Mr Guangyu Zhu | Intelligent transportation system | Best Researcher Award

Ph.D. candidate, Tsinghua University, China

Guangyu Zhu is a dedicated researcher and PhD candidate in Automotive Engineering at Tsinghua University, specializing in intelligent connected vehicles and vehicle-road collaborative systems. With a strong academic foundation from Shanghai Jiaotong University (Master’s) and Northeastern University (Bachelor’s), Guangyu has consistently excelled in his field, earning numerous awards and scholarships. His research focuses on the development strategy, cost-benefit analysis, and social value of intelligent automotive technologies. Guangyu has led significant consulting projects for the China Academy of Engineering and top international automobile companies, contributing to the advancement of China’s automotive industry. He has published multiple high-impact papers in SCI and EI-indexed journals, showcasing his expertise in intelligent transportation systems, steer-by-wire technologies, and blockchain applications in automotive fields. Guangyu’s work bridges academic research and industry innovation, aiming to shape the future of intelligent transportation.

Professional Profile

Orcid

Education 🎓

PhD in Automotive Engineering, Tsinghua University (Aug 2020–Jun 2025)
Research: Intelligent connected vehicles, vehicle-road collaborative systems, social and user value.
Awards: SAECCE Young Professional Excellent Paper, University/Institute scholarships.
Master of Engineering in Automotive Engineering, Shanghai Jiaotong University (Sep 2017–Mar 2020)
Research: Steer-by-wire systems, lane-changing decision-making.
Awards: Huawei Cup Mathematical Contest in Modeling (Second Prize).
Bachelor of Science in Applied Physics, Northeastern University (Sep 2013–Jun 2017)
GPA: 3.7/4.0 (Rank: 1/88).
Awards: Outstanding Graduate of Liaoning Province, National Scholarship, Huawei Scholarship.

Experience 💼

Lead Researcher, Consulting Project, China Academy of Engineering (Jun 2020–Apr 2021)
Defined development strategies for intelligent automotive technologies and identified key bottlenecks.
Lead Researcher, Consulting Project for Top International Automobile Company (Aug 2020–Feb 2022)
Analyzed drivers of China’s automotive industry, including pandemic impacts and digital transformation.
Lead Researcher, University-Industry Joint Research Project on Steer-by-Wire Systems (Feb 2019–Feb 2020)
Developed a steer-by-wire test bench and designed an internal model controller for precise steering.

Awards and Honors �

SAECCE Young Professional Excellent Paper Award
University-level Second-Class Scholarship (Tsinghua University)
Institute-level First-Class Scholarship (Tsinghua University)
Second Prize, Huawei Cup Mathematical Contest in Modeling (Shanghai Jiaotong University)
Outstanding Graduate of Liaoning Province (Northeastern University)
National Scholarship (Northeastern University)
Huawei Scholarship (Northeastern University)
University-level First-Class Scholarship (Northeastern University)
Second Prize, Mathematical Contest in Modeling (MCM)

Research Focus 🔍

Guangyu Zhu’s research focuses on intelligent connected vehicles and vehicle-road collaborative systems, emphasizing development strategies, cost-benefit analysis, and social value. He explores the integration of advanced technologies like blockchain and steer-by-wire systems in the automotive industry. His work also addresses traffic efficiency, energy consumption, and user-centric design in high-level autonomous driving scenarios. Guangyu’s research bridges theoretical innovation and practical applications, contributing to the sustainable growth of intelligent transportation systems in China and globally.

Publication Top Notes📚

Cost Analysis of Vehicle‐Road Cooperative Intelligence Solutions for High‐Level Autonomous Driving: A Beijing Case Study
Research on Vehicle-Road Intelligent Capacity Redistribution and Cost Sharing in the Context of Collaborative Intelligence
Research on Social Values of Vehicle-Road Collaborative Intelligent Systems: A Beijing Case Study
Blockchain Technology and Its Application in Automotive Field
Controller Design for an Automobile Steer-by-Wire System
Intelligent Vehicle Technology Innovation Development Strategy Supporting the Upgrading of Traffic
Study on Front Wheel Angle Tracking Strategy of Steering-by-Wire System
Impacts of Connected and Autonomous Vehicles with Level 2 Automation on Traffic Efficiency and Energy Consumption
Evaluation of Traffic Efficiency and Energy-Saving Benefits of L3 Smart Vehicles under the Urban Expressway Scenario
The Expansion of Value Engineering Theory and Its Application in the Intelligent Automotive Industry

Conclusion 🌟

Guangyu Zhu is a highly accomplished researcher and PhD candidate whose work in intelligent connected vehicles and vehicle-road collaborative systems is shaping the future of transportation. With a strong academic background, extensive research experience, and numerous awards, he is a leading voice in the automotive industry. His publications and projects demonstrate a commitment to innovation, sustainability, and practical applications, making him a valuable contributor to the field of intelligent transportation.

Rasha Al-Huthaifi - Transportation - Best Researcher Award

Southwest Jiaotong University - China

AUTHOR PROFILE

GOOGLE SCHOLAR

RASHA AL-HUTHAIFI: INNOVATIVE RESEARCHER IN MACHINE LEARNING AND CYBERSECURITY 🌟

EDUCATION AND EARLY CAREER JOURNEY 🎓

Rasha Al-Huthaifi is a dedicated researcher and educator with a robust background in computer science and engineering. She earned her Bachelor's degree from Sanaa University, where she excelled in teaching Object Oriented Programming using C#. Her academic journey continued with a Master's degree, focusing on enhancing antivirus security systems through innovative memory on-access scanner technologies. This groundbreaking work led to publications in prestigious journals and conferences, including the International Conference on Computer Science, Computer Engineering and Education Technologies.

EXPERTISE IN MACHINE LEARNING AND CYBERSECURITY 🔍

Rasha's expertise spans across a wide range of technologies and methodologies essential for modern cybersecurity and machine learning applications. Her proficiency includes Python programming, federated learning, and the development of secure traffic flow prediction systems using graph-based models. She has also contributed significantly to projects in data mining, bioinformatics, and information retrieval, demonstrating a versatile skill set in tackling complex technological challenges.

SIGNIFICANT PROJECT CONTRIBUTIONS 🚀

Throughout her career, Rasha has spearheaded numerous impactful projects. These include the development of FedAGAT and FedGODE systems for real-time traffic flow prediction in smart cities, leveraging federated learning and graph-based models to ensure privacy and efficiency. Her contributions extend to cybersecurity innovations such as antivirus enhancements and anti-copying software, addressing critical security vulnerabilities in software applications.

ACADEMIC AND PROFESSIONAL ENGAGEMENTS 💼

Rasha's professional journey includes roles as a PhD student at Southwest Jiaotong University, where she continues to contribute to cutting-edge research initiatives. Previously, she served as a Teacher Assistant at Jordan University of Science and Technology, imparting her knowledge in programming labs and mentoring students in computer science fundamentals.

RESEARCH IMPACT AND PUBLICATIONS 📚

Rasha's research has been published in reputable journals and conferences, highlighting her dedication to advancing the field of cybersecurity and machine learning. Her work on automatic Arabic multi-document summarizers and glaucoma disease detection algorithms reflects her commitment to leveraging technology for societal benefit and healthcare advancements.

AWARDS AND RECOGNITIONS 🏆

Rasha's academic achievements include the distinction of having the best graduation project in her Bachelor's program, showcasing her innovative spirit and academic excellence. Her contributions to cybersecurity and machine learning have earned her recognition within the academic community, underscoring her leadership and impact in the field.

FUTURE DIRECTIONS AND INNOVATIONS 🌐

Looking ahead, Rasha remains committed to pushing the boundaries of cybersecurity and machine learning research. Her future endeavors aim to integrate emerging technologies and methodologies to address global cybersecurity challenges and enhance the efficiency of machine learning applications in various domains.

NOTABLE PUBLICATION

FedAGAT: Real-time traffic flow prediction based on federated community and adaptive graph attention network 2024 (1)

Authors: Rasha Al-Huthaifi, Tianrui Li, Zaid Al-Huda, Chongshou Li

Publication date: 2024/5/1

Journal: Information Sciences

Publisher: Elsevier

FedGODE: Secure traffic flow prediction based on federated learning and graph ordinary differential equation networks

Authors: Rasha Al-Huthaifi, Tianrui Li, Zaid Al-Huda, Wei Huang, Zhipeng Luo, Peng Xie

Publication date: 2024/6/10

Journal: Knowledge-Based Systems

Publisher: Elsevier

Federated learning in smart cities: Privacy and security survey 2023 (54)

Authors: Rasha Al-Huthaifi, Tianrui Li, Wei Huang, Jin Gu, Chongshou Li

Publication date: 2023/6/1

Source: Information Sciences

Publisher: Elsevier.

Enhancements of LEACH protocol: Security and open issues 2017 (12)

Authors: Muneer Bani Yassein, Shadi Aljawarneh, Rasha K Al-huthaifi

Publication date: 2017/8/21

Conference: 2017 International Conference on Engineering and Technology (ICET)

Publisher: IEEE

Guangyu Zhu | Intelligent Transportation System | Best Researcher Award