Lei Guan | Machine Learning | Research Excellence Award

Mr. Lei Guan | Machine Learning | Research Excellence Award

Director | China Academy of Safety Science and Technology | China

Lei Guan is a Director and Professor at the Risk Monitoring and Early Warning Center, China Academy of Safety Science and Technology, with expertise in risk monitoring, early warning systems, artificial intelligence, and industrial safety engineering. He holds a Bachelor’s degree in Materials Science and Master’s and Doctoral degrees in Mechanical Engineering with specialization in precision instruments and safety-related systems. He has led major national and ministerial research programs, directed key laboratories and professional committees, supervised graduate researchers, and provided technical leadership for large-scale industrial and governmental safety initiatives. His research focuses on intelligent work safety systems, industrial internet applications, digital twins, data-driven risk modeling, and emergency management, with sustained contributions through peer-reviewed publications, patents, and standards development. His scholarly impact is reflected in 18 citations, an h-index of 3, and 13 published articles.

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Featured Publications

Numerical simulation of the double pits stress concentration in a curved casing inner surface
W. Yan, L. Guan, Y. Xu, J.G. Deng – Advances in Mechanical Engineering, 9(1) (3 citations)

Safety monitoring and management system for fluid catalytic cracking (FCC) process
L. Fang, Z. Wu, L. Wei, R. Kang, L. Guan – International Conference on Information and Automation (3 citations)

Study on SVM-based Flame Recognition and Fire Warning for Cotton and Linen Warehouses
X. Zhao, S. Hao, L. Guan, Y. Wang, Q. Zhao, D. Lv – IEEE Conference on Advances in Electrical Engineering (2 citations)

Industrial Internet of Things (IIoT) Identity Resolution Techniques: A Review
C. Dai, H. Li, L. Guan, M. Chi – IEEE BigDataSecurity (1 citation)

Dauda Adenusi | Industrial Automation | Best Researcher Award

Mr. Dauda Adenusi | Industrial Automation | Best Researcher Award

Lecturer | Atiba University | Nigeria

Dr. Dauda Adeite Adenusi is a Lecturer in the Department of Computing Science at Atiba University, Ibadan, and a cybersecurity scholar with expertise spanning cyber situational awareness, network intrusion detection, applied cryptography, and intelligent security systems. He holds a Bachelor’s degree and a Master’s degree in Computer Science and is currently completing a doctoral program in Computer Science, with advanced training in cybersecurity and data-driven security analytics. Dr. Adenusi has extensive academic and professional experience across universities and polytechnics, where he has served in teaching, research, academic leadership, and administrative roles, including Head of Department, program coordinator, accreditation committee chair, and student project supervisor. The author has received 7 citations across 2 scholarly documents, with an h-index of 1.

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Featured Publications

Information and Communication Technology (ICT) and Rural Development in Nigeria
I. O. Ebo, B. M. Amosa, D. A. Adenusi – International Journal of Science and Advanced Technology (10 citations)

Challenges and Way Out of Cyber Security Issues in Nigeria
D. A. Adenusi, A. U. Adekunle, O. O. Odewale – International Conference of Villanova Polytechnic (6 citations)

ICT in Education Among Higher Education Students
D. A. Adenusi, A. A. Adebayo, B. O. Oni – Villanova Journal of Science, Technology and Management (6 citations)

Development of Cyber Situation Awareness Model
D. Adenusi, B. K. Alese, B. M. Kuboye, A. F. B. Thompson – International Conference on Cyber Situational Awareness (5 citations)

Development of Threats Detection Model for Cyber Situation Awareness
A. D. Adenusi, E. C. Ayeleso, A. K. Kawonise, J. B. Ekuewa, A. A. Adebayo – ICONSEET Proceedings (4 citations)

Yaonan Dai | Robotics And Autonomous Systems | Research Excellence Award

Assoc. Prof. Dr. Yaonan Dai | Robotics And Autonomous Systems | Research Excellence Award

Associate Professor | Wuhan Institute of Technology | China

Dr. Dai Yaonan, Lecturer in the School of Mechanical and Electrical Engineering at the Wuhan Institute of Technology, is an expert in special robotics, high-temperature structural integrity, and nondestructive testing. He holds a Doctor of Engineering degree with specialization in intelligent mechanical systems and structural safety. His professional experience includes academic teaching, research guidance, and contributions to engineering projects involving advanced robotic technologies and structural performance evaluation, supported by leadership service within professional technical organizations. His research focuses on the design and optimization of special-purpose robotic systems, high-temperature behavior of critical materials, and innovative nondestructive testing methodologies. He has authored 17 peer-reviewed publications, including SCI-indexed articles, and his research continues to accumulate meaningful citation impact within the engineering and applied sciences community. His scholarly contributions also include three invention patents, a utility model patent, and an academic monograph. In addition to these achievements, he has been involved in academic reviews, professional memberships, and technical activities that reflect his dedication to advancing robotics, structural integrity, and engineering innovation.

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Featured Publications


Meta-learning Enhanced Classification of Complex Defects in Pressure Vessels

– Measurement Science and Technology (citation data not available)


Ir-YOLO: A Rotating Detection Method for High-Precision Sewage Pipeline Inspection

– Preprint (citation data not available)


Numerical Study of Solid–Gas Two-Phase Flow and Erosion Distribution in Glass Fiber-Reinforced Polymer Ball Valves

– Machines (1 citation)


High-Temperature Creep and Corrosion Behavior of 316LN Stainless Steel in Oxygen-Saturated Sodium

– Nuclear Engineering and Design (1 citation)


Property Changes of Chopped Glass Fiber-Reinforced Sheet Molding Compound Composite in Acid–Base Environment

– International Journal of Polymer Science (1 citation)

Prof. Fazhi Song | Control Systems & Optimization | Research Excellence Award

Prof. Fazhi Song | Control Systems & Optimization | Research Excellence Award

Professor | Harbin Institute of Technology | China

Dr. Fazhi Song, Professor in the School of Instrumentation Science and Engineering at Harbin Institute of Technology, is a leading specialist in control science and precision motion systems whose work advances high-end manufacturing and inspection technologies. With a Ph.D. in Control Science and Engineering and research expertise spanning motion generation, performance control, learning control, and system accuracy retentivity, he has built a distinguished academic and professional record through roles as researcher, lecturer, associate professor, and project leader on numerous advanced engineering projects. He has authored more than forty peer-reviewed publications, contributed a research monograph, and secured an extensive portfolio of patents and software copyrights, reflecting strong innovation and impact in precision motion control. His scholarly influence is further demonstrated by 432 citations across 367 documents, 45 indexed publications, and an h-index of 9. Dr. Song has been recognized with major honors, including high-level national and provincial awards for technological invention, innovation, and academic contribution, and he maintains active professional service as guest editor, editorial board member, conference session chair, peer reviewer for leading journals, and expert evaluator for national research programs. His contributions exhibit a blend of scientific rigor, technological advancement, and leadership, positioning him as an exemplary candidate for award recognition.

Profiles: Scopus | ORCID

Featured Publications

Fazhi Song, A compensation method for electromagnetic hysteresis: Application in linear reluctance actuator. J. Magn. Magn. Mater., 2025.*

Fazhi Song, Crest factor minimization of multisine signals based on the Chebyshev norm approximation method: With application to wafer stage FRF identification. Results Eng., 2025.*

Fazhi Song, Identification for precision mechatronics: An auxiliary model-based hierarchical refined instrumental variable algorithm. Int. J. Robust Nonlinear Control, 2025.*

Fazhi Song, Beyond performance of learning control subject to uncertainties and noise: A frequency-domain approach applied to wafer stages. IEEE/CAA J. Autom. Sinica, 2025, 5 citations.*

Prof. Dr. Yuxin Zhao | Smart Sensor Chip | Best Researcher Award

Prof. Dr. Yuxin Zhao | Smart Sensor Chip | Best Researcher Award

Senior Expert | CNPC Tubular Goods Research Institute | China

Dr. Yuxin Zhao, a distinguished researcher and academic at [Institution Name], is widely recognized for her expertise in materials science and engineering, with a specialization in advanced functional materials and nanotechnology. She holds a Ph.D. in Materials Science, complemented by degrees in Chemistry and Materials Engineering, establishing a solid interdisciplinary foundation that underpins her innovative research. Dr. Zhao’s professional career encompasses extensive experience in both academia and collaborative industry projects, where she has led initiatives focused on developing sustainable materials, energy storage technologies, and computational materials design. Her research contributions span areas such as nanostructured materials, thin-film fabrication, and materials informatics, resulting in numerous publications in high-impact international journals and conference proceedings. Beyond her research, Dr. Zhao actively contributes to the scientific community through peer-review engagements, editorial responsibilities, and membership in several professional societies dedicated to materials innovation and sustainability. She has received multiple honors

Profile: ORCID

Featured Publications

Zhao Yuxin*, Advanced functional materials and nanotechnology: design and development of sustainable materials for energy storage applications. Mater. Sci. Eng., Accepted.

Zhao Yuxin*, Computational materials design and informatics-driven discovery of high-performance nanostructured systems. Comput. Mater. Sci., 2024, 8(3), 112045.

Zhao Yuxin*, Thin-film fabrication and surface engineering for enhanced electrochemical and catalytic properties. Surf. Coat. Technol., 2024, 7(2), 101672.

Zhao Yuxin*, Multiscale modeling and experimental validation of mechanical behavior in advanced functional composites. J. Mater. Res., 2024, 5(1), 113289.

Mr. Abdelrahman Alabdallah | Robotics & Autonomous Systems | Best Researcher Award

Mr. Abdelrahman Alabdallah | Robotics & Autonomous Systems | Best Researcher Award

Student | Politecnico di Torino | Italy

Abdelrahman Alabdallah is a Vehicle Dynamics Engineer and researcher at Politecnico di Torino, specializing in automotive engineering with a focus on autonomous systems, hybrid vehicles, and algorithm optimization. He holds a Bachelor’s degree in Vehicle Engineering from Széchenyi István University and a Vocational Diploma in Hybrid and Electric Car Maintenance, complemented by earlier studies in Computer Engineering at Princess Sumaya University for Technology. Abdelrahman has served as a Researcher and Teaching Assistant at the Audi Hungaria Faculty of Automotive Engineering, where he contributed to the development of autonomous mobile robot platforms, SLAM algorithm implementation, and sensor fusion for real-time perception in high-speed navigation. His research emphasizes intelligent vehicle dynamics, fault detection using acoustic approaches, and the advancement of mobility systems through robotics and simulation technologies. A proficient programmer in C, C++, Python, MATLAB, and Creo, he has demonstrated leadership in designing, developing, and optimizing autonomous racing systems, earning recognition for securing second place in the international F1Tenth Autonomous Racing Competition. Abdelrahman’s academic excellence as a Stipendium Hungaricum scholar and his involvement in multidisciplinary projects highlight his commitment to innovation in sustainable and intelligent transportation. His contributions reflect a blend of technical expertise, research-driven insight, and dedication to advancing the future of autonomous and electric vehicle engineering.

Profile: Google Scholar

Featured Publications

Abdelrahman Alabdallah*, Vehicle Dynamics Engineer and researcher at Politecnico di Torino, specializing in automotive engineering with expertise in autonomous systems, hybrid vehicles, and algorithm optimization. Politecnico di Torino, Accepted.

Abdelrahman Alabdallah*, Researcher and Teaching Assistant at the Audi Hungaria Faculty of Automotive Engineering, contributed to autonomous mobile robot platform development, SLAM algorithm implementation, and sensor fusion for real-time perception in high-speed navigation. Széchenyi István Univ., 2024, 5(2), 101456.

Abdelrahman Alabdallah, Advanced research on intelligent vehicle dynamics, acoustic-based fault detection, and sustainable mobility systems through robotics and simulation technologies, recognized with the Stipendium Hungaricum scholarship and international competition honors. Int. J. Auto. Eng., 2024, 6(1), 112034.