Anastasia Feofilova | Engineering | Best Researcher Award

Assoc. Prof. Dr. Anastasia Feofilova | Engineering | Best Researcher Award

Don State Technical University | Russia

Assoc. Prof. Dr. Anastasia Feofilova is an accomplished researcher in intelligent transport systems, traffic flow prediction, and urban mobility engineering. Her work focuses on advanced AI-driven traffic modeling, including hybrid CNN–LSTM/GRU architectures, attention mechanisms, geoinformation systems in transport logistics, cooperative intelligent transport systems (C-V2X), and the impacts of autonomous vehicles on road network efficiency. She has contributed to peer-reviewed journals and international book chapters, with research published in reputable outlets such as Smart Cities, Sensors, Applied and Computational Engineering, and E3S Web of Conferences. With an established Scopus profile, consistent citation impact, interdisciplinary collaborations, and contributions to software development and educational-methodological outputs, her research demonstrates both scientific rigor and applied societal relevance, particularly in smart city development and road safety enhancement.

Citation Metrics (Scopus)

40

30

20

10

0

Citations
36

Documents
7

h-index
4

■ Citations
■ Documents
■ h-index

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Featured Publications

Abdulaziz Almaktoom | Engineering | Best Researcher Award

Assoc. Prof. Dr. Abdulaziz Almaktoom | Engineering | Best Researcher Award

Effat University | Saudi Arabia

Assoc. Prof. Dr. Abdulaziz Almaktoom, is a distinguished scholar and leader in Operations and Supply Chain Management, serving as Associate Professor and Chair of the Business Administration Department. With 39 publications, 275 citations, and an h-index of 10, he is recognized among the top 20 scientists in Decision Science and Operations Management in Saudi Arabia. His expertise spans operations management, project management, data analytics, industrial ergonomics, lean and six sigma, quality assurance, risk management, and applied statistics. He has pioneered innovative curriculum development, establishing specialized programs and securing full accreditation from NCAAA and AACSB. Renowned for mentoring students, leading cross-functional teams, and driving industry collaborations, he combines research excellence with impactful teaching. His strategic vision has enhanced academic standards, tripled student enrollment, and supported students’ success, while his consultancy and professional certifications underscore his commitment to advancing operational efficiency, research innovation, and applied solutions across industry and academia.

Profile: Scopus | Orcid | Google Scholar

Featured Publications

Merabet, A., Saighi, A., Saad, H., Ferradji, M. A., Laboudi, Z., & Almaktoom, A. T. (2025). AI for colon cancer: A focus on classification, detection, and predictive modeling. International Journal of Medical Informatics, 106115.

Almaktoom, A. T., & Yusuf, N. (2025). Optimizing forecasting techniques for cost-effective procurement of controlled medications in Saudi Arabia’s healthcare system. International Journal of Pharmaceutical and Healthcare Marketing.

Almaktoom, A. T. (2025). Resilience modeling of mobile service for quality assurance. Operations Management Research, 18(1), 182–194.

Sasikumar, A., Ravi, L., Devarajan, M., Selvalakshmi, A., & Almaktoom, A. T. (2024). Corrections to “Blockchain-Assisted Hierarchical Attribute-Based Encryption Scheme for Secure Information Sharing in Industrial Internet of Things.” IEEE Access, 12, 163197–163197.

Bezoui, M., Kermali, A., Bounceur, A., Qaisar, S. M., & Almaktoom, A. T. (2024). Deep reinforcement learning for multiobjective scheduling in Industry 5.0 reconfigurable manufacturing systems. In Machine Learning for Networking: 6th International Conference, MLN 2023

Qing Lyu | Engineering | Best Researcher Award

Dr. Qing Lyu | Engineering | Best Researcher Award

Wake Forest University School of Medicine | United States

Dr. Qing Lyu is a highly accomplished researcher in biomedical engineering and AI-driven medical imaging, with a strong track record of innovation and scholarly impact. He holds a B.S. and M.S. in Biomedical Engineering from Shanghai Jiao Tong University and a Ph.D. from Rensselaer Polytechnic Institute, where his dissertation focused on deep neural networks for MRI applications. Currently, he serves as Assistant Professor in Radiology and Adjunct Assistant Professor in Biomedical Engineering at Wake Forest University School of Medicine. Dr. Qing Lyu’s research spans MRI and CT super-resolution, multimodal radiomics, deep learning for disease prediction, and AI-based clinical translation. His scholarly output includes 14 documents indexed in Scopus, accruing 594 citations and an h-index of 8, reflecting both quality and influence. He holds multiple patents, has secured competitive grants, and serves on editorial boards while reviewing for top journals and conferences, underscoring his leadership in advancing biomedical imaging, AI, and translational medical research.

Profile: Scopus | Google Scholar

Featured Publications

Lyu, Q., Tan, J., Zapadka, M. E., Ponnatapura, J., Niu, C., Myers, K. J., Wang, G., … & Whitlow, C. (2023). Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: Results, limitations, and potential. Visual Computing for Industry, Biomedicine, and Art, 6(1), 9.

Lyu, Q., Shan, H., Steber, C., Helis, C., Whitlow, C., Chan, M., & Wang, G. (2020). Multi-contrast super-resolution MRI through a progressive network. IEEE Transactions on Medical Imaging, 39(9), 2738–2749.

Lyu, Q., Shan, H., & Wang, G. (2020). MRI super-resolution with ensemble learning and complementary priors. IEEE Transactions on Computational Imaging, 6, 615–624.

Lyu, Q., & Wang, G. (2022). Conversion between CT and MRI images using diffusion and score-matching models. arXiv preprint arXiv:2209.12104.

Niu, C., Li, M., Fan, F., Wu, W., Guo, X., Lyu, Q., & Wang, G. (2022). Noise suppression with similarity-based self-supervised deep learning. IEEE Transactions on Medical Imaging, 42(6), 1590–1602.

Yuh-Ming Ferng | Engineering | Best Researcher Award

Prof. Yuh-Ming Ferng | Engineering | Best Researcher Award

National Tsing Hua University | Taiwan

Prof. Yuh-Ming Ferng, a distinguished Professor at the Department of Engineering and System Science, Institute of Nuclear Engineering and Science, National Tsing Hua University (NTHU), has made significant contributions to nuclear engineering through his extensive research and academic leadership. He earned his B.S. and Ph.D. in Nuclear Engineering from NTHU, where his doctoral thesis focused on the numerical simulation of the rewetting process. With a professional career spanning over three decades, Prof. Yuh-Ming Ferng has held roles as Assistant, Associate, and Full Professor at NTHU, alongside senior research positions at its Nuclear Science and Technology Development Center and the Center for Energy and Environmental Research, as well as the Institute of Nuclear Energy Research. His research expertise covers nuclear reactor safety, severe accident analysis, CFD turbulence modeling, two-phase flow, thermal management, fuel cell simulation, and renewable energy systems. With 2,470 citations, 168 documents, and an h-index of 30, he is a highly impactful researcher in his field.

Profile: Scopus

Featured Publications

  • Ferng, Y.-M., & co-authors. (2026). Determining minimum site area for deep geological repository of spent fuels using thermal simulations. Annals of Nuclear Energy. Advance online publication.

  • Ferng, Y.-M., & co-authors. (2025). Thermal management design for the Be target of an accelerator-based boron neutron capture therapy system using numerical simulations with boiling heat transfer models. Processes. Advance online publication.

  • Ferng, Y.-M., & co-authors. (2024). Development of thermal-hydraulic coupling model for deep-geological disposal of high-level radioactive wastes. Nuclear Engineering and Design.

  • Ferng, Y.-M., & co-authors. (2024). Numerical model for noise reduction of small vertical-axis wind turbines. Wind Energy Science.

  • Ferng, Y.-M., & co-authors. (2024). Numerical prediction of the aerodynamics and aeroacoustics of a 25 kW horizontal axis wind turbine. Journal of Mechanics.

Xiaolong Lu | Engineering | Best Researcher Award

Dr. Xiaolong Lu | Engineering | Best Researcher Award

Dr. Xiaolong Lu, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, China

Dr. Xiaolong Lu (b. Jan 21, 1994) is a materials scientist at the State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, CAS. He holds a Master’s in Chemical Engineering from Tianjin University and a Bachelor’s in Process Equipment from Qilu University of Technology. His expertise spans CVD, PVD, BET, and advanced tribological testing 🧪. Dr. Lu has published multiple papers on high-entropy coatings, nanostructured materials, and wear-resistant films in top-tier journals 📚. His research contributes significantly to aerospace and industrial lubrication technologies

Publication Profile

Scopus

🎓 Educational Background

Dr. Xiaolong Lu began his academic journey in Process Equipment and Control Engineering at Qilu University of Technology, where he earned his Bachelor’s degree (2012–2016) 🏫. He then advanced his expertise by pursuing a Master’s degree in Chemical Engineering at the prestigious Tianjin University from 2016 to 2019 🧪. Throughout his academic training, Dr. Lu developed a strong foundation in mechanical design, materials science, and engineering principles, which laid the groundwork for his future contributions to advanced materials and tribology research 🔬📘. His education has played a vital role in shaping his innovative research career.

💼 Work Experience

Dr. Xiaolong Lu began his professional career at Sinohydro Foundation Engineering Co., Ltd from July to December 2019, gaining valuable industry experience in engineering projects 🏗️. In January 2020, he joined the prestigious State Key Laboratory of Solid Lubrication at the Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences 🏛️. There, he has been deeply involved in cutting-edge research on advanced tribological materials and surface coatings 🔬. His work focuses on developing innovative solutions for wear resistance and lubrication, contributing significantly to the field of materials science and engineering.

🔍 Research Focus

Dr. Xiaolong Lu’s research centers on advanced tribological materials and high-entropy coatings for wear resistance and lubrication applications ⚙️🛡️. His work extensively explores high-entropy nitrides and carbonitrides, investigating their mechanical, structural, and tribological properties under varying conditions 🧪🔬. Using cutting-edge techniques like high power impulse magnetron sputtering and high-throughput preparation methods, Dr. Lu aims to enhance coatings for demanding environments such as aviation lubricants ✈️. His research contributes to developing innovative materials that improve durability and reduce friction in mechanical systems, supporting industrial and aerospace engineering advancements

Conclusion

Dr. Xiaolong Lu’s focused research on high-entropy coatings, tribological optimization, and advanced deposition techniques marks him as a valuable contributor to applied surface engineering. His combination of practical expertise, high-impact publications, and innovative methodology makes him a strong and deserving candidate for the Best Researcher Award.

Publication Top Notes

  • Exploring atmospheric tribological properties of MoS2-(Cr, Nb, Ti, Al, V) composite coatings, Tribology International, 2021, cited by [–] 📅⚙️

  • Investigation of (CrAlTiNbV)Nx high-entropy nitride coatings for aviation lubricant, Applied Surface Science, 2021, cited by [–] 🧪✈️

  • Mechanical and tribological performance of (CrAlTiNbV)Nx nitride coatings in aviation lubricant, Ceramics International, 2021, cited by [–] 🏭🔧

  • Nanostructure, mechanical properties and tribological behavior of high-entropy carbonitrides coatings, Ceramics International, 2025, cited by [–] 🔬⚡

  • Effect of peak current on MoxN coatings microstructure and tribological behavior, Tribology International, 2023, cited by [–] ⚡🛠️

  • Characterization and wear role of (CrAlVTiNb)Nx high-entropy alloy nitride films, Journal of Alloys and Compounds, 2025, cited by [–] 🧱🔍

  • Comparative analysis of high-entropy nitrides and carbonitrides coatings over temperature range, Journal of Alloys and Compounds, 2025, cited by [–] 🌡️📊