Dr. Xin Zhou | Engineering | Best Researcher Award

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Dr. Xin Zhou | Engineering | Best Researcher Award

Dr. Xin Zhou | Engineering – Lecture at Shanghai University of Electric Power, China

Dr. Xin Zhou is a passionate and emerging researcher in the field of automation engineering, currently serving as a lecturer at Shanghai University of Electric Power. With a solid international educational background and hands-on research in robotics and intelligent optimization, he brings both academic insight and practical relevance to his work. Dr. Zhou has focused his career on robotic path planning, artificial intelligence in manufacturing, and intelligent control systems. His rapid contributions to both the theoretical foundations and industrial applications of intelligent robotics make him a promising candidate for the Best Researcher Award.

Education:

Dr. Zhou’s academic path spans several prestigious institutions across China, the UK, and Australia. He received his Ph.D. in Control Science and Engineering from East China University of Science and Technology in 2022, concentrating on intelligent algorithms and robotic optimization. He earned his Master’s degree in Digital Systems and Communication Engineering from the Australian National University (2016–2017), developing skills in communication and embedded systems. His undergraduate training was jointly conducted at the University of Liverpool and Xi’an Jiaotong-Liverpool University (2011–2015), where he majored in Electrical Engineering and Automation, providing a strong technical foundation for his current work.

Profile:

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Experience:

Since August 2022, Dr. Zhou has been working as a lecturer at the School of Automation Engineering, Shanghai University of Electric Power. In this position, he teaches undergraduate and graduate courses while engaging in active research. He has participated in two completed projects funded by the National Natural Science Foundation of China (NSFC), focusing on welding robotics and production scheduling under uncertainty. Dr. Zhou is also leading a current industry-funded research project on motion planning algorithms for robotic systems used in complex maintenance tasks. His combination of academic research and industrial cooperation demonstrates a comprehensive and practical research profile.

Research Interest:

Dr. Zhou’s primary research interests include robotic path planning, multi-objective optimization, intelligent algorithms, and smart manufacturing systems. He specializes in developing evolutionary algorithms and applying them to real-world robotic control challenges, especially in arc welding scenarios. His work aims to enhance the intelligence, flexibility, and adaptability of autonomous robotic systems, contributing to Industry 4.0 initiatives. He is particularly known for his work on decomposition-based optimization methods and real-time obstacle avoidance strategies.

Awards:

While Dr. Zhou is still early in his career, he has already made notable contributions to applied innovation, as evidenced by three Chinese patents in the area of robotic path planning. These patents include novel systems and methods for arc welding robot navigation and gantry-type robotic control, with the most recent filed in December 2023. His work in patented technologies reflects his practical approach to academic research and commitment to industry-aligned solutions.

Publications:

Dr. Zhou has authored and co-authored several influential journal papers. Below are seven key publications, with emojis, journal names, publication years, and citation notes:

📘 A decomposition-based multiobjective evolutionary algorithm with weight vector adaptation – Swarm and Evolutionary Computation, 2021. Cited for its novel adaptive mechanism in multi-objective optimization.

🤖 An approach for solving the three-objective arc welding robot path planning problem – Engineering Optimization, 2023. Frequently referenced in robotics and optimization studies.

🛠️ Online obstacle avoidance path planning and application for arc welding robot – Robotics and Computer-Integrated Manufacturing, 2022. Cited in real-time control literature.

🔍 A Collision-free path planning approach based on rule-guided lazy-PRM with repulsion field for gantry welding robots – Robotics and Autonomous Systems, 2024. Recent paper gaining citations in dynamic path planning.

📚 A survey of welding robot intelligent path optimization – Journal of Manufacturing Processes, 2021. Serves as a key reference for scholars in the welding robotics field.

🧠 Rule-based adaptive optimization strategies in robotic welding systems – Under review, targeted at IEEE Transactions on Industrial Informatics.

🔄 Multi-objective task sequencing and trajectory planning under dynamic constraints – Manuscript in progress for Journal of Intelligent Manufacturing.

Conclusion:

Dr. Xin Zhou is a standout young researcher whose work in robotic path planning and intelligent optimization has already made a significant impact in the field of automation. His research integrates high-level algorithm development with real-world engineering applications, making his contributions both academically valuable and practically useful. With a growing body of well-cited publications, involvement in both national and industry-sponsored projects, and active innovation through patents, Dr. Zhou is a strong candidate for the Best Researcher Award. His trajectory reflects both dedication and innovation, and he continues to show strong potential to lead transformative work in intelligent automation in the years ahead.

 

 

 

Iman Khosravi | Engineering | Best Researcher Award

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Dr. Iman Khosravi | Engineering | Best Researcher Award 

Assistant Professor at Department of Geomatics Engineering, Faculty of Civil Engineering & Transportation, University of Isfahan, Iran 

Dr. Iman Khosravi is an Assistant Professor at the University of Isfahan, Iran, in the Department of Geomatics Engineering, Faculty of Civil Engineering and Transportation. A specialist in Remote Sensing and Photogrammetry, he has made substantial academic and scientific contributions through research, teaching, and interdisciplinary collaborations. He has actively participated in national and industry-based projects and is recognized for his leadership in academic program development and innovation. His scientific expertise is grounded in image processing, pattern recognition, and surveying technologies, where he continues to shape the future of geomatics education and research.

profile

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Education

Dr. Khosravi obtained his Ph.D. in Remote Sensing Engineering in 2018 from the University of Tehran, one of Iran’s leading institutions for advanced studies in geographical sciences. Following his doctoral completion, he further refined his research skills as a postdoctoral researcher in the Department of Remote Sensing & GIS, Faculty of Geography, University of Tehran. This strong academic foundation enabled him to pursue a comprehensive academic and research career with a focus on both theoretical knowledge and applied innovations.

Experience

Currently serving as an Assistant Professor at the University of Isfahan, Dr. Khosravi brings years of practical and academic experience in the fields of geomatics, surveying, and remote sensing. His academic role is complemented by his service in various departmental and institutional leadership positions, including roles as Educational Deputy, Research Deputy, and Deputy of the Industry Relations Office. He also directs the Specialized Career Guidance and Employment Center, fostering industry-academia connections. His background includes supervising national projects and offering consultancy in remote sensing and surveying engineering initiatives.

Research Interest

Dr. Khosravi’s research is centered on the integration and advancement of radar and optical remote sensing, photogrammetry, and high-resolution image processing for geospatial applications. He is especially focused on the development of object-oriented image analysis and the application of pattern recognition techniques to spatial data. His work often explores the synergy between theoretical models and real-world application, including environmental monitoring and urban infrastructure assessment through advanced survey techniques. He is also committed to innovation in unmanned aerial vehicle (UAV) photogrammetry and educational methods in analytical photogrammetry.

Award

Dr. Khosravi is nominated for the Best Researcher Award in recognition of his remarkable publication record, multidisciplinary contributions, and academic leadership. With more than 25 peer-reviewed journal articles indexed in SCI and Scopus, over 300 citations, two published textbooks with ISBNs, and involvement in five research projects, he exemplifies academic excellence. His continued efforts to blend scientific rigor with educational advancement and practical implementation position him as a leader in the geomatics research community.

Publication

Among his published work, the following are selected key contributions:

“Urban Green Space Classification Using Object-Oriented Techniques” (2017, Remote Sensing Letters) – Cited by 32 articles.

“Fusion of Radar and Optical Imagery for Surface Change Detection” (2018, International Journal of Applied Earth Observation and Geoinformation) – Cited by 27 articles.

“Object-Based Image Analysis in Agricultural Monitoring” (2019, GIScience & Remote Sensing) – Cited by 19 articles.

“UAV-Based Photogrammetry for Urban Infrastructure Mapping” (2020, ISPRS International Journal of Geo-Information) – Cited by 15 articles.

“Pattern Recognition in High-Resolution Satellite Imagery” (2021, Sensors) – Cited by 11 articles.

“Integration of GIS and Remote Sensing for Land Use Planning” (2022, Land Use Policy) – Cited by 9 articles.

“Machine Learning Approaches in Remote Sensing Classification” (2023, Computers & Geosciences) – Cited by 6 articles.

Each of these articles demonstrates his commitment to advancing remote sensing techniques and their applications across diverse fields, reflecting strong interdisciplinary relevance.

Conclusion

Dr. Iman Khosravi exemplifies the qualities of a top-tier researcher through his commitment to high-impact research, publication excellence, academic authorship, and service to the scholarly and professional communities. His holistic contribution to the fields of remote sensing and geomatics engineering makes him an outstanding candidate for the Best Researcher Award. His continued pursuit of innovation and mentorship ensures that his influence extends beyond publications—nurturing future scholars and fostering cross-sector collaboration.

Zhenyu Gao | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Zhenyu Gao | Engineering | Best Researcher Award

Assoc. Prof. Dr. Zhenyu Gao | Engineering – Associate Professor at Northeastern University at Qinhuangdao, China

Zhenyu Gao is a distinguished Associate Professor at the School of Control Engineering, Northeastern University at Qinhuangdao. His academic journey is marked by groundbreaking research in control science and engineering, particularly in unmanned systems, autonomous intelligence, and intelligent transportation systems. Gao’s work is recognized globally for its innovative approaches to vehicular platoon control and multi-agent systems, contributing significantly to both theoretical advancements and practical applications in the field. His dedication to academic excellence is reflected in numerous prestigious awards, influential publications, and leadership roles in scientific communities.

Profile:

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Education:

Zhenyu Gao earned his Ph.D. in Control Science and Engineering from Dalian Maritime University, China, where he developed a strong foundation in advanced control theories. Prior to his doctoral studies, he completed his Bachelor’s degree in Automation at Shandong University of Technology. His educational background reflects a consistent trajectory of academic rigor, equipping him with the analytical skills and technical expertise necessary to excel in complex research areas.

Experience:

Currently serving as an Associate Professor, Gao has played a pivotal role in advancing research in control engineering. His professional journey includes leading several high-impact projects funded by national and provincial research foundations. Gao has also contributed as an Associate Editor for reputable journals and serves as a reviewer for top-tier publications in intelligent transportation systems and vehicular technology. His role as a mentor has guided numerous graduate students, fostering the next generation of researchers in his field.

Research Interests:

Gao’s research interests span unmanned systems, autonomous intelligence, collaborative control, multi-agent systems, and intelligent transportation systems. His work focuses on developing robust control strategies for vehicular platoons, addressing challenges related to actuator nonlinearities, sensor attacks, and real-time system performance. Gao’s innovative approaches have significantly advanced the understanding of dynamic systems and their applications in modern transportation and automation technologies.

Awards 🏆:

  • Wiley Top Downloaded Article Award (2023): Recognizing his highly cited publication in intelligent transportation systems.

  • Excellent Master Thesis Advisor of Northeastern University (2023): Honoring his mentorship and academic guidance.

  • Excellent Master Thesis Advisor of Liaoning Province (2024): Acknowledging his contributions to graduate education and research excellence.

Selected Publications 📚:

  1. Gao, Z., Li, X., Wei, Z., Liu, W., Guo, G., & Wen, S. (2025). Observer-based secure predefined-time control of vehicular platoon systems under attacks in sensors and actuators – IEEE Transactions on Intelligent Transportation Systems 📈 (Cited by 150+)
  2. Gao, Z., Liu, W., Wei, Z., & Guo, G. (2025). Adaptive finite-time prescribed performance control of vehicular platoons with multilevel threshold and asymptotic convergence – IEEE Transactions on Intelligent Transportation Systems 📊 (Cited by 120+)
  3. Gao, Z., Li, X., Wei, Z., Guo, G., Wen, S., Zhao, Y., & Mumtaz, S. (2025). Fixed-time secure control for vehicular platoons under deception attacks on both sensor and actuator via adaptive fixed-time disturbance observer – IEEE Internet of Things Journal 🚗 (Cited by 95+)
  4. Gao, Z., Li, X., Wei, Z., & Guo, G. (2024). Adaptive fuzzy finite-time asymptotic tracking control of vehicular platoons with nonsmooth asymmetric input nonlinearities – IEEE Transactions on Intelligent Transportation Systems 🚀 (Cited by 85+)
  5. Gao, Z., Wei, Z., Liu, W., & Guo, G. (2025). Adaptive finite-time prescribed performance control with small overshoot for uncertain 2-D plane vehicular platoons – IEEE Transactions on Vehicular Technology 🛰️ (Cited by 80+)
  6. Gao, Z., Sun, Z., & Guo, G. (2024). Adaptive predefined-time tracking control for vehicular platoons with finite-time global prescribed performance independent of initial conditions – IEEE Transactions on Vehicular Technology 🚦 (Cited by 75+)
  7. Gao, Z., Zhang, Y., & Guo, G. (2023). Adaptive fixed-time sliding mode control of vehicular platoons with asymmetric actuator saturation – IEEE Transactions on Vehicular Technology 🛣️ (Cited by 60+)

Conclusion:

Zhenyu Gao’s distinguished career reflects an exceptional blend of academic rigor, innovative research, and impactful mentorship. His contributions to control science and engineering, particularly in autonomous systems and intelligent transportation, have set new benchmarks in the field. Gao’s extensive publication record, combined with his leadership in research projects and academic communities, underscores his suitability for the “Best Researcher Award.” His work continues to influence and inspire advancements in control engineering, making him a worthy candidate for this prestigious recognition.

Yingyuan Liu | Engineering | Women Researcher Award

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Ms. Yingyuan Liu | Engineering | Women Researcher Award

Professor | Shanghai Normal university | China

Dr. Liu Yingyuan is an accomplished researcher and faculty member specializing in the application of artificial intelligence (AI) in fluid machinery. With a strong academic foundation and extensive professional experience, she has contributed significantly to advancing machine learning models, turbulence analysis, airfoil optimization, and fault diagnosis. Currently serving at Shanghai Normal University, Dr. Liu’s expertise bridges the intersection of AI and fluid mechanics, making her a leader in her field.

Profile

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Education

Dr. Liu Yingyuan earned her Ph.D. in Fluid Machinery from Zhejiang University in 2016, where she focused on the intricate dynamics of fluid mechanics and advanced computational methods. Her undergraduate studies in Process Equipment and Control Engineering at the China University of Petroleum (East China), completed in 2011, laid a strong foundation in engineering principles and process optimization.

Experience

Dr. Liu has been a faculty member at Shanghai Normal University, where she combines her deep research expertise with her passion for teaching. Her academic career is marked by impactful research, collaborative projects, and mentorship of students, particularly in the realm of AI applications in fluid mechanics. Her contributions extend beyond academia through her active engagement in professional committees and collaborations with industry experts.

Research Interests

Dr. Liu’s research is centered on leveraging artificial intelligence technologies to address complex challenges in fluid machinery. Her interests include machine learning modeling for turbulence, optimal airfoil shape design, and fault diagnosis in fluid machinery. By integrating AI with engineering, she has developed innovative solutions that enhance the efficiency and reliability of mechanical systems.

Awards

Dr. Liu’s innovative research has garnered recognition in the academic and professional community. Notably, her studies in machine learning-driven fault diagnosis and airfoil optimization have earned her nominations for awards in engineering and AI applications. Her commitment to excellence continues to inspire peers and students alike.

Publications

  1. Liu YY, Shen JX, Yang PP, Yang XW. A CNN-PINN-DRL driven method for shape optimization of airfoils. Engineering Application of Computational Fluid Mechanics, 2025, 19(1): 2445144.
    • Cited by: Researchers developing AI-driven aerodynamics models.
  2. Shen JX, Liu YY, Wang Leqin.* A Deep Learning-Based Method for Airfoil Parametric Modeling. Chinese Journal of Engineering Design, 2024, 31(03): 292-300.
    • Cited by: Articles on parametric modeling techniques.
  3. Liu D, Liu YY. A Deep Learning-Based Fault Diagnosis Method for Fluid Machinery with Small Samples. Journal of Shanghai Normal University (Natural Sciences), 2023, 52(02): 264-271.
    • Cited by: Studies on fault diagnosis in mechanical systems.
  4. Liu YY, Gong JG, An K, Wang LQ. Cavitation Characteristics and Hydrodynamic Radial Forces of a Reversible Pump–Turbine at Pump Mode. Journal of Energy Engineering, 2020, 146(6): 04020066.
    • Cited by: Publications on hydrodynamics and pump-turbine systems.
  5. Liu Y Y, An K, Liu H, et al. Numerical and experimental studies on flow performances and hydraulic radial forces of an internal gear pump with a high pressure. Engineering Applications of Computational Fluid Mechanics, 2019, 13: 1, 1130-1143.
    • Cited by: Research focused on internal gear pump performance.
  6. Liu Y Y, Wang L Q, Zhu Z C.* Experimental and numerical studies on the effect of inlet pressure on cavitating flows in rotor pumps. Journal of Engineering Research, 2016, 4(2): 151-171.
    • Cited by: Studies on cavitation phenomena in rotor pumps.
  7. Liu Y Y, Wang L Q, Zhu Z C.* Numerical study on flow characteristics of rotor pumps including cavitation. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2015, 229(14): 2626-2638.
    • Cited by: Articles on numerical modeling of fluid flows.

Conclusion

Dr. Liu Yingyuan exemplifies the integration of advanced engineering knowledge and AI-driven innovation. Her pioneering contributions to the fields of fluid mechanics and machinery have not only pushed technological boundaries but also inspired the next generation of engineers and researchers. Dr. Liu’s work continues to serve as a cornerstone for advancements in intelligent mechanical systems, ensuring her lasting impact on both academia and industry.

Ahmed Ibrahim | Electrical Engineering | Best Researcher Award

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Mr . Ahmed Ibrahim | Electrical Engineering | Best Researcher Award 

Graduate Research Assistant , Florida International University , United States

Ahmed Mosaad Abdelfattah Ibrahim is an accomplished electrical engineer with over eight years of experience in both industry and academia. He holds a BSc and an MSc with honors from Mansoura University, where he also served as an assistant lecturer and academic researcher. Currently, he is a Graduate Research Assistant pursuing a PhD in Electrical Engineering at Florida International University (FIU). Ahmed’s expertise spans electrification of transportation, microgrids, and renewable energy systems. He has received prestigious scholarships, including Erasmus and USAID, for his academic contributions and research excellence.

Profile

Google Scholar

Education 🎓

  • PhD in Electrical Engineering (January 2024 – Present): Pursuing a doctorate at Florida International University, focusing on energy systems research, specifically in controlling multi-port converters for microgrids and wireless power transfer systems.
  • MSc in Electrical Engineering (April 2018 – April 2021): Mansoura University, Egypt. His research explored wireless power transfer for electric vehicle charging.
  • BSc in Electrical Engineering (September 2011 – June 2016): Graduated with honors from Mansoura University, Egypt, with a thesis on smart grid load management.
  • High School: Graduated with a GPA of 3.92/4, ranking first in both school and state.

Experience 💼

  • Graduate Research Assistant, FIU, Miami, FL (January 2024 – Present): Working on power routing in microgrids and optimized energy transfer systems. Engages in writing journal papers and proposals in electrification and microgrid research.
  • Assistant Lecturer, Mansoura University, Egypt (August 2018 – December 2023): Taught various electrical engineering courses and conducted research on power systems.
  • Scientist Engineer (Volunteer), Electro Green, Canada (December 2022 – December 2023): Led R&D for Electric Mobility systems, developed prototypes, and collaborated with industry partners.
  • Electrical Site Engineer, GS E&C, Cairo, Egypt (December 2017 – November 2018): Managed construction supervision, commissioning, and maintenance of electrical systems in a major industrial project.

Research Interests 🔬

Ahmed’s research focuses on:

  1. Transportation Electrification
  2. Wireless Power Transfer Systems
  3. Hybrid Microgrid Control and Stability
  4. Magnetic Energy Routers
  5. Renewable Energy Systems
  6. Battery Management Systems

Awards 🏆

  • USAID Scholarship, Arizona State University, USA (2023): For research on enhancing the resilience and stability of microgrids.
  • Erasmus Scholarship, Hellenic Mediterranean University, Greece (2022): For research on wind energy and load management.
  • Erasmus Scholarship, University of Central Lancashire, UK (2020): For designing a control system for wireless electric vehicle charging.

Publications 📚

  • “Analysis of Inductive Characteristics for various Helical and Spiral Coil Configurations”, Mansoura Engineering Journal, Mar. 2021, Link.
  • “Hardware Implementation of Hybrid Data Driven-PI Control Scheme for Resilient Operation of Standalone DC Microgrid”, Batteries, 2024, Link.

         “State-of-the-Art Electric Vehicle Modeling: Architectures, Control, and Regulations”, Electronics, 2024, Link.

Conclusion

Ahmed Mosaad Abdelfattah Ibrahim presents a strong case for the “Best Researcher Award” due to his comprehensive academic background, diverse research experience, and leadership in both industry and academia. His international exposure and contributions to key areas of electrical engineering research further strengthen his candidacy. Focusing on a specialized area of research, enhancing his funding portfolio, and expanding his research output could further improve his prospects for the award. Overall, Ahmed demonstrates substantial potential and achievements, making him a worthy candidate for consideration.

Muhammad Noman Shahid | Mechanical Engineering | Best Researcher Award

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Mr.Muhammad Noman Shahid | Mechanical Engineering | Best Researcher Award

MS Scholar Capital University of Science and Technology Pakistan

Muhammad Noman Shahid is a dedicated Mechanical Engineer currently pursuing an MS in Mechanical Engineering at CUST, Islamabad. With a CGPA of 4.00/4.00 and a solid foundation in mechanical engineering principles, Muhammad’s expertise spans FEA, CFD, topological optimization, and CAD modeling. His academic and professional journey reflects his commitment to innovation and excellence in the engineering field.

Profile

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Education

🎓 Muhammad Noman Shahid is completing his MS in Mechanical Engineering at Capital University of Science and Technology (CUST), Islamabad, with an expected graduation date of July 2025 and a perfect CGPA of 4.00/4.00. He also holds a BS in Mechanical Engineering from the same institution, achieved from 2019 to 2023, where he worked on the “Design and Development of Continuous Passive Motion (CPM) Machine for Post Knee Surgery Rehabilitation” as his final year design project.

Experience

💼 Muhammad’s professional experience includes an internship at SABRO Air Conditioning Pakistan in Islamabad, where he gained over 200 hours of hands-on experience in various HVAC manufacturing processes. His contributions included optimizing production time, ensuring product integrity, and enhancing overall HVAC system efficiency. Muhammad has also demonstrated leadership in numerous extracurricular roles, such as Focal Person at Pakistan Nuclear Society and President Media at Al-Muhandis Society, CUST.

Research Interests

🔬 Muhammad’s research interests lie in mechanical engineering, focusing on fluid dynamics, computational modeling, topological optimization, and biomechanics. He is particularly passionate about developing innovative solutions in tissue engineering and energy storage systems.

Awards and Funding

🏅 Muhammad has received several accolades for his academic excellence and innovative projects. In 2024, he achieved the Chancellor’s Honor Roll and secured the 3rd position in Mechanical Engineering (Entrepreneurship) at the 2nd Federal Engineering Capstone Expo. He also received IGNITE funding under the National Technology Fund’s Grossroot ICT Research Initiative for his final year design project.

Publications

📚 Muhammad has published significant research work, including:

  1. “Computational Investigation of the Fluidic Properties of Triply Periodic Minimal Surface (TPMS) Structures in Tissue Engineering,” Designs, vol. 8, no. 4, 2024. Link
    • Cited by: Articles in tissue engineering and fluid dynamics journals.
  2. “A Biomechanical Approach for Computational Assessment of Heavy Payload Robots in Human-Robot Accident Scenarios for Industry 4.0,” Nanotechnology Reviews, 2023. [In Review]