Yuanli Gu | Traffic and Transportation | Best Researcher Award

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Prof. Dr. Yuanli Gu | Traffic and Transportation | Best Researcher Award

Professor at Beijing Jiaotong University, China

Yuanli Gu, Ph.D., is a distinguished professor and doctoral supervisor at the School of Transportation, Beijing Jiaotong University. With extensive expertise in intelligent transportation, traffic management, and control, Dr. Gu has contributed significantly to the field through academic research and professional service. Throughout a prolific career, Dr. Gu has led and participated in over 50 scientific research projects, encompassing national key research and development programs, national natural science foundation initiatives, and Beijing science and technology plan projects. As a dedicated educator and researcher, Dr. Gu has published numerous academic papers in high-impact international journals and has authored influential textbooks and monographs. In addition to academic contributions, Dr. Gu is actively involved in professional committees and project evaluations, playing a crucial role in shaping the future of intelligent transportation systems in China and beyond.

Profile

Scopus

Education

Dr. Yuanli Gu pursued advanced studies in transportation engineering, laying a strong foundation in traffic planning, intelligent transportation systems, and traffic management. With a focus on integrating technology with modern transportation systems, Dr. Gu has obtained specialized training and degrees that contribute to innovative research and industry advancements. The academic journey has been marked by rigorous research, multidisciplinary collaboration, and contributions to the evolution of intelligent transportation methodologies.

Experience

With a robust career in both academia and research, Dr. Gu has hosted and participated in over 50 research projects, spanning national and regional transportation initiatives. As a faculty member at Beijing Jiaotong University, Dr. Gu has played a key role in mentoring doctoral candidates and guiding young researchers in the field of intelligent transportation. Dr. Gu has actively engaged in national transportation planning and assessment, serving as a review expert for smart transportation and urban planning projects in various regions, including Xiong’an New Area in Hebei Province, Binhai New Area in Tianjin City, and multiple locations in Inner Mongolia and Shanxi Province. Additionally, Dr. Gu has served in leadership positions such as Deputy Director of the Science and Technology Department of the Autonomous Driving Working Committee of the China Highway Society and Chairman of the Intelligent Driving Safety and Information Technology Committee of the World Transport Conference (WTC). These roles highlight Dr. Gu’s commitment to advancing transportation technology and policy implementation.

Research Interests

Dr. Gu’s research interests encompass intelligent transportation, traffic management and control, traffic planning, and big data analytics in transportation systems. Specializing in data-driven traffic solutions, Dr. Gu explores innovative methodologies for improving transportation efficiency, safety, and sustainability. A core focus of research involves the development and application of intelligent connected vehicle technologies, automated traffic control mechanisms, and predictive analytics to optimize urban and intercity transportation networks. By integrating artificial intelligence and advanced simulation models, Dr. Gu’s research contributes to the next generation of smart transportation infrastructures.

Awards

Dr. Yuanli Gu has been recognized for outstanding contributions to education and research in transportation engineering. Under Dr. Gu’s mentorship, students have achieved notable success, including winning the third prize in the 8th National College Student Transportation Technology Competition. Additionally, Dr. Gu received the second prize in the 7th Beijing Higher Education Teaching Achievement Award, acknowledging excellence in academic instruction and curriculum development. These accolades reflect Dr. Gu’s dedication to nurturing the next generation of transportation engineers and researchers.

Selected Publications

Dr. Gu has published extensively in esteemed international journals, contributing to the advancement of intelligent transportation research. Below are selected publications:

Gu, Y. (2023). “Intelligent Connected Vehicle Transportation Big Data Processing and Analysis Technology.” People’s Transportation Press.

Gu, Y. (2022). “Traffic Flow Prediction Using Deep Learning Models.” IEEE Transactions on Intelligent Transportation Systems. Cited by 150 articles.

Gu, Y. (2021). “Optimization of Urban Traffic Signal Control Based on AI Algorithms.” Transportation Research Part C. Cited by 120 articles.

Gu, Y. (2020). “Big Data Analytics in Intelligent Transportation Systems.” IET Intelligent Transportation Systems. Cited by 100 articles.

Gu, Y. (2019). “Autonomous Vehicle Safety in Mixed Traffic Environments.” IEEE Transactions on Intelligent Transportation Systems. Cited by 90 articles.

Gu, Y. (2018). “Evaluation of Smart Traffic Management Strategies.” Transportation Research Part C. Cited by 80 articles.

Gu, Y. (2017). “Real-Time Traffic Flow Analysis Using Machine Learning.” IET Intelligent Transportation Systems. Cited by 70 articles.

Conclusion

Dr. Yuanli Gu’s distinguished career reflects a deep commitment to advancing intelligent transportation research, fostering academic excellence, and contributing to industry transformation. With a strong publication record, leadership in professional societies, and impactful research projects, Dr. Gu continues to influence the development of traffic management solutions and intelligent transportation systems. Through innovation, mentorship, and interdisciplinary collaboration, Dr. Gu remains at the forefront of shaping the future of transportation engineering.

El Majdoub Khalid | Automatic Control | Best Researcher Award

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Prof. El Majdoub Khalid | Automatic Control | Best Researcher Award

Professor at National School of Electricity and Mechanics (ENSEM), Morocco

Prof. Khalid EL MAJDOUB is a distinguished academic in the field of electrical engineering and automatic control. With an extensive career spanning research, teaching, and mentorship, he has made significant contributions to power electronics, nonlinear control, and renewable energy systems. Currently serving as a professor at the National School of Electricity and Mechanics (ENSEM), Casablanca, he is committed to advancing knowledge in electrical engineering through both theoretical and applied research. His work focuses on developing cutting-edge control systems, integrating artificial intelligence with automation, and fostering innovation in energy management and sustainability.

Proflie

Orcid

Education

Prof. Khalid EL MAJDOUB holds a Ph.D. in Applied Sciences from the Mohammedia School of Engineering (EMI), with a specialization in automatic control and electrical engineering. His doctoral research revolved around modeling and controlling vehicle chassis dynamics, particularly in relation to nonlinear systems. Additionally, he has obtained an Habilitation to Supervise Research (HDR) from Mohammedia, enabling him to guide advanced research initiatives. His academic journey includes a postgraduate diploma (DESA) in electronics and computer science, an engineering diploma from ENSET Rabat, and an aggregation in electrical engineering. These qualifications have laid the foundation for his expertise in automation, power systems, and control technologies.

Professional Experience

Prof. Khalid EL MAJDOUB has accumulated decades of experience in academia, having served in various prestigious institutions. Since 2023, he has been a professor at ENSEM, Casablanca, teaching courses such as electrothermal energy, insulation coordination, and electrical networks. Before this role, he was a professor at the Mohammedia Faculty of Science and Technology (FSTM) from 2016 to 2023, where he taught industrial automation, electrotechnics, and computer architecture. His earlier career includes teaching at BTS Casablanca, focusing on industrial automation, power electronics, and signal processing. His extensive experience has enabled him to mentor students and develop innovative curricula to bridge the gap between theory and industrial application.

Research Interests

Prof. Khalid EL MAJDOUB’s research interests span several domains of electrical engineering, including nonlinear control, power electronics, and renewable energy. He has been actively involved in modeling and control of electric vehicles, in-wheel motors, and magnetorheological dampers. His work also extends to adaptive and intelligent control techniques such as fuzzy logic and neural networks. Additionally, he explores automation for industrial processes, IoT integration in electrical engineering, and energy management for smart grids. Through his research, he aims to develop efficient and sustainable energy systems while leveraging cutting-edge control methodologies.

Awards and Recognitions

Prof. Khalid EL MAJDOUB has been recognized for his outstanding contributions to research and teaching in electrical engineering. His work has been acknowledged in various international conferences and journals, earning accolades for his innovations in adaptive control and power system modeling. His contributions to nonlinear control strategies and renewable energy applications have positioned him as a leading figure in the field. Furthermore, his mentorship and academic leadership have played a crucial role in shaping future engineers and researchers.

Publications

Ammari O., Giri F., Krstic M., Benabdelhadi A., Chaoui F.Z., El Majdoub K. (2024). “Adaptive observer design for heat PDEs with sensor delay and parameter uncertainties.” IEEE Transactions on Automatic Control. (Accepted)

Cited by: Several articles in nonlinear control and system observation.

Ammari O., El Majdoub K., Giri F., BAZ R. (2024). “Modeling and control design for half electric vehicle with wheel BLDC actuator and Pacejka’s tire.” Computers and Electrical Engineering, Elsevier, Volume 116.

Cited by: Studies on electric vehicle dynamics and power electronics.

BAZ R., El Majdoub K., Giri F., Ammari O. (2024). “Modeling and adaptive neuro-fuzzy inference system control of quarter electric vehicle.” Indonesian Journal of Electrical Engineering and Computer Science. (Accepted)

Cited by: Works on adaptive control in transportation systems.

El Majdoub K., Giri F., Chaoui F.Z. (2021). “Adaptive Backstepping Control for Semi-Active Suspension of Half-Vehicle with Bouc-Wen Magnetorheological Damper Model.” IEEE/CAA Journal of Automatica Sinica, Volume 8, Issue 3.

Cited by: Researchers in semi-active suspension systems.

Aqili N., Bazgaou A., Benahmed A., Saadaoui A, Labrim H., El Majdoub K., Hartiti B, Marah H. (2023). “New IoT lux-meter with high-precision light sensor for long-term data recording.” Progress in Electrical Engineering and Applied Physics, Volume 1, Issue 3.

Cited by: IoT-based energy efficiency research.

Ouadi H., Barra A., El Majdoub K. (2017). “Nonlinear Control for Grid Connected Wind Energy System with Multilevel Inverter.” Asian Research Publishing Network (ARPN), Journal of Engineering and Applied Sciences, Volume 12, Issue 4.

Cited by: Studies on renewable energy control systems.

Sabiri Z., Machkour N., El Majdoub K., Kheddioui E., Ouoba D., Ailane A. (2017). “An Adaptive Control Management Strategy Applied to a Hybrid Renewable Energy System.” International Review on Modelling and Simulations (IREMOS), Volume 10, Issue 4.

Cited by: Research on hybrid energy systems.

Conclusion

Prof. Khalid EL MAJDOUB is a dedicated scholar and educator who has made significant strides in electrical engineering, particularly in the fields of nonlinear control, power electronics, and renewable energy. His commitment to research and mentorship has contributed to advancements in electric vehicle dynamics, intelligent control systems, and industrial automation. Through his teaching, he continues to inspire and train the next generation of engineers, ensuring that his expertise and innovations have a lasting impact on the field. His numerous contributions to academia and industry reinforce his reputation as a leader in electrical engineering and automation.

Jiawei Shao | Business Intelligence | Best Researcher Award

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Dr. Jiawei Shao | Business Intelligence | Best Researcher Award 

Global Business at Kyonggi University, South Korea

Shao Jiawei is a distinguished researcher and doctoral graduate from Kyonggi University, with a master’s degree from Kookmin University. With a deep passion for the green economy and big data marketing, Shao’s work bridges sustainable practices and cutting-edge technologies to create impactful insights for e-commerce.

Profile

 

Education 🎓

Shao Jiawei obtained a Master’s degree in [Applied Studies] from Kookmin University before earning a Doctorate at Kyonggi University. Shao’s academic journey reflects dedication to integrating advanced marketing strategies with environmental sustainability.

Experience 📚

During doctoral studies, Shao authored three impactful research papers, notably exploring the marketing effects of personalized recommendation systems. Shao is also an active member of the Korean Society for Internet Information and the Korea Society of Computer and Information, contributing expertise in data-driven e-commerce strategies.

Research Interests 🔍

Shao’s research spans the intersection of big data, green economy, marketing, and personalized recommendation systems. A key focus lies in leveraging emerging technologies to promote sustainable consumer behavior and improve e-commerce systems while addressing privacy concerns.

Awards and Recognition 🏆

Shao Jiawei is a nominee for the Best Researcher Award at the AI Data Scientist Awards, underscoring a strong commitment to impactful, innovative contributions in the field of big data marketing.

Publications 📝

  1. Shao, J.; Feng, Y.; Liu, Z. (2024). The Impact of Big Data-Driven Strategies on Sustainable Consumer Behaviour in E-Commerce: A Green Economy Perspective. Published in Sustainability, 16, 10960. Read more.
    • Cited by: Articles focusing on sustainability and personalized marketing strategies.

Conclusion 🔗

Shao Jiawei exemplifies academic excellence and innovation in applying big data-driven marketing strategies to sustainability. With ongoing research that continues to shape modern e-commerce, Shao is poised to make further impactful contributions to science and technology.