Qingling Zhao | Computer Science | Research Excellence Award

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Prof. Qingling Zhao | Computer Science | Research Excellence Award

Nanjing University of Science and Technology | China

Prof. Qingling Zhao is a leading researcher in embedded systems, real-time systems, mixed-criticality scheduling, and intelligent computing, with significant contributions spanning system architecture, cyber–physical systems, and AI-driven embedded intelligence. With an h-index of 12, 26 scholarly documents, and 456 citations across 345 citing publications, the research output demonstrates sustained academic impact. The work covers core areas such as mixed-criticality scheduling theory, resource synchronization, stack memory optimization, AUTOSAR model optimization, and schedulability analysis, alongside recent advances in deep learning, reinforcement learning optimization, network-on-chip systems, intrusion detection, and remote sensing object detection. Publications appear in high-impact venues including ACM Transactions on Embedded Computing Systems, IEEE Transactions, Journal of Systems Architecture, IEEE Access, and major international conferences. Recent research extends classical real-time system theory toward AI-enabled embedded and cyber-secure systems, reflecting a strong integration of theoretical rigor and practical applicability across safety-critical and intelligent computing platforms.

Citation Metrics (Scopus)

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456

h-index
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26

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Petro Pavlenko | Engineering | Research Excellence Award

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Prof. Dr. Petro Pavlenko | Engineering | Research Excellence Award

Zhejiang Ocean University | China

Prof. Dr. Petro Pavlenko is a distinguished researcher whose contributions span engineering design, CAD/CAM/CAE/PDM systems, digital manufacturing, and integrated information environments for industrial applications. With an h-index of 4, 27 documents, and 53 citations, his scholarship reflects both depth and sustained relevance across engineering and information technology domains. His research encompasses automation of design processes, digital 3D modeling, production data management, logical-dynamic models for information security, digital twins, robotics, energy lifecycle management, and industrial information system integration. He has produced more than 250 scientific publications, including 43 international journal papers, alongside 9 patents and multiple influential textbooks and monographs on mathematical modeling, information systems, and production automation. His leadership roles include chairing specialized academic councils, contributing to expert committees in informatics and cybernetics, directing research laboratories, and guiding PhD program development. Collaborations with universities and research centers across Ukraine, Kazakhstan, Germany, France, Latvia, and Russia have supported advancements in automated manufacturing, robot trajectory planning, and industrial data technologies. His recent works focus on additive manufacturing, microstructure–hardness modeling, digital energy systems, and intelligent information support, reinforcing his impact on modern engineering innovation and computational design methodologies.

 

 

Citation Metrics (Scopus)

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Citations
53

Documents
27

h-index
4



View Scopus Profile

 

Featured Publications

Fucan Huang | Engineering | Excellence in Research Award

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Dr. Fucan Huang | Engineering | Engineering | Excellence in Research Award

Shandong University of Science and Technology | China

Dr. Fucan Huang is an emerging researcher in mechanical fault diagnosis, known for advancing intelligent diagnostic methods through deep learning, multi-attention mechanisms, and cross-domain adaptability. His work focuses on improving fault detection accuracy in complex industrial environments, particularly under fluctuating conditions, imbalanced datasets, and multi-source domain challenges. He has contributed significantly to Measurement Science and Technology and Machines, co-authoring several influential papers. His research includes the development of an adaptive attenuation self-attention adversarial network for cross-domain diagnosis, a multi-source domain collaborative bearing fault method guided by multi-attention mechanisms, and innovative dual-domain vision transformer frameworks. These contributions enhance the robustness, generalizability, and interpretability of diagnostic models, strengthening intelligent maintenance systems and promoting safer, more efficient industrial operations.

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Featured Publications

An, Y., Zhang, D., Zhang, M., Xin, M., Wang, Z., Ding, D., Huang, F., & Wang, J. (2025). Residual attention-driven dual-domain vision transformer for mechanical fault diagnosis. Machines, 13(12), Article 1096.

Huang, F., Zhang, Q., Han, B., Wang, J., Zhang, Z., Ge, R., & Gong, H. (2025). Adaptive attenuation self-attention adversarial network for cross-domain fault diagnosis under imbalanced conditions. Measurement Science and Technology, 31 December 2025.

Ge, R., Zhang, Z., Wang, J., Wang, W., Fan, Z., & Huang, F. (2025). Multi-source domain bearing fault collaborative diagnosis method for unbalanced samples guided by multi-attention mechanism. Measurement Science and Technology, 30 November 2025.

Han, B., Huang, F., Qin, M., Qin, H., Wang, J., Zhang, Z., & Yu, Y. (2025). Dual-domain fused vision transformer for mechanical fault diagnosis under fluctuating working conditions. Measurement Science and Technology, 30 April 2025.

Hongfei Yang | Engineering | Best Researcher Award

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Assoc Prof Dr. Hongfei Yang | Engineering | Best Researcher Award

Shihezi University | China

Author Profile

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🌱 Early Academic Pursuits

Dr. Hongfei Yang’s academic journey is marked by an impressive foundation in engineering and scientific disciplines. He earned his Bachelor's degree in Mechanical Design, Manufacturing, and Automation from Dalian University in 2016. Following this, he pursued his Master’s in Mechanical Design and Theory at Jilin University, complemented by a joint training program at Cambridge University. These early years laid a solid groundwork in mechanical design, equipping him with a unique blend of theoretical knowledge and practical skills.

💼 Professional Endeavors

Currently an Associate Professor in Electronic Information Engineering at Shihezi University, Dr. Yang has dedicated his career to advancing precision engineering and measurement technology. His experience includes a rigorous doctoral program in Testing and Measurement Technology at Jilin University, where he focused on developing innovative solutions in instrument technology. Dr. Yang's professional path reflects his commitment to impactful research and teaching in electronic and mechanical engineering fields.

📚 Contributions and Research Focus

Dr. Yang’s research is distinguished by its focus on magnetic sensing and machine vision, especially in applications for unstructured environments and deep-earth observations. As the first author of 11 academic papers with a cumulative impact factor of 59.4, he has made substantial contributions to journals like IEEE Transactions on Geoscience and Remote Sensing and IEEE Sensors Journal. His work addresses pressing challenges in instrument measurement, such as developing methods for identifying rail defects and creating robust magnetic sensing systems. His expertise extends to multiple patents, demonstrating practical solutions for applications ranging from long-term monitoring in extreme environments to automated mushroom collection devices.

🏆 Accolades and Recognition

Dr. Yang’s contributions have been recognized with numerous honors. Among them are the prestigious National Scholarship for Doctoral Students in China, awarded by the Ministry of Education, and Jilin University's First-Class Doctoral Excellence Scholarship. His scholarly achievements and dedication have earned him the title of "Outstanding Graduate" and the Geological Instrument Scholarship from Jilin University. These accolades reflect his exceptional research performance and his ongoing impact in his field.

🌍 Impact and Influence

Dr. Yang’s influence extends beyond academia, as he actively participates in shaping engineering knowledge as a reviewer for top journals like IEEE Transactions on Instrumentation and Measurement. His work on projects, such as the National Natural Science Foundation of China project on environmental recognition for engineering vehicles, has pushed the boundaries of how advanced data processing can improve machine vision in complex environments. His contributions to deep borehole observation technology are advancing our understanding of deep-earth environments, with applications in various scientific and industrial domains.

🏅 Legacy and Future Contributions

Dr. Yang’s career represents a blend of innovation, interdisciplinary expertise, and real-world applications. His research in precision engineering, machine vision, and magnetic sensing continues to inspire advancements in technology and scientific exploration. His legacy lies in both his published works and his commitment to teaching, mentoring, and advancing engineering research. Looking forward, Dr. Yang is set to further enrich the field of electronic information engineering, leaving an enduring impact on the next generation of scientists and engineers.

 

Publications

📝 SwinLabNet: Jujube Orchard Drivable Area Segmentation Based on Lightweight CNN-Transformer Architecture

Authors: Mingxia Liang, Longpeng Ding, Jiangchun Chen, Liming Xu, Xinjie Wang, Jingbin Li, Hongfei Yang
Journal: Agriculture
Year: 2024

📝 Neural Network-Based 3D Point Cloud Detection of Targets in Unstructured Environments

Authors: D. Wang, H. Yang, Z. Yao, Z. Chang, Y. Wang
Journal: Advances in Mechanical Engineering
Year: 2024

📝 MI-FPD: Magnetic Information of Free Precession Signal Data Measurement Method for Bell-Bloom Magnetometer

Authors: D. Bai, L. Cheng, Y. Sun, H. Yang, Y. Wang
Journal: IEEE Transactions on Geoscience and Remote Sensing
Year: 2024

📝 Efficient Measurement of Free Precession Frequency in Bell-Bloom Atomic Magnetometers

Authors: D. Bai, Y. Zhou, Y. Sun, H. Yang, Y. Wang
Journal: IEEE Transactions on Instrumentation and Measurement
Year: 2024

📝 EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application

Authors: J. Hu, H. Yang, J. He, D. Bai, H. Chen
Journal: IEEE Access
Year: 2024

 

Dariusz Mazurkiewicz | Engineering | Excellence in Research Award

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Prof. Dariusz Mazurkiewicz | Engineering | Excellence in Research Award

Politechnika Lubelska | Poland

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Early Academic Pursuits

Professor Dariusz Mazurkiewicz embarked on his academic journey by earning a Master’s degree in Mechanical Engineering from the Technical University of Lublin, Poland, in 1991. He further pursued his academic endeavors by completing his doctorate in technical sciences from the same university in 1997. His commitment to scholarly pursuits continued as he successfully passed the final habilitation procedure examination in technical sciences at the Technical University of Lublin in 2011. This foundation laid the groundwork for his illustrious career in academia and research.

Professional Endeavors

Professor Mazurkiewicz’s professional journey is marked by significant achievements and contributions in the fields of engineering and academia. Notably, he was bestowed with the prestigious title of full professor in technical and engineering sciences by the President of the Republic of Poland in 2022. Throughout his career, he has been actively involved in national and international research projects, contributing to advancements in areas such as digital twin technology, systems engineering, and reliability management. He has served as a keynote speaker at various esteemed conferences, sharing his expertise and insights with the global academic community.

Contributions and Research Focus

Professor Mazurkiewicz’s research focus spans a diverse range of topics, including digital twin-based fault prediction, process optimization, and reliability engineering. His pioneering work in developing innovative measurement technologies and digital data processing algorithms has garnered recognition and acclaim from peers worldwide. He has led numerous research projects aimed at enhancing the efficiency and reliability of production systems, thereby contributing to the advancement of industrial practices and technologies.

Accolades and Recognition

Professor Mazurkiewicz’s contributions to academia and research have been recognized through a multitude of awards and distinctions. He has been listed among the world’s top scientists by Stanford University and Elsevier, underscoring the impact of his scholarly endeavors. His research presentations and publications have received accolades such as the Best Paper Award at prestigious international conferences. Additionally, he has been honored by academic institutions and organizations for his outstanding scientific achievements and organizational contributions.

Impact and Influence

Professor Mazurkiewicz’s work has had a profound impact on the fields of engineering, reliability, and systems management. His research findings and innovative methodologies have not only advanced scientific knowledge but also contributed to practical applications in industry and academia. Through his leadership and mentorship, he has inspired future generations of researchers and scholars to pursue excellence in their respective domains, thereby fostering a culture of innovation and inquiry.

Legacy and Future Contributions

Professor Mazurkiewicz’s legacy is characterized by a steadfast commitment to excellence, innovation, and collaboration in research and academia. His continued efforts to push the boundaries of knowledge and technology are poised to shape the future of engineering and reliability sciences. As he continues to lead groundbreaking research initiatives and mentor aspiring scholars, his legacy will endure as a testament to his enduring dedication to advancing the frontiers of scientific inquiry and engineering excellence.

Notable Publications

Virtual tomography as a novel method for segmenting machining process phases with the use of machine learning-supported measurement 2024

Novel Approach to Prognostics and Health Management to Combine Reliability and Process Optimisation 2023

Production Process Stability: The Advantages of Going Beyond Qualitative Analysis 2023 (2)

Systems Engineering: Availability and Reliability 2022 (13)

Method for assessing the impact of rainfall depth on the stormwater volume in a sanitary sewage network 2021 (3)