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.

Mehnaz Tabassum | Computer Science and Artificial Intelligence | Women Researcher Award

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Dr. Mehnaz Tabassum | Computer Science and Artificial Intelligence | Women Researcher Award

University of Sydney | Australia

Dr. Mehnaz Tabassum is an accomplished researcher in Computational Neurosurgery and Health Innovation, with core expertise in medical image analysis, artificial intelligence, and brain tumor diagnostics. Her research integrates deep learning, radiomics, and neuroimaging to enhance the precision of tumor segmentation, classification, and recurrence prediction in neuro-oncology. Her scholarly contributions include 14 Scopus-indexed publications, with a total of 87 citations and an h-index of 4 (Scopus metrics). She has published in prestigious journals such as Cancers, European Radiology, and Neuro-Oncology Advances, and has presented her findings at leading international conferences including IEEE EMBC and IEEE ISBI. Dr. Mehnaz Tabassum’s recent research explores cross-modality medical image synthesis, MRI-to-PET generation using diffusion and GAN-based models, and meta transfer learning for brain tumor segmentation. Her innovative work advances computational solutions for precision medicine and AI-assisted neuroimaging. She has received multiple distinctions, including the Pro-Vice Chancellor’s Research Excellence Scholarship and the Henry Sutton Postgraduate Research Scholarship, alongside a Best Paper Award for excellence in scientific contribution. Her interdisciplinary research continues to impact the fields of AI-driven diagnostics, eye-tracking in medical imaging, and computational modeling for neurosurgical innovation, reflecting her commitment to advancing data-driven healthcare and translational neuroscience.

Profiles: Scopus | Google Scholar | ORCID | ResearchGate | Staff Page

Featured Publications

  • Tabassum, M., Suman, A. A., Suero Molina, E., Pan, E., Di Ieva, A., & Liu, S. (2023). Radiomics and machine learning in brain tumors and their habitat: A systematic review. Cancers, 15(8), Article 2034. https://doi.org/10.3390/cancers15082034

  • Ghose, P., Alavi, M., Tabassum, M., Ashraf Uddin, M., Biswas, M., Mahbub, K., … & Hassan, M. (2022). Detecting COVID-19 infection status from chest X-ray and CT scan via single transfer learning-driven approach. Frontiers in Genetics, 13, 980338. https://doi.org/10.3389/fgene.2022.980338

  • Moradizeyveh, S., Tabassum, M., Liu, S., Newport, R. A., Beheshti, A., & Di Ieva, A. (2024). When eye-tracking meets machine learning: A systematic review on applications in medical image analysis. arXiv preprint arXiv:2403.07834. https://arxiv.org/abs/2403.07834

  • Tabassum, M., Suman, A. A., Russo, C., Di Ieva, A., & Liu, S. (2023). A deep learning framework for skull stripping in brain MRI. Neurocomputing (Under review).

  • Afrin, F., Al-Amin, M., & Tabassum, M. (2015). Comparative performance of using PCA with K-means and fuzzy C means clustering for customer segmentation. International Journal of Scientific and Technology Research, 4(8), 70–74.

Dong Yang | Technologies | Best Researcher Award

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Prof. Dong Yang | Technologies | Best Researcher Award

Dalian Institute of Chemical Physics Chinese Academy of Sciences | China

Dong Yang is currently a professor at the Dalian Institute of Chemical Physics, Chinese Academy of Sciences. He also serves as the Deputy Director of the State Key Laboratory of Photoelectric Conversion and Utilization of Solar Energy. His research focuses on advancing solar energy technologies, particularly in perovskite photovoltaics and renewable energy applications.

Profile👤

Google Scholar

Strengths for the Awards✨

  • Extensive Research Experience – Professor Dong Yang has a well-rounded academic and research background, spanning China and the United States, with positions at Dalian Institute of Chemical Physics (CAS), Virginia Tech, and Pennsylvania State University.
  • Leadership & Innovation – As a Deputy Director of a State Key Laboratory, he plays a pivotal role in advancing solar energy research, which is highly impactful in the field of sustainable energy.
  • Cutting-Edge Research – His work in perovskite photovoltaics, flexible electronics, tandem solar cells, and renewable energy harvesters is at the forefront of energy research, addressing critical global challenges.
  • Industrial Applications – His research is not just theoretical but has strong potential for real-world applications, bridging the gap between academia and industry.
  • International Collaborations – Having worked in China and the United States, he brings a global perspective to research, fostering international partnerships.

🎓 Education

Dong Yang earned his Ph.D. in Physical Chemistry from the Dalian Institute of Chemical Physics in 2014. His academic journey has been instrumental in shaping his expertise in solar energy conversion and flexible electronics.

🏆 Experience

Following his Ph.D., Dr. Yang expanded his research through postdoctoral positions at Shaanxi Normal University in China and Virginia Tech in the United States. From 2018 to 2022, he served as an Assistant Research Professor at Pennsylvania State University, contributing significantly to solar cell innovation. Currently, he leads a research group specializing in next-generation photovoltaics and energy-harvesting technologies.

🔬 Research Interests On Technologies

Dr. Yang’s research interests include perovskite photovoltaics, flexible electronics, tandem solar cells, and renewable energy devices. His work aims to enhance the efficiency, stability, and industrial scalability of solar energy solutions.

🏅 Awards

Dr. Yang has received several prestigious awards for his contributions to solar energy research. His innovations in perovskite solar cells and flexible electronics have been recognized internationally.

📚 Publications

Dr. Yang has authored numerous high-impact publications in esteemed journals. Below are some of his notable works:

  • High efficiency planar-type perovskite solar cells with negligible hysteresis using EDTA-complexed SnO2

    • Authors: D Yang, R Yang, K Wang, C Wu, X Zhu, J Feng, X Ren, G Fang, S Priya, …
    • Year: 2018
    • Citations: 1358

  • Surface optimization to eliminate hysteresis for record efficiency planar perovskite solar cells

    • Authors: D Yang, X Zhou, R Yang, Z Yang, W Yu, X Wang, C Li, SF Liu, …
    • Year: 2016
    • Citations: 993

  • Stable high efficiency two-dimensional perovskite solar cells via cesium doping

    • Authors: X Zhang, X Ren, B Liu, R Munir, X Zhu, D Yang, J Li, Y Liu, DM Smilgies, …
    • Year: 2017
    • Citations: 668

  • High efficiency flexible perovskite solar cells using superior low temperature TiO2

    • Authors: D Yang, R Yang, J Zhang, Z Yang, SF Liu, C Li
    • Year: 2015
    • Citations: 579

  • Record efficiency stable flexible perovskite solar cell using effective additive assistant strategy

    • Authors: J Feng, X Zhu, Z Yang, X Zhang, J Niu, Z Wang, S Zuo, S Priya, S Liu, …
    • Year: 2018
    • Citations: 490

  • Hysteresis‐suppressed high‐efficiency flexible perovskite solar cells using solid‐state ionic‐liquids for effective electron transport

    • Authors: D Yang, R Yang, X Ren, X Zhu, Z Yang, C Li, S Liu
    • Year: 2016
    • Citations: 436

  • 20‐mm‐Large single‐crystalline formamidinium‐perovskite wafer for mass production of integrated photodetectors

    • Authors: Y Liu, J Sun, Z Yang, D Yang, X Ren, H Xu, Z Yang, S Liu
    • Year: 2016
    • Citations: 390

  • Recent advances in flexible perovskite solar cells: fabrication and applications

    • Authors: D Yang, R Yang, S Priya, S Liu
    • Year: 2019
    • Citations: 378

  • Thinness-and shape-controlled growth for ultrathin single-crystalline perovskite wafers for mass production of superior photoelectronic devices

    • Authors: Y Liu, Y Zhang, Z Yang, D Yang, X Ren, L Pang, SF Liu
    • Year: 2016
    • Citations: 373

  • Solution-Processed Nb:SnO2 Electron Transport Layer for Efficient Planar Perovskite Solar Cells

    • Authors: X Ren, D Yang, Z Yang, J Feng, X Zhu, J Niu, Y Liu, W Zhao, SF Liu
    • Year: 2017
    • Citations: 356

🔚 Conclusion

Dr. Dong Yang is a distinguished researcher in solar energy and flexible electronics. His pioneering work continues to drive advancements in photovoltaic technology, bridging the gap between scientific discovery and industrial application.