Jing Meng | Medical image processing | Research Excellence Award

Prof. Jing Meng | Medical image processing | Research Excellence Award

Qufu Normal University | China

Prof. Jing Meng is an active researcher in medical image analysis and intelligent healthcare systems, with a primary focus on deep learning–based image segmentation, disease grading, and multimodal medical imaging. Her work addresses critical challenges in diabetic retinopathy analysis, OCT/OCTA vessel segmentation, low-dose CT denoising, and cross-domain feature fusion using advanced neural network architectures. She has authored 73 Scopus-indexed publications, receiving 814 citations and achieving an h-index of 13, reflecting sustained research impact. Her studies are published in high-quality international journals, including Science Advances, Information Fusion, Expert Systems with Applications, and Neurocomputing. Dr. Meng maintains extensive academic collaboration, evidenced by 157 co-authors, highlighting strong interdisciplinary and international engagement. Her research contributes significantly to early disease diagnosis, clinical decision support, and improved medical imaging accuracy, demonstrating clear societal and healthcare impact through the advancement of AI-driven diagnostic technologies.

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Mehdi Hosseini Chagahi | Medical Imaging | Research Excellence Award

Dr. Mehdi Hosseini Chagahi | Medical Imaging | Research Excellence Award

University of Tehran | Iran

Dr. Mehdi Hosseini Chagahi is a researcher affiliated with the University of Tehran, specializing in financial data science, artificial intelligence, and cryptocurrency market forecasting. His work focuses on advanced deep learning architectures, particularly transformer-based and multimodal fusion frameworks that integrate market data with sentiment signals for trend prediction. He has authored 2 publications, accumulating 9 citations, with an h-index of 1, reflecting emerging scholarly impact. His recent open-access publication in IEEE Access (2025) demonstrates methodological innovation in cross-attention modeling. Through interdisciplinary collaboration at the intersection of AI and fintech, his research contributes to improved decision-support systems and broader societal understanding of digital financial markets.

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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.