Fangxia Zhao | Computational Methods | Best Researcher Award

Mrs. Fangxia Zhao | Computational Methods | Best Researcher Award

Associate Professor at Capital University of Economics and Business, China

👨‍🎓 Profiles

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Early Academic Pursuits 🎓

Dr. Fangxia Zhao embarked on her academic journey with a strong foundation in Transportation Engineering. Her advanced studies and research helped her gain a deep understanding of complex transportation networks and big data analytics. Over the years, she honed her expertise in the modeling of traffic systems, urban mobility, and data-driven optimization. Her academic pursuits, supported by several national-level projects, allowed her to make significant strides in theoretical research, laying the groundwork for her future professional achievements.

Professional Endeavors 💼

Dr. Zhao is currently an Associate Professor and Master’s Supervisor at the School of Management Engineering, where she also serves as the Head of the Department of Big Data. With years of academic leadership and research guidance, she has led cutting-edge projects funded by prestigious research bodies, including the Central University Research Fund and University Research Start-up Fund. Throughout her career, she has actively contributed to national and provincial research projects, consistently pushing the boundaries of transportation modeling and big data analytics.

Teaching Experience 👩‍🏫

Dr. Zhao is a dedicated educator, teaching courses such as:

  • Computer Network Technology and Applications
  • Data Structures
  • Principles and Applications of Databases
  • Python Programming Design
  • Green, Intelligent, and Shared Transportation

Her teaching focuses on equipping students with the skills needed to succeed in data science, network optimization, and smart transportation systems. She emphasizes hands-on learning and problem-solving, ensuring that her students are well-prepared for the challenges of modern transportation engineering.

Contributions and Research Focus 🔍

Dr. Zhao’s primary research interests include:

  • Complexity Modeling of Transportation Networks 🚗
  • Big Data Analysis in Transplantation 💉
  • Optimization of Urban Mobility 🏙️
  • Intelligent and Green Transportation 🌱

Her work has played a pivotal role in advancing transportation research, especially in the areas of electric vehicle behavior and network optimization. Through mathematical modeling, she has contributed to understanding how factors such as travel mode choice, vehicle scheduling, and urban road evolution influence the design of more efficient, sustainable, and intelligent transportation systems.

Academic Cites 📚

Dr. Zhao’s research has gained widespread recognition, particularly in the realms of transportation modeling and big data analytics. Her papers have been cited numerous times, including high-impact articles on the evolutionary dynamics of transportation networks, the role of electric vehicles, and the integration of bus services. Her work on the coevolution of population distribution and road networks has been particularly influential, establishing her as a key figure in the field of spatial economics and network theory.

Impact and Influence 🌟

Dr. Zhao’s influence in the academic community is reflected in her extensive publication record, including SCI-indexed papers in leading journals such as Physica A, Networks & Spatial Economics, and Plos One. With over 20 academic papers, she has made major contributions to the study of transportation networks, population distribution, and disaster prevention systems. Her research is widely cited, and her contributions are used by scholars and industry professionals to design smarter, more resilient transportation systems.

Technical Skills 💻

Dr. Zhao is a skilled data scientist, proficient in a variety of technical tools essential for big data analysis and computational modeling. Her expertise includes:

  • Python Programming 🐍
  • Database Management 🗄️
  • Network Design Optimization 🛠️
  • Data Visualization 📊
  • Algorithm Development ⚙️

These skills allow her to analyze complex datasets, develop robust optimization models, and design effective algorithms that improve transportation efficiency and sustainability. Additionally, her involvement in developing software like the School Bus Scheduling Solver and MaaS Systems highlights her technical prowess in real-world applications.

Invention Patents and Software Copyrights 💡

In addition to her research papers, Dr. Zhao holds a national invention patent for the Railway Disaster Prevention System and has developed two software copyrights:

  • School Bus Scheduling Solver
  • MaaS System Based on Knowledge Graphs

These patents and software showcase her ability to transform research ideas into practical solutions, driving innovation in the field of transportation safety and mobility services.Dr. Zhao’s legacy is marked by her pioneering work in the intersection of transportation, data science, and urban development, setting the stage for future breakthroughs in smart mobility and sustainable transportation systems.

Top Noted Publications

Multi-depot vehicle scheduling with multiple vehicle types on overlapped bus routes

  • Authors: Shang, H., Liu, Y., Wu, W., Zhao, F.
    Journal: Expert Systems with Applications, 2023

Role of electric vehicle driving behavior on optimal setting of wireless charging lane

  • Authors: Zhao, F., Shang, H., Cui, J.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2023

Integration of conventional and customized bus services: An empirical study in Beijing

  • Authors: Shang, H., Chang, Y., Huang, H., Zhao, F.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2022

Role of transportation network on population distribution evolution

  • Authors: Zhao, F.X., Shang, H.Y.
    Journal: Physica A: Statistical Mechanics and Its Applications, 2021

 

 

Jie Li | Computational Methods | Best Researcher Award

Assoc. Prof. Dr. Jie Li | Computational Methods | Best Researcher Award

Teacher at Chongqing University of Science and Technology, China

Li Jie is an accomplished doctor, associate professor, and master’s supervisor at Shanghai Jiaotong University, where he also serves as a postdoctoral fellow. As the deputy director of the 2011 Collaborative Innovation Center for Smart Security in Chongqing, he leads initiatives in smart neurosurgery and participates actively in various professional committees related to artificial intelligence and smart transportation. An Associate Editor for IEEE Transactions on Emerging Topics in Computational Intelligence, he has contributed significantly to international conferences.

Profile🎓

Early Academic Pursuits🌱

Li Jie began his academic journey with a strong focus on artificial intelligence and smart technologies, laying a solid foundation for his future endeavors. His time at Tsinghua University and later at the University of Rhode Island enriched his understanding and broadened his research perspectives, preparing him for a distinguished career in academia and industry.

Professional Endeavors 💼

As a postdoctoral fellow at Shanghai Jiaotong University, Li Jie has undertaken significant leadership roles, including serving as the deputy director of the 2011 Collaborative Innovation Center for Smart Security in Chongqing. His involvement with the Smart Neurosurgery Group and various professional committees reflects his commitment to advancing healthcare through innovative technology and collaboration.

Contributions and Research Focus 🔍

Li Jie’s research primarily centers on smart security and neurosurgery, where he utilizes artificial intelligence to enhance medical practices. He has hosted 16 funded projects and has published over 40 academic papers in high-impact journals, showcasing his dedication to contributing valuable knowledge to the field.

Impact and Influence 🌍

With a reputation as a thought leader, Li Jie has made significant contributions that have influenced both academia and industry. His role as an Associate Editor for IEEE Transactions on Emerging Topics in Computational Intelligence and participation in various international conferences underscore his influence in shaping research agendas and fostering collaborations.

Academic Citations 📚

Li Jie’s work is widely recognized, as evidenced by his 40 published papers and the acclaim received for his book, “Artificial Intelligence.” His research has garnered citations that highlight its relevance and impact, establishing him as a respected figure in his field.

Technical Skills ⚙️

Possessing a robust set of technical skills, Li Jie excels in areas such as computational intelligence, data analysis, and machine learning. His expertise in securing over 40 invention patents demonstrates his innovative approach and practical application of technology in research.

Teaching Experience 👨‍🏫

As a master’s supervisor and associate professor, Li Jie has mentored numerous students, instilling in them a passion for research and innovation. His teaching methods emphasize practical applications of theory, preparing students for successful careers in technology and science.

Legacy and Future Contributions 🔮

Li Jie’s legacy is marked by his commitment to advancing smart technologies in healthcare. Looking ahead, he aims to expand his research collaborations internationally and engage in interdisciplinary projects, furthering the impact of his work on society and technology. His vision for the future underscores a dedication to innovation that will shape the next generation of researchers and practitioners.

Publication Top Notes📖

Metric learning based multi-branch network for tongue manifestation recognition
  • Authors: Ren, S., Wu, R., Luo, Q., Wang, Y., Li, J.
    Publication Year: 2024
FASCNet: An Edge-Computational Defect Detection Model for Industrial Parts
  • Authors: Li, J., Wu, R., Zhang, S., Chen, Y., Dong, Z.
    Publication Year: 2024
Multi-scale attention-based lightweight network with dilated convolutions for infrared and visible image fusion
  • Authors: Li, F., Zhou, Y., Chen, Y., Dong, Z., Tan, M.
    Publication Year: 2024
A Mixed-Precision Transformer Accelerator With Vector Tiling Systolic Array for License Plate Recognition in Unconstrained Scenarios
  • Authors: Li, J., Yan, D., He, F., Dong, Z., Jiang, M.
    Publication Year: 2024
A novel medical text classification model with Kalman filter for clinical decision making
  • Authors: Li, J., Huang, Q., Ren, S., Deng, B., Qin, Y.

           Publication Year: 2023