Fang Yang – Transportation Engineering – Best Researcher Award

Posted on 29/07/202429/07/2024 by ScienceFather

Fang Yang - Transportation Engineering - Best Researcher Award

Kunming University of Science and Technology - China

AUTHOR PROFILE

SCOPUS

EXPERT IN ELECTRIC VEHICLE CHARGING SAFETY

Fang Yang is a leading researcher in the field of electric vehicle technology, with a focus on enhancing the safety and efficiency of electric bike charging systems. His work explores innovative methods for detecting charging anomalies and promoting safe charging practices through advanced data analysis and machine learning techniques.

PROLIFIC AUTHOR IN ENGINEERING AND TRANSPORTATION

Fang has contributed significantly to academic literature with several high-impact publications. Notably, his paper on electric bike charging anomaly detection was published in Engineering Applications of Artificial Intelligence, highlighting his expertise in big data applications for transportation systems.

MAJOR PROJECT CONTRIBUTOR

Fang has played a pivotal role in various major projects, including evaluating traffic impacts and organizing traffic during the construction of Guiyang Rail Transit Line S2. His contributions extend to optimizing safety operations for new energy vehicle charging piles and researching big data public services for Kunming mobile signaling.

ADVANCING MACHINE LEARNING IN TRANSPORTATION

His research also includes leveraging machine learning to enhance the safety of electric bicycle charging systems. His work in this area has been featured in iScience, reflecting his commitment to applying cutting-edge technology to real-world transportation challenges.

RESEARCH IN URBAN RAIL TRANSIT DEMANDS

Fang's research extends to the predictability of passenger demands in urban rail transit. His study, published in Transportation, delves into short-term predictions for passenger origins and destinations, showcasing his expertise in optimizing urban transit systems.

FOCUS ON DATA-DRIVEN FORECASTING

His paper on battery swapping demands for electric bicycles, published in the Journal of Transportation Systems Engineering and Information Technology, underscores his proficiency in data-driven forecasting and its applications in improving transportation infrastructure.

DIVERSE RESEARCH EXPERIENCE

With extensive experience across multiple research projects, Fang Yang's work spans from safety analysis of new energy vehicle infrastructure to public service optimization using big data. His diverse expertise reflects a broad commitment to advancing transportation systems through innovative research.

NOTABLE PUBLICATION

Predictability of Short-Term Passengers’ Origin and Destination Demands in Urban Rail Transit.
Authors: F. Yang, C. Shuai, Q. Qian, M. He, J. Lee
Year: 2023
Journal: Transportation, 50(6), pp. 2375–2401

Online Car-Hailing Origin-Destination Forecast Based on a Temporal Graph Convolutional Network.
Authors: C. Shuai, X. Zhang, Y. Wang, F. Yang, G. Xu
Year: 2023
Journal: IEEE Intelligent Transportation Systems Magazine, 15(4), pp. 121–136

Intelligent Diagnosis of Abnormal Charging for Electric Bicycles Based on Improved Dynamic Time Warping.
Authors: C. Shuai, Y. Sun, X. Zhang, X. Ouyang, Z. Chen
Year: 2023
Journal: IEEE Transactions on Industrial Electronics, 70(7), pp. 7280–7289

Promoting Charging Safety of Electric Bicycles via Machine Learning.
Authors: C. Shuai, F. Yang, W. Wang, Z. Chen, X. Ouyang
Year: 2023
Journal: iScience, 26(1), 105786

Battery Swapping Demands Forecast for Electric Bicycles Based on Data-Driven.
Authors: C.-Y. Shuai, F. Yang, X. Ouyang, G. Xu
Year: 2021
Journal: Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 21(2), pp. 173–179

Rasha Al-Huthaifi – Transportation – Best Researcher Award

Posted on 15/06/202415/06/2024 by ScienceFather

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

Lila Dhar Sigdel – Transportation engineering – Best Researcher Award

Posted on 24/02/202424/02/2024 by ScienceFather

Lila Dhar Sigdel - Transportation engineering - Best Researcher Award

Douglas Partners Pty Ltd - Australia

AUTHOR PROFILE

Scopus

ORCID

EARLY ACADEMIC PURSUITS

Lila Dhar Sigdel embarked on his academic journey with a Bachelor of Civil Engineering from Tribhuvan University, Nepal. This foundational education provided him with a solid understanding of civil engineering principles and laid the groundwork for his future endeavors in the field of transportation engineering.

PROFESSIONAL ENDEAVORS

Sigdel's professional journey began with a role as a Graduate Geotechnical Engineer at Douglas Partners Pty Ltd. In this capacity, he gained valuable experience in conducting field investigations, assisting in design processes, and performing engineering calculations related to geotechnical structures. His role also involved collaborating with multidisciplinary teams to develop innovative solutions for complex geotechnical challenges.

CONTRIBUTIONS AND RESEARCH FOCUS

Sigdel's contributions extend beyond his professional roles to include research endeavors during his tenure as a Research Trainee at Western Sydney University. Here, he was involved in geotechnical investigation, site risk assessment, and laboratory soil testing. His research focused on foundational aspects of geotechnical engineering, contributing to the understanding of soil behavior and its implications for infrastructure projects.

IMPACT AND INFLUENCE

Sigdel's work as a Casual Academic Tutor further underscores his commitment to knowledge dissemination and academic excellence. By running tutorial classes, preparing practical works, and supervising engineering labs, he played a pivotal role in nurturing the next generation of engineers. His efforts contributed to the development of teaching experience and the enhancement of students' learning outcomes.

ACADEMIC CITATIONS

While Sigdel's academic citations may not be explicitly mentioned in the provided information, his contributions to geotechnical engineering and transportation engineering are evident through his research, professional experiences, and educational background.

LEGACY AND FUTURE CONTRIBUTIONS

Sigdel's legacy lies in his dedication to excellence in both academia and industry. His multidisciplinary expertise in geotechnical engineering and transportation engineering positions him as a valuable asset in addressing contemporary challenges in infrastructure development and transportation systems. Moving forward, Sigdel is poised to continue making significant contributions to the field through his expertise, passion, and commitment to excellence.

TRANSPORTATION ENGINEERING

Sigdel's professional and academic journey highlights his involvement in various aspects of transportation engineering, including site risk assessment for infrastructure development, supervision of project development stages to meet design standards, and the preparation of technical reports related to transportation infrastructure. His expertise in this field is demonstrated through his hands-on experience and academic achievements, making him a proficient practitioner and contributor to the advancement of transportation engineering practices.