Maria Victoria – SUSTAINABLE URBAN MOBILITY – Best Researcher Award

Maria Victoria - SUSTAINABLE URBAN MOBILITY - Best Researcher Award

CARTAGENA POLYTECHNIC UNIVERSITY - Spain

AUTHOR PROFILE

SCOPUS

EXPERT IN LOGISTICS RESEARCH đźš›

Maria Victoria de la Fuente AragĂłn is a seasoned researcher specializing in logistics and supply chain management. She has significantly contributed to reverse engineering methodologies and optimization strategies for business units. Her work is instrumental in improving the efficiency of logistical systems and enterprise operations.

REVERSE ENGINEERING SPECIALIST 🛠️

Maria's key research project involved the development of methodologies for applying reverse engineering to enterprise business units. This project, funded by the SÉNECA Foundation, helped uncover innovative solutions for logistics challenges, setting a foundation for more efficient operational practices in various industries.

EUROPEAN COLLABORATOR 🇪🇺

Involved in the Erasmus Project, Maria played a pivotal role in developing a European Master's degree in logistics. This initiative fostered collaboration among top universities across Europe, including Cartagena, Cardiff, Ljubljana, and Linköping, enhancing educational standards and research in logistics and supply chain management.

SUPPLY CHAIN INNOVATOR 🔄

Her contributions to supply chain management extend to distributed parameters in this field. Working with international entities, Maria's research in collaboration with the Ministry of Foreign Affairs has advanced the understanding of complex supply chain dynamics, focusing on both direct and reverse flows.

ACADEMIC COOPERATION LEADER 🌍

Maria led efforts to develop academic cooperation strategies between Costa Rica and Murcia. This project aimed at fostering sustainable and innovative capacities within agribusiness environments, contributing to the economic and social development of both regions through shared expertise and educational collaboration.

UNIVERSITY TEACHING INNOVATOR 🎓

Committed to educational advancement, Maria has been actively involved in projects aimed at improving university teaching through innovation. As part of the “Teaching Teams” project, she contributed to enhancing pedagogical practices at the Polytechnic University of Cartagena, focusing on convergence and quality in education.

CONFERENCE CONTRIBUTOR 🎤

Maria has presented her research at numerous conferences, including on topics like logistics applications, reverse engineering, and supply chain integration. Her work has been featured in key international conferences, showcasing her contributions to the field of production and operations management.

NOTABLE PUBLICATION

Title: Analysis of the behavior of logistics delivery men in pedestrian areas
Authors: Gómez-Sánchez, J.C., de-La-Fuente-Aragón, M.V., Ros-McDonnell, L.
Journal: Direccion y Organizacion
Year: 2020

Title: Development of a biking index for measuring Mediterranean cities mobility
Authors: Ros-McDonnell, L., de-La-Fuente, M.V., Ros-McDonnell, D., CardĂłs, M.
Journal: International Journal of Production Management and Engineering
Year: 2020

Title: Scheduling sustainable homecare with urban transport and different skilled nurses using an approximate algorithm
Authors: Ros-McDonnell, L., Szander, N., de-la-Fuente-AragĂłn, M.V., Vodopivec, R.
Journal: Sustainability (Switzerland)
Year: 2019

Title: Analysis of freight distribution flows in an urban functional area
Authors: Ros-McDonnell, L., de-la-Fuente-AragĂłn, M.V., Ros-McDonnell, D., CardĂłs, M.
Journal: Cities
Year: 2018

Title: Sustainable urban homecare delivery with different means of transport
Authors: Szander, N., Ros-McDonnell, L., de-la-Fuente-AragĂłn, M.V., Vodopivec, R.
Journal: Sustainability (Switzerland)
Year: 2018

Fang Yang – Transportation Engineering – Best Researcher Award

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