Associate professor at Guangxi Normal University, China
Dr. Yuanpeng Li is a distinguished Associate Professor at the School of Physical Science and Technology, Guangxi Normal University, China. Renowned for his cross-disciplinary expertise, he has significantly contributed to biomedical engineering, optical spectroscopy, and machine learning. His innovative research focuses on developing non-invasive technologies for medical diagnostics and food quality analysis. Over the past decade, Dr. Li has established a solid academic footprint through national and provincial research grants, mentoring students, and publishing impactful articles in high-ranking scientific journals. His work stands at the convergence of science and real-world application, earning him recognition as a leading researcher in spectroscopy-based diagnostics.
Profile
ORCID
Education
Dr. Li’s academic journey demonstrates a strong progression from core physics to specialized biomedical technologies. He earned his Bachelor of Science in Physics from Guangxi Normal University in 2013. Pursuing his passion for applied sciences, he obtained a Master of Science in Optics from Jinan University in 2016. He then completed his Ph.D. in Biomedical Engineering at the same institution in 2019. This comprehensive education provided him with a multidisciplinary foundation, combining physical principles with biological systems, and positioned him to make impactful contributions to healthcare and food safety technologies through optical methods.
Professional Experience
Since 2019, Dr. Li has served as an Associate Professor at Guangxi Normal University, where he leads and collaborates on national and regional research projects. His role includes supervising graduate students, fostering interdisciplinary collaborations, and advancing cutting-edge research in spectroscopy and AI-driven diagnostics. He has developed strong academic-industrial partnerships and has been instrumental in securing research funding and guiding projects from inception to publication. His responsibilities extend to teaching and curriculum design, where he ensures that students are well-trained in the latest techniques in spectroscopy, data processing, and biomedical analysis.
Research Interests
Dr. Li’s research is centered on non-invasive diagnostics, where he integrates advanced spectroscopy techniques—such as Raman and near-infrared (NIR)—with machine learning and deep learning algorithms. His work explores the detection and classification of biological and chemical changes in medical and food samples. He is especially interested in using optical methods for early disease detection, like osteoarthritis, and for analyzing food quality during processing and storage. This research has vast implications in healthcare, food safety, agriculture, and pharmaceutical industries, offering quick, accurate, and non-destructive alternatives to traditional analytical methods.
Awards
Although specific individual awards are not listed, Dr. Li has secured multiple competitive research grants at both the national and provincial levels. These grants are awarded based on the scientific merit, innovation potential, and societal relevance of his proposals. His consistent success in receiving funding speaks to the high regard in which his research is held. His collaborative roles and publication impact further underline his professional recognition within the scientific community.
Selected Publications
Dr. Li has authored over 20 peer-reviewed publications. Some of his recent and notable works include:
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“Rapid Analysis of Flaxseed Oil Quality During Frying Using Raman Spectroscopy and Peak-Area-Ratio Method”, LWT, 2024 – This article enhances food safety practices and has been cited by studies focusing on oil stability.
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“Advanced Nosema bombycis Spore Identification Using Single-Cell Raman Spectroscopy and Deep Learning”, Analytical Chemistry, 2024 – Cited in microbial detection literature, this paper offers a precise method for pathogen identification.
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“Non-Destructive Identification of Citrus Granulation Using Raman Spectroscopy and Machine Learning”, Journal of Food Science, 2024 – Recognized for its contribution to post-harvest quality control.
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“Rapid Identification of Diacylglycerol Edible Oils Using Raman Spectroscopy and ‘Oil Microscopy'”, Journal of Food Composition and Analysis, 2024 – Referenced in articles exploring lipid analysis technologies.
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“Early Osteoarthritis Diagnosis Using Near-Infrared Spectroscopy and Aquaphotomics”, Spectrochimica Acta Part A, 2023 – Frequently cited in early-diagnosis and aquaphotomics research.
These publications demonstrate the practical impact of his research across different sectors and have been cited by numerous articles focusing on spectroscopy and machine learning applications.
Conclusion
Considering Dr. Yuanpeng Li’s consistent scholarly excellence, innovation-driven research, interdisciplinary expertise, and international-level impact, he is a highly deserving candidate for the Best Researcher Award. His work not only advances academic frontiers but also addresses real-world problems with practical, data-driven solutions. Dr. Li exemplifies what the award seeks to honor—a researcher pushing boundaries, inspiring future scientists, and contributing meaningfully to science and society.