Tursun Mamat | Engineering | Best Researcher Award

Mr. Tursun Mamat | Engineering | Best Researcher Award

Professor from Xinjiang Agriculture University, China

Dr. Tuerxun Maimaiti is an Associate Professor at Xinjiang Agricultural University in the College of Transportation & Logistics Engineering, specializing in Traffic Engineering and Intelligent Transportation Systems. He serves as the Director of the College Laboratory and the Head of the Engineering Research Center for Intelligent Transportation. His research interests focus on driving behavior, traffic safety, vehicle-road coordination, and the environmental impact of traffic. With a strong academic background, including a Ph.D. in Transport Engineering from Nanjing Agricultural University and experience as a visiting Ph.D. student at Dalhousie University, he combines technical expertise with practical solutions for modern traffic challenges. Dr. Maimaiti is a prolific researcher with numerous published works in the field and leads multiple innovative research projects aimed at improving traffic systems, safety, and environmental sustainability.

Professional Profile

Education

Dr. Tuerxun Maimaiti holds a Ph.D. in Transport Engineering from Nanjing Agricultural University, awarded in 2017. His educational background also includes a Master’s degree in Computer Science from Xinjiang Agricultural University in 2008 and a Bachelor’s degree in Computer Application from Wuhan University in 2000. Additionally, Dr. Maimaiti pursued a visiting Ph.D. in Computer Science at Dalhousie University in 2013, where he expanded his expertise in computational techniques, particularly in the context of transportation systems. His education has equipped him with a strong foundation in both engineering and computer science, allowing him to bridge the gap between traffic engineering and technology.

Professional Experience

Dr. Maimaiti’s professional career spans over two decades, with significant experience in both academic and research settings. He began his academic career as a Teaching Assistant at Xinjiang Agricultural University from 2000 to 2005 before becoming an Associate Professor at the same institution in 2015. He also serves as the Director of the College Laboratory and Head of the Engineering Research Center for Intelligent Transportation. His leadership in these roles has contributed to the development of cutting-edge research and educational programs in the field of transportation engineering. Dr. Maimaiti has also managed several large-scale research projects, demonstrating his ability to combine academic knowledge with practical applications in the transportation sector.

Research Interests

Dr. Maimaiti’s research interests lie in several critical areas within traffic engineering and intelligent transportation systems. His primary focus includes studying driving behavior, road traffic safety, and the environmental impacts of traffic, particularly carbon emissions from urban roads. He has a strong interest in vehicle-road collaboration and its impact on traffic safety and efficiency. Additionally, Dr. Maimaiti explores the potential of digital twin technology in transportation systems and traffic simulations to improve infrastructure management and safety measures. His work aims to integrate ecological driving practices and intelligent transportation technologies to create sustainable, safe, and efficient transportation systems.

Research Skills

Dr. Maimaiti possesses a broad range of research skills that include expertise in traffic simulation, data analysis, and the application of machine learning techniques in transportation systems. He is proficient in using advanced algorithms, including YOLO v5s, for detecting pavement cracks and deep learning models for emission prediction. His research skills also extend to the development of intelligent systems for road maintenance, traffic data mining, and the optimization of toll collection systems. His ability to combine theoretical knowledge with practical applications has enabled him to lead several successful research projects that address both current and future challenges in transportation engineering.

Awards and Honors

While specific awards and honors were not listed in the provided details, Dr. Maimaiti’s impressive academic and professional record suggests that he has made significant contributions to the field of transportation engineering. His leadership in multiple high-profile research projects and the successful application of advanced technologies in real-world transportation systems reflect the recognition he has received from both academic and industry communities. His continued work in intelligent transportation systems and sustainable traffic solutions is likely to attract further recognition and accolades in the near future.

Conclusion

Dr. Tuerxun Maimaiti is an accomplished researcher and academic in the field of Traffic Engineering, with a strong focus on intelligent transportation systems and sustainable traffic management. His research on driving behavior, traffic safety, and vehicle-road collaboration has the potential to significantly impact transportation systems worldwide. Dr. Maimaiti’s expertise in utilizing advanced technologies like deep learning and digital twins enhances the practical application of his research. His extensive professional experience and leadership in large-scale projects further demonstrate his capabilities. While his impact is already notable, expanding his research into broader interdisciplinary areas and increasing the visibility of his work could further elevate his contributions. Overall, Dr. Maimaiti’s work in traffic engineering and intelligent transportation systems makes him a strong candidate for prestigious research awards.

Publications Top Notes

  1. Title: Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion
    Authors: Mamat, Tursun; Dolkun, Abdukeram; He, Runchang; Nigat, Zulipapar; Du, Hanchen
    Journal: Journal of Advanced Transportation
    Year: 2025

Weiwei Bai | Engineering | Best Researcher Award

Assoc. Prof. Dr. Weiwei Bai | Engineering | Best Researcher Award

Associate Professor from Dalian Maritime University, China

Dr. Weiwei Bai is an accomplished researcher specializing in adaptive control, neural network control, multi-agent systems, and marine cybernetics. He earned his Ph.D. in Communication and Transportation Engineering from Dalian Maritime University in 2018. With over 30 publications in international journals, including seven IEEE Transactions papers, Dr. Bai has made significant contributions to the field. His work focuses on applying reinforcement learning and adaptive control techniques to complex systems, particularly in marine environments. Dr. Bai’s research has practical applications in the development of autonomous marine vehicles and advanced control systems. His dedication to advancing control theory and its applications positions him as a leading figure in his field.

Professional Profile​

Education

Dr. Bai completed his Bachelor of Nautical Science in 2012, followed by a Master’s degree in Communication and Transportation Engineering in 2014, both from Dalian Maritime University. He continued at the same institution to earn his Ph.D. in Communication and Transportation Engineering in 2018. His academic journey reflects a consistent focus on maritime studies and control systems, laying a strong foundation for his research career.

Professional Experience

Dr. Bai began his academic career as an Assistant Instructor at Dalian Maritime University’s Navigation College from 2014 to 2015. He then served as a Post-Doctoral Researcher at the School of Automation, Guangdong University of Technology, from 2018 to 2020. Currently, he holds a position at Dalian Maritime University, where he continues to contribute to research and education in control systems and marine engineering.​

Research Interests

Dr. Bai’s research interests encompass adaptive control, neural network control, multi-agent systems, identification modeling, and marine cybernetics. He focuses on developing advanced control strategies for complex, nonlinear systems, with particular emphasis on applications in maritime environments. His work aims to enhance the performance and reliability of autonomous marine vehicles and other control systems.​

Research Skills

Dr. Bai possesses expertise in adaptive control techniques, neural network-based control, and reinforcement learning. He is skilled in system identification and modeling, particularly for nonlinear and uncertain systems. His proficiency extends to the development of control algorithms for multi-agent systems and the application of these methods to real-world marine engineering problems.​

Awards and Honors

Dr. Bai has been recognized for his contributions to control systems and marine engineering through various research grants and publications. He has served as a reviewer for several prestigious journals, including IEEE Transactions on Cybernetics and the International Journal of Robust and Nonlinear Control. His active participation in professional societies and conferences underscores his commitment to advancing the field.​

Conclusion

Dr. Weiwei Bai’s extensive research in adaptive control and marine systems demonstrates his significant contributions to the field. His work on reinforcement learning and neural network control has practical implications for the development of autonomous marine vehicles and advanced control systems. Dr. Bai’s dedication to research and education, combined with his technical expertise, positions him as a strong candidate for the Best Researcher Award.​

Publications Top Notes

  1. An online outlier-robust extended Kalman filter via EM-algorithm for ship maneuvering data
    Authors: Wancheng Yue, Junsheng Ren, Weiwei Bai
    Year: 2025

  2. Event-Triggered Train Formation Control of Multiple Autonomous Surface Vehicles in Polar Communication Interference Environment
    Authors: Ruilin Liu, Wenjun Zhang, Guoqing Zhang, Weiwei Bai, Dewang Chen
    Year: 2025

  3. Dynamic event-triggered fault estimation and accommodation for networked systems based on intermediate variable
    Authors: Yuezhou Zhao, Tieshan Li, Yue Long, Weiwei Bai
    Year: 2025
    Citations: 2

  4. Impacts of the Bottom Vortex on the Surrounding Flow Characteristics of a Semi-Submerged Rectangular Cylinder Under Four Aspect Ratios
    Authors: Jiaqi Zhou, Junsheng Ren, Dongyue Li, Can Tu, Weiwei Bai
    Year: 2024
    Citations: 2