Yanping Mo | Image Restoration Algorithms | Best Researcher Award

Ms. Yanping Mo | Image Restoration Algorithms | Best Researcher Award

Postgraduate Student | Xi’an University of Science and Technology | China

Ms. Yanping Mo is a researcher affiliated with the School of Communication and Information Engineering at Xi’an University of Science and Technology, China, and associated with the China Education and Research Network in Beijing. Her research primarily focuses on the intersection of computational imaging, signal processing, and optimization algorithms for image restoration and enhancement. In particular, her recent work titled “Research on plug-and-play image restoration algorithm based on dual weighted ADMM,” published in Optics & Laser Technology (December 2025), demonstrates her expertise in developing advanced optimization frameworks for image reconstruction. The study explores a dual weighted Alternating Direction Method of Multipliers (ADMM) approach that integrates plug-and-play priors to enhance the flexibility and accuracy of image restoration tasks. This approach effectively addresses common challenges in image denoising, deblurring, and super-resolution by adaptively balancing data fidelity and regularization terms. Her contribution lies in improving the convergence stability and computational efficiency of traditional ADMM-based algorithms while maintaining high-quality visual outputs. Through her collaborative work with researchers such as Wei Chen, Zhaohui Li, and Bin Fan, Mo advances the application of mathematical modeling and artificial intelligence techniques in optical and laser imaging technologies. Her research supports the broader goal of enhancing image processing methodologies for scientific imaging, remote sensing, medical imaging, and industrial inspection applications. Overall, Yanping Mo’s research reflects a strong commitment to the development of robust and intelligent algorithms that bridge theory and application in the field of computational optics and image restoration.

Profile: ORCID

Featured Publications

1. Chen, W., Mo, Y., Li, Z., & Fan, B. (2025, December). Research on plug-and-play image restoration algorithm based on dual weighted ADMM. Optics & Laser Technology, 113997.

Hongzhen Wang | HealthTech and Wearables | Women Researcher Award

Dr. Hongzhen Wang | HealthTech and Wearables | Women Researcher Award

Associate Professor at Zhejiang A&F University, China

Wang Hongzhen is an accomplished Associate Professor and Master’s Supervisor specializing in plant biochemistry and medicinal plant research. With over two decades of academic and research experience, she has focused on advancing the authenticity, classification, and cultivation of Anoectochilus roxburghii, a highly valued medicinal orchid. Her academic journey spans Shanxi University, Guizhou University, and a Ph.D. from Linnaeus University in Sweden, equipping her with a global research perspective. Currently serving at Zhejiang A&F University, she integrates traditional plant sciences with modern biotechnological tools, including hyperspectral imaging and machine learning, to address challenges in medicinal plant authenticity and health applications. Having authored more than 30 high-impact papers, led numerous provincial and national projects, and earned awards for her contributions, Wang’s research significantly contributes to the advancement of health-related technologies and the sustainable development of medicinal plant resources.

Professional Profile

Scopus

Education

Wang Hongzhen’s education reflects a solid foundation in biological sciences and plant biochemistry. She began her academic training at the College of Life Sciences, Shanxi University, where she acquired essential knowledge of genetics and plant physiology. She then pursued postgraduate studies at the Institute of Genetic Engineering and Molecular Biology, Guizhou University, focusing on genetic regulation and biochemical pathways in plants. To advance her expertise, she completed her doctoral studies at Linnaeus University, Sweden, where she conducted extensive research in plant biochemistry, molecular biology, and the physiological mechanisms underlying medicinal plants. Her education uniquely combines traditional Chinese medicine plant studies with modern molecular tools and international scientific methodologies. This broad educational background prepared her to address critical questions in plant-based healthcare and medicinal resource development. Through this journey, she gained the capacity to integrate advanced research technologies, including hyperspectral imaging and bioinformatics, into her research on medicinal plant authentication.

Experience

Wang Hongzhen has built a rich academic and research career that bridges plant biochemistry, medicinal plant cultivation, and health-related applications. She began her professional journey as a teacher at Zhejiang Forestry College, where she contributed to developing courses in biotechnology and plant sciences. After completing her Ph.D. in Sweden, she joined Zhejiang A&F University in, where she continues to serve in the Discipline of Chinese Medicine. Over her career, she has presided over or contributed to more than 14 national and provincial projects, including studies funded by the National Natural Science Foundation of China. Her project leadership includes topics such as germplasm quality evaluation, resistance mechanisms, and cultivation innovations for Anoectochilus roxburghii. Beyond academic teaching, she has actively collaborated in advancing agricultural biotechnology and integrating medicinal plant research with modern imaging and computational analysis. Her career illustrates a continuous progression toward interdisciplinary, impactful scientific contributions in HealthTech and plant sciences.

Research Focus

Wang Hongzhen’s research focuses on the intersection of plant biochemistry, computational imaging, and medicinal resource sustainability. Her primary work centers on Anoectochilus roxburghii, a rare and valuable medicinal orchid widely used in traditional medicine. She investigates quality evaluation of germplasm resources, development of high-yield and disease-resistant varieties, and protocorm-like body formation mechanisms for scalable cultivation. Recently, she has integrated hyperspectral imaging and machine learning to achieve small-sample authenticity identification and variety classification, bridging biotechnology with cutting-edge computational methods. This research ensures authenticity, prevents adulteration, and enhances traceability of medicinal plants in healthcare applications. Additionally, she has explored molecular mechanisms such as polyamine regulation, enzyme gene function, and stress resistance in medicinal species. Her work is not only fundamental for improving the pharmacological reliability of herbal resources but also future-oriented in connecting plant sciences with HealthTech innovations, including wearable biosensing and AI-based diagnostic tools.

Publication Top Note

Title: Small-Sample Authenticity Identification and Variety Classification of Anoectochilus roxburghii (Wall.) Lindl. Using Hyperspectral Imaging and Machine Learning
Authors: Wang Hongzhen.
Summary: The study combines hyperspectral imaging with machine learning to authenticate and classify A. roxburghii from small samples, offering a fast and reliable method to prevent adulteration in medicinal plants.

Conclusion

Wang Hongzhen’s research demonstrates a rare combination of depth in plant biochemistry and breadth in applying advanced computational tools such as hyperspectral imaging and machine learning to address real-world problems in medicinal plant science. Her contributions in germplasm evaluation, cultivation, and molecular regulation of Anoectochilus roxburghii are significant, impactful, and forward-looking. With further emphasis on interdisciplinary international collaboration and AI-driven translational outputs, she is highly suitable for the Women Researcher Award.