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

Scopus

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

ORCiD

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]