Mr. Keyi Chen | AI Advancements | Best Researcher Award

Mr. Keyi Chen | Jihua Laboratory | China

Keyi Chen is a Research Engineer at Jihua Laboratory, located in Foshan, Guangdong Province, China. He obtained his Master of Science degree in Crop Informatics from Huazhong Agricultural University in 2023. His research primarily focuses on artificial intelligence and deep learning applications in computer vision and environmental informatics. He has successfully completed three research projects and has contributed to several high-quality publications indexed in international databases such as SCI and Scopus. His Scopus citation score reflects his growing research impact, supported by a total of 38 citations across multiple publications and an h-index of 2, demonstrating steady academic recognition in his domain. He has also filed three patents, demonstrating his strong commitment to transforming innovative research ideas into practical solutions. His professional work bridges the gap between advanced AI methodologies and their application in environmental data analysis and recognition systems. One of his recent studies introduces a new computational framework designed for marine microalgae recognition, tackling the long-standing challenges of inefficiency and class imbalance in microscopic image analysis. His proposed model employs a novel multi-expert architecture combined with feature compression techniques to enhance recognition accuracy and computational efficiency. The model has been rigorously tested on complex datasets containing various marine microalgae species, establishing a new benchmark in performance evaluation and reliability. His research contributes not only to artificial intelligence but also to ecological monitoring and marine life science, offering a robust foundation for further innovation in automated species identification. With his technical expertise and analytical approach, Keyi Chen continues to advance the integration of deep learning algorithms into scientific and industrial applications. His research interests extend to intelligent data processing, image-based classification systems, and bioinformatics-driven AI models.