Jinquan Ding | Vehicle Dynamics | Research Excellence Award

 Prof. Jinquan Ding | Vehicle Dynamics | Research Excellence Award

Senior Engineer  |  Zhengzhou University of Light Industry  | China

Prof. Jinquan Ding is a senior engineer with strong expertise in vehicle system dynamics and advanced automotive engineering, contributing extensively to both theoretical development and applied research. His professional experience focuses on vehicle handling dynamics, intelligent electric chassis systems, and suspension kinematics and compliance analysis, with active involvement in high-impact journal and SAE technical publications addressing multi-axle vehicle dynamics, suspension lateral dynamics, and parameter identification methodologies. His research interests center on vehicle dynamics modeling, suspension system analysis, and intelligent chassis control strategies. He demonstrates advanced research skills in dynamic modeling, kinematic analysis, parameter identification, and numerical evaluation methods. His achievements have been recognized through prestigious provincial science and technology progress awards, reflecting sustained research excellence and industry relevance. Overall, his work significantly advances modern vehicle dynamics research and engineering practice. He has achieved 42 Citations, 10 Documents,3h-index. 

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Talaat Abdelhamid | Automobile Engineering | Research Excellence Award

Assoc. Prof. Dr. Talaat Abdelhamid | Automobile Engineering | Research Excellence Award

Associate Professor  |  University of Milan  |  Italy

Assoc. Prof. Dr. Talaat Abdelhamid is an accomplished researcher in applied and computational mathematics with strong expertise in numerical analysis, inverse problems, and large-scale scientific computing. His professional experience spans academic appointments, postdoctoral and visiting positions, and international research collaborations, contributing to high-impact studies in cardiac bioelectricity modeling, computational fluid dynamics, heat transfer, elasticity imaging, and optimal control of PDE-based systems. His research interests focus on domain decomposition methods, inverse and ill-posed problems, biomedical modeling, and high-performance numerical solvers. He demonstrates advanced research skills in mathematical modeling, algorithm development, finite element methods, optimization techniques, and multidisciplinary simulation. His achievements include multiple competitive research grants, international fellowships, and outstanding academic awards, reflecting sustained scholarly impact and leadership in applied mathematics research. He has achieved 858 Citations, 42 Documents,12h-index.

 

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Featured Publications


Energy and Exergy Analysis of Solar Stills with Micro/Nano Particles

– Energy Conversion and Management, 2018 (227 Citations)


Heat Transfer and Flow Around Cylinder: Effect of Corner Radius and Reynolds Number

– International Journal of Heat and Mass Transfer, 2021 (108 Citations)


Effect of Cylinder Corner Radius and Attack Angle on Heat Transfer and Flow Topology

– International Journal of Mechanical Sciences, 2020 (97 Citations)

Youqun Zhao | Vehicle Dynamics | Research Excellence Award

Prof. Dr.Youqun Zhao | Vehicle Dynamics | Research Excellence Award

Second-level Professor  |  Nanjing University of Aeronautics and Astronautics  |  China

Prof. Dr. Youqun Zhao is a leading scholar in vehicle engineering and intelligent transportation systems, with extensive contributions spanning green intelligent transport equipment, new-energy and electric vehicles, vehicle safety and control, non-pneumatic mechanical elastic wheels, and human–machine shared control for autonomous driving. Professional experience reflects long-term leadership in advanced vehicle dynamics, handling inverse dynamics, and intelligent control, alongside visiting and collaborative international research roles. Research interests focus on vehicle system dynamics, unmanned and co-driving vehicles, mechanical elastic wheel technology, suspension and steering control, and energy-efficient mobility systems. Research skills include theoretical modeling, inverse dynamics, multi-objective optimization, control algorithms, simulation–experiment integration, and patent development. Awards and honors include multiple national and ministerial science and technology prizes, invention awards, and recognition among the world’s top 2% scientists. Overall, the work demonstrates sustained impact, innovation, and academic excellence in automotive and intelligent vehicle engineering.He has achieved 2904 Citations, 261 Documents, 28 h-index.

 

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Muhammad Zahid Iqbal | Crash Analysis and Safety | Research Excellence Award

Dr. Muhammad Zahid Iqbal | Crash Analysis and Safety | Research Excellence Award

HOD  |  PIEAS  |  Pakistan

Dr. Muhammad Zahid Iqbal is an accomplished mechanical engineering professional with extensive expertise in product development, vibration and shock isolation, CAD/CAM, and advanced finite element analysis. His professional experience spans academia and industry, including leadership roles in mechanical engineering departments and senior engineering positions focused on CNC manufacturing, system design, and applied mechanics. His research interests center on impact dynamics, shock pulse control, vibration attenuation, energy absorption devices, and development of experimental test machines and damping systems. He possesses strong research skills in numerical modeling, experimental validation, CAD/CAM integration, and nonlinear dynamic analysis, supported by proficiency in advanced engineering software and control systems. His work has earned recognition through peer-reviewed publications and contributions to high-impact engineering solutions, reflecting a sustained commitment to innovation, teaching excellence, and applied research advancement.He has achieved 26 Citations, 10 Documents, 3h-index.

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Esraa Kotb | Automotive Manufacturing | Research Excellence Award

Dr. Esraa Kotb | Automotive Manufacturing | Research Excellence Award

Assistant Researcher | Central Metallurgical Research and Development Institute (CMRDI) | Egypt

Dr. Esraa Kotb is an emerging researcher in steel, physical metallurgy, and ferroalloys technology with strong contributions to applied and industrial materials research. Professional experience includes progressive research roles within a national metallurgical institute, active participation in funded projects, laboratory accreditation activities, and collaboration with multidisciplinary teams addressing advanced steel development and energy-efficient alloy production. Research interests focus on medium-manganese steels, ferroalloys processing, microstructure–property relationships, and sustainable metallurgical technologies. Research skills include materials characterization, alloy design, process optimization, experimental analysis, technical reporting, and project coordination. Awards and honors recognize excellence in research projects and thesis-level innovation. Overall, the profile reflects consistent scientific impact, industrial relevance, and commitment to advancing metallurgical research. She has achieved 10 Citations, 5 Documents, 2 h-index.

 

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Silicomanganese Alloy from Rich Manganese Slag Produced from Egyptian Low-Grade Manganese Ore

– Journal of the Southern African Institute of Mining and Metallurgy, 2022

Mahmoud Zadehbagheri | Powertrain Engineering | Research Excellence Award

Assoc. Prof. Dr. Mahmoud Zadehbagheri | Powertrain Engineering | Research Excellence Award

Member of Electrical Faculty | Islamic Azad University of Iran |  Iran

Assoc. Prof. Dr. Mahmoud Zadehbagheri is a distinguished researcher and academic professional with extensive contributions to electrical engineering, particularly in power electronics and modern power systems. His professional experience encompasses advanced research leadership, academic supervision, and international collaboration, with active involvement in high-impact journals and conferences. His research interests focus on renewable energy integration, distributed generation, microgrids, power quality enhancement, FACTS devices, optimization techniques, and smart energy systems. He demonstrates strong research skills in system modeling, optimization algorithms, power system analysis, simulation, and applied engineering solutions. His scholarly output and service have earned multiple academic recognitions and honors for research excellence and leadership. Overall, his work significantly advances sustainable energy technologies and intelligent power system development at both theoretical and applied levels.He has acheived 705 Citations, 58 Documents,16 h-index.

 

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Zhen Guo | Automotive Robotics | Research Excellence Award

Dr. Zhen Guo | Automotive Robotics | Research Excellence Award

Doctoral student |  Wuhan University of Technology |  China

Dr. Zhen Guo is an emerging researcher in intelligent fault diagnosis and industrial artificial intelligence, with work spanning advanced data-driven methods for complex mechanical and robotic systems. The academic profile reflects strong training in engineering research with a focus on applying deep learning and statistical learning to real-world reliability challenges. Professional experience includes active service as a peer reviewer for leading international journals and conferences in engineering informatics, artificial intelligence, measurement science, and mechanical systems, demonstrating recognition within the scholarly community. Research interests center on deep learning–based fault diagnosis, rotating machinery health monitoring, robotics, anomaly detection, imbalance learning, few-shot and incremental learning, and transfer learning, particularly for wind turbines, gearboxes, and autonomous systems. Research skills encompass convolutional and attention-based neural networks, adversarial learning, feature extraction, time-series analysis, imbalance data handling, and intelligent condition monitoring frameworks. Contributions are evidenced by publications in high-impact journals such as Renewable Energy, IEEE Transactions on Instrumentation and Measurement, Expert Systems with Applications, Measurement, Ocean Engineering, and Scientific Reports, addressing both theoretical modeling and practical deployment. Awards and honors are reflected through consistent publication in top-tier venues and trusted reviewer roles. Overall, the work demonstrates a coherent trajectory toward robust, scalable, and intelligent diagnostic solutions for next-generation industrial and transportation systems. He has achieved 152 Citations 11 Documents 7h-index.

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Mehdi Modabberifar | Automobile Engineering | Research Excellence Award

Assoc. Prof. Dr. Mehdi Modabberifar | Automobile Engineering | Research Excellence Award

Associate Professor | Arak University | Iran

Assoc. Prof. Dr. Mehdi Modabberifar is an accomplished researcher with sustained contributions to mechatronic systems, advanced manufacturing, and electrostatic-based actuation technologies, demonstrating a strong balance between theoretical modeling and experimental validation. His professional experience includes active involvement in academic research environments, collaborative projects, and applied engineering studies addressing challenges in precision actuation, robotic manipulation, and smart material systems. His research interests focus on manufacturing processes, mechatronic system design, electrostatic actuators and motors, sensors, gecko-inspired adhesives, robotic grippers, and micro- and nano-scale manipulation, with applications spanning robotics, automation, and intelligent mechanical systems. His research skills encompass system modeling and simulation, actuator and sensor design, experimental mechanics, electrostatic induction mechanisms, robotic end-effector development, data analysis, and performance optimization under varying operational conditions. He has authored a diverse body of peer-reviewed journal and conference publications in reputable international outlets, with several widely cited works on gecko-inspired robotic grippers, electrostatic motors, dielectric sheet conveying, and smart actuator behavior, reflecting both originality and impact. His scholarly output demonstrates interdisciplinary reach across robotics, materials, and manufacturing engineering. Awards and honors include recognition through citation impact and research visibility within his fields of expertise. Overall, his work reflects a consistent trajectory of innovation, methodological rigor, and meaningful contribution to modern mechatronics and intelligent manufacturing research. He has achieved 202 Citations 23 Documents 7 h-index.

 

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Ayşe Tuğba Yapıcı | Electric Vehicles | Best Research Article Award

Ms. Ayşe Tuğba Yapıcı | Electric Vehicles | Best Research Article Award

Doctoral Researcher  |  Kocaeli University  |  Turkey

Ms. Ayşe Tuğba Yapıcı is a dedicated doctoral researcher whose academic journey is strongly rooted in cutting-edge technologies for electric vehicles, smart energy systems, and intelligent power electronics. She has cultivated significant professional experience through her active involvement in research addressing real-world problems such as electric vehicle charging optimization, grid-integrated charging infrastructures, and advanced modeling of power converter systems. Throughout her career, she has contributed to impactful scientific studies focusing on induction heating systems, charging time prediction using deep learning, and data-driven forecasting on electric vehicle adoption and infrastructure planning. Her research interests include electric vehicle technologies, charging station design, renewable-integrated smart grids, artificial intelligence–based energy forecasting, machine learning and deep learning applications in power systems, and IoT-enhanced smart mobility frameworks. She possesses strong research skills in Python-based deep learning toolkits, MATLAB/Simulink, DigSilent PowerFactory modeling, statistical evaluation metrics, time-series forecasting, optimization algorithms, and performance analysis of intelligent systems. She has published multiple peer-reviewed articles in international SCI/Scopus-indexed journals, delivering innovative research outcomes that offer comprehensive and practical solutions for the sustainable development of electric transportation. Her research achievements include proposing an intelligent deep learning–based framework for EV charging time prediction, integrating spatial–temporal mobility parameters, and enhancing operational efficiency for fast-charging infrastructures. Her work stands out for its interdisciplinary approach and technological significance, supporting the transition toward cleaner mobility, optimized charging networks, and smart energy management. In addition to research excellence, she continues to contribute to academic and scientific communities through conference participation, collaborations, and knowledge dissemination. She aims to advance secure, intelligent, and scalable charging automation systems that support next-generation autonomous electric mobility. Her long-term vision is to shape energy-efficient transportation ecosystems, reduce environmental impacts, and contribute to the global sustainability agenda through innovation and scientific leadership. She has achieved  3 Citations , 2 Documents,  1 h-index.

Featured Publications

Yapıcı, A. T., & Abut, N. (2025, November 23). An intelligent and secure IoT-based framework for predicting charging and travel duration in autonomous electric taxi systems. Applied Sciences.

Yapıcı, A. T., Abut, N., & Yıldırım, A. (2025, October 27). Estimation of future number of electric vehicles and charging stations: Analysis of Sakarya Province with LSTM, GRU and multiple linear regression approaches. Applied Sciences.

Yapıcı, A. T., & Abut, N. (2025, August 21). Geleceğe yönelik elektrikli araç ve şarj istasyonu sayılarının LSTM ve GRU derin öğrenme yöntemleri kullanılarak tahmin edilmesi: Kocaeli ili örneği. Politeknik Dergisi.

Yapıcı, A. T., Abut, N., & Erfidan, T. (2025, April 11). Comparing the effectiveness of deep learning approaches for charging time prediction in electric vehicles: Kocaeli example. Energies.

Yapıcı, A. T., & Abut, N. (2024, September 15). Elektrikli araç şarj istasyonu konum tasarımında, Digsilent yazılımı kullanılarak Kocaeli Üniversitesi Umuttepe Kampüsü için örnek uygulama. Black Sea Journal of Engineering and Science.

Ayşe Tuğba Yapıcı’s research advances intelligent and sustainable electric mobility by integrating deep learning, smart grid technologies, and IoT-based predictive frameworks to optimize charging infrastructure and energy management. Her work supports the transition toward autonomous electric transportation, reducing environmental impacts, improving urban mobility planning, and contributing to global innovation in smart energy systems. She envisions scalable, reliable, and human-centered smart mobility ecosystems that accelerate the adoption of clean transportation worldwide.

Hongbo Wang | Vehicle Dynamics | Best Researcher Award

Prof. Hongbo Wang | Vehicle Dynamics | Best Researcher Award

Professor  |  Hefei University of Technology  | China

Prof. Hongbo Wang is a distinguished scholar whose work in intelligent vehicle dynamics and control has shaped both academic research and industrial applications, consistently advancing methodologies in vehicle motion modeling, intelligent control algorithms, and automated driving technologies. With extensive experience leading more than forty national, provincial, and municipal projects, his professional contributions span high-impact investigations into off-road vehicle technology, autonomous driving stability, integrated chassis control, and intelligent mobility systems. His research interests focus on vehicle dynamic behavior analysis, intelligent control strategies, computational modeling, and multi-source information fusion for advanced driving systems, supported by strong research skills in algorithm development, real-time system implementation, experimental platform construction, and interdisciplinary engineering integration. His portfolio of scientific achievements includes more than one hundred academic publications, thirty authorized invention patents, six software copyrights, participation in two provincial standard developments, and the publication of two influential monographs, positioning him as a leading contributor to the field’s evolution. His professional experience is complemented by service roles such as External Expert of the Off-Road Vehicle Technology Branch of the Chinese Society of Automotive Engineers, Member of the Vehicle Control and Intelligentization Technical Committee of the Chinese Association of Automation, and Director of the Anhui Society of Automotive Engineers, reflecting broad recognition across national organizations. His awards include the First Prize of the Science and Technology Award of the Chinese Society of Automotive Engineers, the Second Prize of the Machinery Industry Technology Invention Award, and multiple Anhui Provincial Teaching Achievement Awards, underscoring excellence in both research innovation and educational leadership. Overall, his career demonstrates a sustained commitment to advancing intelligent automotive technologies and fostering academic growth in the engineering community. He has achieved 532 Citations,  63 Documents , 12 h-index.

Profile:  Scopus

Featured Publications 

1. Wang, H., et al. (2025). Multi-objective parallel human–machine steering coordination control strategy of intelligent vehicles path tracking based on deep reinforcement learning. Chinese Journal of Mechanical Engineering (English Edition).

2. Wang, H., et al. (2025). Trajectory tracking multi-constraint model predictive control of unmanned vehicles based on sideslip stiffness estimation with XGBoost algorithm. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering.

3. Wang, H., et al. (2025). Yaw stability control of tractor vehicle based on nonsingular fast terminal sliding mode. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering.

4. Wang, H., et al. (2025). Intelligent vehicle path tracking coordinated optimization based on dual-steering cooperative game with fault-tolerant function. Applied Mathematical Modelling.

5. Wang, H., et al. (2025). Identification of intrusion obstacles for underground locomotives based on the fusion of LiDAR and wireless positioning technology. International Journal of Vehicle Performance.

Professor Hongbo Wang’s research advances intelligent vehicle control by integrating reinforcement learning, predictive modeling, and human–machine cooperation to enhance safety, stability, and autonomy. His work contributes directly to next-generation intelligent transportation systems, improves industrial vehicle technologies, and supports global innovation in automated mobility.