Posted on 06/01/202506/01/2025 by sciencefather 80 / 100 Powered by Rank Math SEO Ms. Qing Liang | Food Safety and Quality Control | Best Researcher Award College of Mechanical and Electrical Engineering at College of Mechanical and Electrical Engineering, China Qing Liang is a graduate student in Mechanical Engineering with a strong focus on food safety and quality control. His research combines non-destructive testing methods, such as dielectric spectroscopy, with machine learning to address challenges in food quality, particularly within the dairy industry. Liang has contributed to several publications in well-regarded journals, demonstrating his expertise and commitment to advancing food science. With a passion for innovation, he is working towards bridging the gap between mechanical engineering and food safety. Liang’s ongoing research positions him as a promising young researcher in the fields of engineering and food technology. Professional Profile Scopus Profile ORCID Profile Education Qing Liang is currently pursuing a postgraduate degree in Mechanical Engineering, graduating in the class of 2023. His academic journey has been marked by a strong foundation in engineering principles, alongside specialized focus areas such as non-destructive testing and machine learning applications in food safety and quality control. Liang’s academic training has equipped him with advanced problem-solving skills, research methodologies, and a deep understanding of both mechanical engineering and food science. His rigorous coursework and research have allowed him to contribute to innovative solutions in food safety, further solidifying his expertise in the intersection of engineering and food technology. Professional Experience Qing Liang currently works as a graduate student researcher at the Xinjiang Production and Construction Corps Key Laboratory of Utilization and Equipment of Special Agricultural and Forestry Products in Southern Xinjiang, China. In this role, he focuses on developing and testing innovative solutions for food safety and quality control, particularly within the dairy industry. His professional experience spans non-destructive testing, machine learning, and food safety methodologies. Qing has contributed to various projects that explore advanced techniques like dielectric spectroscopy to improve the quality and safety of agricultural products. Through his research, he actively bridges mechanical engineering and food science to address industry challenges. Research Interests Qing Liang’s research interests lie at the intersection of mechanical engineering, food safety, and machine learning. He focuses on applying non-destructive testing methods, such as dielectric spectroscopy, to enhance food quality control and safety, particularly in dairy products. His work explores innovative approaches to detecting adulteration, protein content, and other key factors influencing food safety. Liang is also passionate about integrating machine learning techniques with traditional testing methods to improve accuracy and efficiency in food quality assessment. By combining engineering principles with food science, his research aims to develop sustainable solutions that address current challenges in food safety and quality control. Awards and Honors Although Qing Liang is still early in his career, his research has already earned recognition in academic circles. He has authored multiple research papers in high-impact journals, such as the Journal of Food Science and Foods, focusing on innovative methods for food safety and quality control. Liang’s work has garnered citations, reflecting its growing influence in the field. His contributions to advancing non-destructive testing and machine learning applications in food science showcase his potential for future awards and honors. As a promising researcher, Liang’s continuous commitment to innovation positions him for further accolades in his field. Conclusion While LiangQing has demonstrated promise as an emerging researcher with a focus on innovative topics, they may currently lack the breadth and depth of achievements typically expected for the Best Researcher Award. Strengthening their profile with completed high-impact research, industry collaborations, and leadership roles in the scientific community would make them a stronger contender for future awards. Publications Top Noted Non-destructive detection of water adulteration level in fresh milk based on combination of dielectric spectrum technology and machine learning method Authors: Liang, Q., Liu, Y., Zhang, H., Xia, Y., Li, S. Journal: Journal of Food Composition and Analysis Year: 2024 Volume: 136 Article Number: 106807 Citations: 0 The Study on Nondestructive Detection Methods for Internal Quality of Korla Fragrant Pears Based on Near-Infrared Spectroscopy and Machine Learning Authors: Che, J., Liang, Q., Xia, Y., Zhang, H., Lan, H. Journal: Foods Year: 2024 Volume: 13(21) Article Number: 3522 Citations: 3 Dielectric spectroscopy technology combined with machine learning methods for nondestructive detection of protein content in fresh milk Authors: Liang, Q., Liu, Y., Zhang, H., Che, J., Guo, J. Journal: Journal of Food Science Year: 2024 Volume: 89(11) Pages: 7791–7802 Citations: 0 Non-Destructive Testing of the Internal Quality of Korla Fragrant Pears Based on Dielectric Properties Authors: Tang, Y., Zhang, H., Liang, Q., Che, J., Liu, Y. Journal: Horticulturae Year: 2024 Volume: 10(6) Article Number: 572 Citations: 1 Qing Liang | Food Safety and Quality Control | Best Researcher Award