions of the Chinese Institute of Engineers, Series A. Advance online publication.

Huaiqu Feng | Robot | Best Researcher Award

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Dr. Huaiqu Feng | Robot | Best Researcher Award

Zhejiang University | China

Huaiqu Feng is an accomplished researcher and engineer from China with a strong academic background in agricultural mechanization engineering and automation. He completed his undergraduate studies in Automation at Hubei Normal University, where he built a solid foundation in control theory, intelligent systems, signal processing, and electronics. He then pursued a master’s degree in Agricultural Mechanization Engineering at Northeast Agricultural University, focusing on areas such as image processing, deep learning, computer vision, and advanced agricultural mechanics. His research interests center on the integration of intelligent control systems and machine vision technologies to improve agricultural equipment and automation. He has contributed to several scientific papers submitted to international SCI-indexed journals, addressing topics such as deep learning-based corn kernel selection and targeted pesticide spraying platforms. His research output includes 20 documents with 431 citations by 376 documents, reflecting his growing impact in the scientific community. His innovative work is also demonstrated through multiple patents for agricultural machinery and software copyrights related to neural network-based prediction and measurement systems. He has received various scholarships and awards for academic excellence and innovation, including recognition in national competitions such as the “Blue Bridge Cup” and the “Huawei Cup.” Beyond his technical achievements, he has demonstrated leadership through active involvement in student organizations, academic committees, and innovation programs, leading teams in robotics and intelligent control system design. His multidisciplinary expertise bridges automation, machine learning, and agricultural engineering, contributing to the advancement of smart farming technologies.

Profile: Scopus

Featured Publications

Feng, Huaiqu (2025). TD-CFD-DPM coupled method for multi-objective optimization of collision pollination parameters in hybrid rice seed production. Smart Agricultural Technology.

Feng, Huaiqu (2025). nUGV-1UAV robot swarms: Low-altitude remote sensing-based decentralized planning framework in-field environments. ISPRS Journal of Photogrammetry and Remote Sensing.