Yinfeng Yang | Artificial Intelligence |Young Scientist Award

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Assoc. Prof. Dr. Yinfeng Yang | Artificial Intelligence | Young Scientist Award

Anhui University of Chinese Medicine | China

Assoc. Prof. Dr. Yinfeng Yang is an Associate Professor and emerging research leader at the intersection of artificial intelligence and traditional Chinese medicine, with a strong focus on biomedical big data analytics and AI-driven drug discovery. With a publication record of 45 documents and a citation impact exceeding 5,738 citations from 5,599 citing documents, alongside an h-index of 18, her research demonstrates significant international influence. Her work integrates bioinformatics, machine learning, molecular simulation, and systems biology to uncover key biomarkers, elucidate disease mechanisms, and accelerate the development of innovative therapeutic strategies. She has made notable contributions to multi-omics data mining, virtual screening, quantitative structure–activity relationship modeling, and mechanistic analysis of natural products and traditional prescriptions, particularly in oncology, immunology, cardiovascular disorders, and neurological diseases. Her research advances include AI-powered ADMET prediction, graph neural network–based drug-target discovery, and multiscale modeling of herbal medicine mechanisms. She has authored more than sixty publications, including first- and corresponding-author papers in high-impact journals such as Journal of Advanced Research, Phytomedicine, Drug Discovery Today, International Journal of Surgery, and ACS Omega, contributing influential and highly cited work. In addition to her scientific output, she has edited scholarly works, holds an authorized patent, and has received provincial recognition for scientific achievements. She also serves on editorial boards and contributes extensively as a reviewer for numerous international journals across pharmacology, bioinformatics, natural product research, and integrative medicine. Her expertise spans molecular dynamics, docking, high-throughput virtual screening, AI algorithms, multi-omics integration, and experimental pharmacology, positioning her at the forefront of intelligent medicine and translational research in traditional Chinese medicine.

Featured Publications

  • Fan, N. N., Chen, J., Wang, J. H., Chen, Z. S., & Yang, Y. F. (2025). Bridging data and drug development: Machine learning approaches for next-generation ADMET prediction. Drug Discovery Today, Article 104487.

  • Han, Z. J., Liu, Q. W., Yang, J. H., Wang, X. Y., Song, W. C., Wang, J. H., & Yang, Y. F. (2025). Exploration of the mechanism of Ginkgo biloba leaves targeted angiogenesis against gastric cancer. ACS Omega, 10, 40460–40476.

  • Yang, P. Z., Wang, X. Y., Yang, J. H., Yan, B. B., Sheng, H. Y., Li, Y., Yang, Y. F., & Wang, J. H. (2025). AI-driven multiscale study on the mechanism of Polygonati Rhizoma in regulating immune function in STAD. ACS Omega, 10(19), 19770–19796.

  • Li, H., Fu, S. F., Shen, P., Zhang, X., Yang, Y. F., & Guo, J. C. (2025). Mitochondrial pathways in rheumatoid arthritis: Therapeutic roles of traditional Chinese medicine and natural products. Phytomedicine, Article 157106.

  • Zhang, H. R., Xu, Q., Kan, H. X., Yang, Y. F., & Cai, Y. Q. (2025). Exploration of the clinicopathological and prognostic significance of BRCA1 in gastric cancer. Discover Oncology, 16(1), 381.

 

Sharmila More | Machine Learning | Women Researcher Award

Published on by Young Scientists Awards

Dr. Sharmila More | Machine Learning | Women Researcher Award

MIT Arts, Commerce & Science College| India

Dr. Sharmila More is an accomplished academician and researcher, currently serving as Assistant Professor in the Department of Science and Computer Science at MIT ACSC, Alandi (D), Pune. With over nine years of teaching and administrative experience, along with eight years of dedicated research expertise, she has significantly contributed to the fields of computer science, data science, cyber security, and artificial intelligence. She holds a Ph.D. in Computer Science from MATS University, Raipur, an MCA from Pune University, and a Postgraduate Diploma in Core Competency from Shivaji University. Dr. More has published 18 research papers in reputed journals, presented 20 papers at national and international conferences, and authored a book titled Solving Security Issues in Personal Identification using Fuzzy Approach and Multimodal Images. She has also guided several students in research and academic projects. Her innovations are reflected in multiple patents, including an Indian patent at the FER stage, one design patent, and granted patents in Australia, Germany, and the UK. She is actively engaged in academic committees, curriculum development under the NEP framework, and serves as an editorial board member for journals. Her professional memberships include the Computer Society of India, Indian Science Congress Association, and Soft Computing Research Society. Recognized for her excellence, she has received prestigious honors such as the International Research Excellence Awards for Outstanding Researcher and Distinguished Researcher, Best Teacher Award, and multiple prizes at research competitions. A sought-after resource person and reviewer, she has delivered expert lectures and contributed as co-supervisor and examiner for Ph.D. programs. Her citation index stands at 67, reflecting her impactful scholarship. Dr. More continues to advance interdisciplinary research in computer science, focusing on biometric systems, machine learning, cryptography, and emerging technologies, while inspiring future scholars through teaching, mentorship, and innovation.

Profile: Google Scholar

Featured Publications

More, S. S. (2025). Revolutionizing military operations: The role of deep learning with YOLO v7 in the evolution of drones. Advancements in Intelligent Systems, 33–43. Computing & Intelligent Systems.

More, S. S. (2024). Pythonic learning: Advancements and innovations in machine intelligence. International Journal of Advanced Research in Science, Communication and Technology.

More, S. S. (2023). Statistical and fuzzy inference system analysis of multimodal. Solovyov Studies ISPU.

More, S. S. (2023). Statistical and fuzzy inference system analysis of multimodal images using NMRSA. Solovyov Studies ISPU, 71(11), 122–127.

More, S., Narain, B., & Jadhav, B. T. (2023). Privacy conserving using fuzzy approach and blowfish algorithm for malicious personal identification. In Institute of Engineering (pp. xx–xx). Springer.