Yinfeng Yang | Computer Science and Artificial Intelligence | Best Researcher Award

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Assist. Prof. Dr. Yinfeng Yang | Computer Science and Artificial Intelligence | Best Researcher Award

Anhui University of Chinese Medicine | China

Dr. Yinfeng Yang is a distinguished researcher specializing in artificial intelligence, bioinformatics, and traditional Chinese medicine (TCM), with a strong emphasis on AI-enabled drug discovery and biomedical big data analysis. Her work integrates multi-omics analytics, computational modeling, and machine learning to uncover disease biomarkers, elucidate therapeutic mechanisms, and accelerate the discovery of bioactive compounds from natural medicines. Dr. Yinfeng Yang has made significant contributions to AI-assisted drug discovery (AIDD), advancing methodologies in molecular docking, molecular dynamics simulations, high-throughput virtual screening, and quantitative structure–activity relationship modeling. She has authored 44 Scopus-indexed publications, accumulating 5,663 citations across 5,524 documents, supported by a Scopus h-index of 18, underscoring her impact in computational biology and integrative medicine research. Her studies, published in leading journals such as Journal of Advanced Research, Phytomedicine, ACS Omega, Drug Discovery Today, and Current Medicinal Chemistry, span diverse topics including cancer prognosis modeling, multi-scale mechanisms of herbal medicine, ADMET prediction frameworks, and the therapeutic potential of Ginkgo biloba in oncology and neurological disorders. Dr. Yinfeng Yang has led and contributed to numerous scientific research projects focused on TCM modernization, biomedical intelligence, and compound drug discovery. She also plays an active role in scholarly publishing as an editorial board member for journals such as PLOS ONE and Journal of Hebei Medical University, and serves as a recognized reviewer for more than 30 international journals, including Nature Communications, Phytomedicine, ACS Omega, and Journal of Ethnopharmacology. Her research excellence continues to advance innovation in AI-driven precision medicine and the global understanding of natural-product-based therapeutics.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

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

  • Han, Z., Liu, Q., Yang, J., Wang, X., Song, W., Wang, J., & Yang, Y. (2025). Exploration of the mechanism of Ginkgo biloba leaves targeted angiogenesis against gastric cancer. ACS Omega, 10(35), 40460–40476.

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

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

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

Bojiang Yin | Engineering | Best Researcher Award

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Mr. Bojiang Yin | Engineering | Best Researcher Award

School of Petrochemical Engineering, Lanzhou University of Technology | China

Mr. Bojiang Yin’s research primarily focuses on the fundamental and applied aspects of special valve design and process systems, with an emphasis on structural parameter optimization, reliability engineering, and multi-physics coupling dynamics. His work addresses critical challenges in extreme operating environments, such as ultra-low temperature liquid hydrogen systems, by developing innovative sealing structures and evaluating their performance using advanced computational approaches. He has employed techniques including thermo-mechanical coupling, sensitivity analysis, high-precision RBF surrogate modeling, and NSGA-II optimization to achieve reliable bidirectional sealing under cryogenic conditions. Bojiang has published in high-impact journals like Scientific Reports, contributing to the scientific understanding of valve mechanics and optimization methodologies. He has collaborated with the National Natural Science Foundation of China, the Double First-Class Key Program of Gansu Province, and other regional technology programs, bridging academic research with practical industry applications. His contributions extend to consultancy projects, product development, and providing references for the design of advanced butterfly valves, positioning him as an emerging researcher in valve innovation and cryogenic system reliability.

Profile: ORCID

Featured Publications

Li, S., Yin, B., Wei, C., Li, W., & Yang, L. (2025). Structural analysis and multi-objective optimization of sealing structure for cryogenic liquid hydrogen triple-offset butterfly valve. Scientific Reports, 15, Article 20095. https://doi.org/10.1038/s41598-025-20095-6