Assoc. Prof. Dr. Feng Xie | intelligence systems | Best Researcher Award

Assoc. Prof. Dr. Feng Xie | intelligence systems | Best Researcher Award

School of Information Science and Technology / Sanda University, China

Dr. Feng Xie is an accomplished Associate Professor at the School of Information Science and Technology, Sanda University, China . With a career that bridges academia and industry, he has been at the forefront of intelligent transportation systems, urban mobility, and smart city innovations. As a tech entrepreneur and researcher, he has led over 500 consultancy projects globally and holds numerous patents and software copyrights. His expertise spans traffic management, AI applications, IoT, and big data analytics, with significant contributions that have earned him prestigious awards and talent program recognitions.

Publication Profile

ORCID

πŸŽ“ Education Background:

Dr. Xie earned his Ph.D. from Nanyang Technological University, Singapore , in 2002 and completed his postdoctoral research at Tongji University, China , in 2005. His academic foundation is rooted in transportation engineering, computer science, and intelligent systems, providing the basis for his interdisciplinary approach to research and technology deployment.

πŸ’Ό Professional Experience:

Currently serving as an Associate Professor at Shanghai Shanda University, Dr. Xie has also been the founder of Shanghai Van-Chance Trans. Technologies (2010–2022), where he led large-scale smart transportation projects across Asia. He worked extensively with government and industry partners, such as Singapore’s Land Transport Authority and IKEA, and directed projects like the world’s largest underground parking facility. He has also held leadership roles in cross-border technology associations and has developed systems used in cities like Beijing, Hangzhou, and Wuhan.

πŸ† Awards and Honors:

Dr. Feng Xie has been recognized with several prestigious awards, including the IES Engineering Achievement Award in 2004 for his contributions to Singapore’s i-Transport project and the Shanghai Science Progress Award in 2013. He has also been selected for elite talent programs such as the Shanghai “3310” Overseas High-level Talent Program and Nanjing “321” Leading Technology Entrepreneurship Talent Program. His innovative work has resulted in 5 patents and 9 software copyrights, solidifying his impact in both academic and applied research domains.

🧠 Research Focus:

Dr. Xie’s research is centered on Intelligent Transportation Systems (ITS), AI-driven traffic management, smart parking, indoor positioning, urban planning, and emerging tech applications in IoT and quantitative finance. His efforts in traffic simulation, traveler behavior modeling, and data-driven urban development have influenced policies and technologies in smart mobility across multiple major cities. He has collaborated with Tongji University, published in Transportation Research Board journals, and contributed to key projects with global relevance.

βœ… Conclusion:

With a unique blend of academic rigor and entrepreneurial innovation, Dr. Feng Xie exemplifies leadership in intelligent systems and sustainable urban technology 🌍. His work has profoundly shaped how modern cities approach mobility, data analytics, and smart infrastructure development. He continues to push the boundaries of AI, transportation science, and cross-border collaboration, earning him a rightful nomination for the Best Researcher Award.

πŸ“š Top Publications :

PDCG-Enhanced CNN for Pattern Recognition in Time Series Data
Journal: Elsevier – Expert Systems with Applications
Year: 2022 | Cited by: 38 articles

Modeling Traveler Behavior Using Hybrid RP/SP Data and Path-Size Logit Models
Journal: Transportation Research Record: Journal of the Transportation Research Board
Year: 2012 | Cited by: 65 articles

AI-Based Traffic Incident Management Systems: A Case Study of Singapore’s i-Transport Project
Journal: IEEE Transactions on Intelligent Transportation Systems
Year: 2014 | Cited by: 79 articles

Urban Traffic Simulation Using GPS Data Fusion and Adaptive Signal Optimization
Journal: Journal of Transportation Engineering, ASCE
Year: 2016 | Cited by: 45 articles

Smart Parking Systems Powered by IoT and AI: A Case Study of Guinness Record Facility
Journal: Sensors (MDPI)
Year: 2020 | Cited by: 54 articles

Dr. ASM Bakibillah| Intelligent Transportation Systems | Best Researcher Award

Dr. ASM Bakibillah| Intelligent Transportation Systems | Best Researcher Award

Assistant Professor, Institute of Science Tokyo, Japan

Dr. A. S. M. Bakibillah is a distinguished researcher in Mechatronics Engineering, specializing in Intelligent Transportation Systems (ITS). With a strong academic foundation and a passion for sustainable mobility solutions, he has contributed extensively to eco-driving strategies, intelligent vehicle control, and cyber-physical frameworks for connected and automated vehicles. His research integrates machine learning, optimization, and control strategies to enhance energy efficiency and safety in transportation.

Publication Profile

πŸŽ“ Education

Dr. Bakibillah earned his Ph.D. in Mechatronics Engineering from Monash University, Australia, in collaboration with Tokyo Institute of Technology, Japan, focusing on intelligent vehicle control strategies for cooperative eco-driving πŸš—πŸŒΏ. He completed his M.Sc. in Information Technology (INFOTECH) from the University of Stuttgart, Germany, specializing in Micro and Optoelectronics, where he worked on silicon tunnel field-effect transistors πŸ­πŸ”¬. His academic journey began with a B.Sc. in Electrical and Electronic Engineering from Rajshahi University of Engineering and Technology (RUET), Bangladesh, where he specialized in control systems and designed a temperature sensor-based speed controller for induction motors βš‘πŸ› οΈ.

πŸ’Ό Experience

Dr. Bakibillah has a dynamic research background in intelligent transportation and control systems, with extensive experience in academia and industry. His work has focused on eco-driving optimization, vehicle trajectory planning, smart parking solutions, and cyber-physical systems for transportation πŸš¦πŸ”. He has collaborated with top institutions in Australia, Japan, and Germany, contributing to cutting-edge innovations in automated driving and vehicle intelligence.

πŸ† Awards and Honors

Dr. Bakibillah has received numerous prestigious awards, including the Monash International Postgraduate Research Scholarship (MIPRS) πŸ…, the Monash Merit Certificate for Engineering Entrepreneurship πŸ†, and the Monash School of Engineering Publication Award (SEPA) πŸŽ–οΈ. He was also honored with the Society of Instrument and Control Engineers (SICE) Student Travel Grant and International Award βœˆοΈπŸ“œ.

πŸ”¬ Research Focus

His research primarily revolves around sustainable transportation and intelligent mobility solutions πŸš˜πŸ’‘. He specializes in energy-efficient eco-driving, cooperative automated vehicle control, and cyber-physical frameworks for traffic optimization. His work bridges the gap between artificial intelligence, control systems, and sustainable mobility, significantly impacting the future of intelligent transportation.

πŸ”š Conclusion

Dr. A. S. M. Bakibillah is a dedicated researcher in ITS, advancing the frontiers of smart mobility and eco-friendly driving solutions 🌍🚦. His innovative research, academic excellence, and multiple high-impact publications make him a valuable contributor to the field of intelligent vehicle technologies.

πŸ“š Publications

Advancements and Challenges of Visible Light Communication in Intelligent Transportation Systems: A Comprehensive Review – Photonics, 2025, Cited by πŸ“‘

Cooperative Look-ahead Lane Change System for Improving Driving Intelligence of Automated Vehicles in Critical Scenarios – IEEE Transactions on Intelligent Vehicles, 2024, Cited by πŸ“‘

Electric Vehicle Eco-Driving Strategy at Signalized Intersections Based on Optimal Energy Consumption – Journal of Environmental Management, 2024, Cited by πŸ“‘

Optimal Eco-Driving Scheme for Reducing Energy Consumption and Carbon Emissions on Curved Roads – Heliyon, 2024, Cited by πŸ“‘

Eco-Driving on Hilly Roads in a Mixed Traffic Environment: A Model Predictive Control Approach – Actuators, 2024, Cited by πŸ“‘

Eco-Friendly Smart Car Parking Management System with Enhanced Sustainability – Sustainability, 2024, Cited by πŸ“‘

Robust Vehicle Mass Estimation Using Recursive Least M-Squares Algorithm for Intelligent Vehicles – IEEE Transactions on Intelligent Vehicles, 2023, Cited by πŸ“‘

A Cyber-Physical Framework for Optimal Coordination of Connected and Automated Vehicles on Multi-Lane Freeways – Sensors, 2023, Cited by πŸ“‘

Robust Estimation of Traffic Density with Missing Data using an Adaptive-R Extended Kalman Filter – Applied Mathematics and Computation, 2022, Cited by πŸ“‘

Autonomous Vehicle Overtaking: Modeling and an Optimal Trajectory Generation Scheme – Sustainability, 2022, Cited by πŸ“‘