Elzbieta Olejarczyk | Artificial Intelligence | Research Excellence Distinction Award

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Assoc. Prof. Dr. Elzbieta Olejarczyk | Artificial Intelligence | Research Excellence Distinction Award

Senior Reasearcher at Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences | Poland

Assoc. Prof. Dr. Elżbieta Olejarczyk is a leading researcher in biomedical engineering and neurophysiology, specializing in the advanced analysis of EEG signals to better understand brain function and neurological disorders. Her work focuses on nonlinear dynamics, fractal analysis, brain connectivity, and the development of computational methods for diagnosing conditions such as schizophrenia, stroke, depression, and sleep disorders. She has contributed extensively to the study of neuronal complexity, functional connectivity, and neuroelectrical biomarkers using innovative mathematical and signal-processing techniques. With highly cited publications in PLoS ONE, Frontiers in Neuroscience, Scientific Reports, and IEEE journals, she is recognized for advancing EEG-based diagnostic methodologies and improving insights into brain activity in both healthy and clinical populations.

 

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Featured Publications

Aaron Finley | Business Intelligence | Research Excellence Award

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Dr. Aaron Finley | Business Intelligence | Research Excellence Award

Assistant Professor at Macau University of Science and Technology | Macau

Dr. Aaron Finley is a researcher at the Macau University of Science and Technology, Macau, with expertise in Business Intelligence, data-driven policy analysis, and applied econometric modeling. His research focuses on the intersection of sustainability analytics, environmental economics, public health modeling, and advanced statistical methodologies. Dr. Finley has made significant scholarly contributions in evaluating carbon pricing instruments and their effectiveness in reducing emissions across major Asian economies, providing evidence-based insights for climate policy optimization. His work on environmental, social, and governance (ESG) factors in relation to business environments demonstrates the practical application of multivariate analysis techniques such as canonical correlation analysis in regional economic systems.

In addition to sustainability and economic modeling, Dr. Finley’s interdisciplinary research extends into public health analytics, where he applies predictive modeling, diffusion theory, and cost-effectiveness analysis to pandemic response strategies, vaccination behaviors, and lung cancer screening programs in Asia. His studies published in BMC Medicine, Journal of Thoracic Disease, Sustainable Futures, and Sustainability highlight his ability to translate complex data into actionable policy insights. Through the integration of business intelligence frameworks with health and environmental datasets, Dr. Finley’s research supports informed decision-making in government, healthcare, and sustainability-focused institutions. His growing citation impact reflects the relevance and applicability of his work across multiple high-impact domains.

Profiles: Scopus | Google Scholar

Featured Publications

  • Finley, A., He, W., Huang, H., & Hon, C. (2024). Analyzing the effectiveness of carbon pricing instruments in reducing carbon emissions in major Asian economies. Sustainability, 16(23), 10542.
    Citation Count: 5

  • Finley, A., He, W., Huang, H., & Hon, C. (2025). A canonical correlation analysis on the relation of environmental, social, governance (ESG) on business environment (paying taxes) in South China. Sustainable Futures, 10, 101369.

  • Zhang, X., Shi, W., Liu, Z., Finley, A., Cen, K., Xie, Z., Yang, P., Li, H., & Leong, U. (2025). Adaptive Fourier decomposition analysis of different pandemic stages in South Korean cities: Policies and trends. Journal of Thoracic Disease, 17(6), 3516–3531.

  • Zhang, T., Wang, Y., Chen, X., Yang, X., Zhang, L., Bazzi, N., Bai, L., & Finley, A. (2025). Cost-effectiveness of risk model-based lung cancer screening in smokers and nonsmokers in China. BMC Medicine, 23(1), 315.

  • He, W., Wu, J., Chen, C. H., Finley, A., Wang, H., Huang, H., Ng, C., & Chui, T. (2025). Predicting COVID-19 vaccination timing by integrating the theory of planned behavior and the diffusion of innovations: A cross-sectional survey in Macao, China. Journal of Thoracic Disease, 17(5), 2813.

Danheng Gao | Deep Learning | Research Excellence Award

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Prof. Dr. Danheng Gao | Deep Learning | Research Excellence Award

Associate Researcher at Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences | China

Prof. Dr. Danheng Gao is a distinguished researcher at the Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, China, specializing in deep learning and its integration with advanced optical and photonic systems. His research bridges the disciplines of machine learning, surface-enhanced Raman spectroscopy (SERS), nonlinear optics, and ultrafast photonics, with a strong emphasis on intelligent data-driven strategies for real-world analytical applications. Prof. Gao has made notable contributions to the development of rapid identification and sensing technologies by combining artificial intelligence with spectroscopic techniques, significantly enhancing accuracy, speed, and automation in chemical and food analysis. His work in ultrafast photonics further explores the convergence of nonlinear optical phenomena with intelligent control systems, enabling breakthroughs in high-speed optical signal processing and precision measurement. Through high-impact publications in leading journals such as Food Chemistry, his research demonstrates strong interdisciplinary value across photonics, artificial intelligence, and applied chemistry. With growing citation impact, Prof. Gao is recognized for advancing intelligent optical sensing, machine-learning-driven spectroscopy, and next-generation photonic technologies.

Profile: Scopus

Featured Publications

  1. Gao, D., et al. (2025). A rapid wine brand identification method based on the joint application of SERS and machine learning techniques.

  2. Gao, D., et al. (2025). Advancements in ultrafast photonics: Confluence of nonlinear optics and intelligent strategies.
    Citation Count: 6

Libo Zhou | Digital Implantology | Research Excellence Award

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Dr. Libo Zhou | Digital Implantology | Research Excellence Award

Associate Chief Physician at Jiamusi University Affiliated Stomatological Hospital | China

Dr. Libo Zhou is a highly respected specialist in digital implantology whose career reflects a strong commitment to advancing dental technology, clinical innovation, and interdisciplinary collaboration. Recognized as an influential figure in the integration of robotics within oral implantology, he has significantly contributed to the development, refinement, and clinical application of robotic surgical systems, demonstrating exceptional expertise in guiding complex digital workflows and precision-based implant procedures. His leadership in pioneering robotic full-arch implant interventions and expanding the use of dynamic navigation has played a vital role in elevating clinical standards and shaping the future of technologically enhanced dental care. As an academic leader and research mentor, he fosters a culture of scientific inquiry, guiding projects that explore advanced imaging techniques, digital planning methodologies, and innovations in automated surgical guidance. His research portfolio includes numerous peer-reviewed publications in reputable indexed journals, reflecting a strong focus on improving procedural accuracy, enhancing patient outcomes, and addressing key engineering challenges in medical-dental integration. He has also contributed to national and regional advancements through patents, collaborative multidisciplinary initiatives, and active participation in professional committees dedicated to implantology and medical-engineering innovation. His work has earned recognition from scientific communities for excellence in research and contributions to clinical practice, further establishing his influence in transforming traditional approaches to implant dentistry. With a steadfast vision for the future of digital healthcare, he continues to drive translational research, promote industry-academia partnerships, and support the evolution of intelligent surgical systems that bridge technological capability with clinical expertise. His professional journey reflects a dedication not only to personal advancement but also to elevating the standards of practice, education, and innovation within the broader field of oral implantology.

Profiles: Scopus | ORCID

Featured Publications

Zhao, W., Teng, W., Su, Y., & Zhou, L. (2024). Accuracy of dental implant surgery with freehand, static computer-aided, dynamic computer-aided, and robotic computer-aided implant systems: An in vitro study. The Journal of Prosthetic Dentistry.

Zhou, L., Wu, F., Wang, J., Zhao, Y., Wu, G., & Su, Y. (2024). Effects of endoplasmic reticulum stress on chondrocyte apoptosis via the PI3K/AKT signaling pathway. Tissue and Cell.

Zhou, L., Teng, W., Li, X., & Su, Y. (2023). Accuracy of an optical robotic computer-aided implant system and the trueness of virtual techniques for measuring robot accuracy evaluated with a coordinate measuring machine in vitro. The Journal of Prosthetic Dentistry.

Ma, R., Liu, Q., Zhou, L., & Wang, L. (2023). High porosity 3D printed titanium mesh allows better bone regeneration. BMC Oral Health.

Zhou, L., Chen, D., Liu, P., Chen, L., & Su, Y. (2022). miR-132-3p participates in the pathological mechanism of temporomandibular joint osteoarthritis by targeting PTEN. Archives of Oral Biology.