David Santiago Pellicer Zubeldía | Transportation Engineering | Best Researcher Award

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Mr. David Santiago Pellicer Zubeldía | Transportation Engineering | Best Researcher Award

Worker | University of Zaragoza | Spain

Short Bio ✨

David Santiago Pellicer Zubeldía is an Industrial Engineer with a specialization in Mechanical and Electrical Engineering from the University of Zaragoza. He has focused his expertise on Machine & Vehicle (Mechanical) Design, particularly within the railway sector. David is passionate about research and development in this field, and he is actively searching for a PhD project to further his academic and professional goals.

Profile👤

Orcid

Education 🎓

David completed his Master’s in Industrial Engineering with a major in Machine & Vehicle (Mechanical) Design in 2021 at the University of Zaragoza. Prior to that, he earned a Degree in Industrial Technologies Engineering (Mechanical + Electrical Engineering) in 2019 from the same institution. Additionally, he pursued a Master’s in Railway Systems at TECH Technological University in 2023. David has also undertaken various specialized courses, including Python programming, SolidWorks, and ANSYS.

Experience 💼

David has accumulated significant experience in railway project development and mechanical design through roles in companies such as INECO, FutureLift S.L., and SEGULA Technologies. At INECO, he worked on I+D+i railway projects, performing technical analyses and writing technical documentation. At FutureLift S.L., he improved hydraulic lifting machines through R+D+i techniques and oversaw design updates. At SEGULA Technologies, he contributed to R+D+i tasks and railway component design, managing 3D modeling and creating technical documents in English.

Research Interest 🔬

David’s primary research interest lies in railway engineering, with a focus on improving vehicle design, wheel wear analysis, and the implementation of the Hyperloop concept. His research revolves around finding innovative solutions for enhancing transportation systems, including studies on vacuum tube transport and wheelbase sensitivity analysis.

Awards 🏆

David has earned honors for his academic achievements, including his Master’s Thesis on the rolling phenomenon of reduced-diameter railway wheels in freight wagons, completed in 2021. He was also recognized for his work on Safe and Sustainable Mobility, where he designed an e-bike and contributed to bikeway safety design in 2021.

Publications 📚

  1. Pellicer, David S. 2024. “Demonstration of the theoretical superelevation formulae for railway lines.” Read article.
    Cited by articles on railway line design.
  2. Pellicer, David S., & Emilio Larrodé. 2024. “Sensitivity Analysis of Bogie Wheelbase and Axle Load for Low-Floor Freight Wagons, Based on Wheel Wear.” Machines, 12(8), 515. Read article.
    Cited by articles on freight wagon dynamics.
  3. Pellicer, David S., & Emilio Larrodé. 2024. “Analysis of the Effectiveness of a Freight Transport Vehicle at High Speed in a Vacuum Tube (Hyperloop Transport System).” Algorithms, 17(1), 17. Read article.
    Cited by articles on futuristic transportation.
  4. Pellicer, David S. 2023. “The Problem of Ballast Pick-Up.” Trenvista, 1(1), 48. Read article.
    Cited by studies on railway ballast management.
  5. Pellicer, David S. 2020. “Conceptual Development, Analysis, and Simulation of the Transport Capacity of a Freight Transport Vehicle in Vacuum Tubes at High Speed (Hyperloop Concept).” SSRN. Read article.
    Cited by articles on Hyperloop systems.

Conclusion 🚀

David Santiago Pellicer Zubeldía’s blend of industrial engineering, railway expertise, and research capabilities positions him as a forward-thinking professional eager to push the boundaries of transportation technologies. His journey from mechanical design to Hyperloop research highlights his commitment to innovation and his readiness to contribute to cutting-edge engineering projects.

Maria Victoria – SUSTAINABLE URBAN MOBILITY – Best Researcher Award

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Maria Victoria - SUSTAINABLE URBAN MOBILITY - Best Researcher Award

CARTAGENA POLYTECHNIC UNIVERSITY - Spain

AUTHOR PROFILE

SCOPUS

EXPERT IN LOGISTICS RESEARCH 🚛

Maria Victoria de la Fuente Aragón 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., Cardós, 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-Aragón, 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-Aragón, M.V., Ros-McDonnell, D., Cardós, M.
Journal: Cities
Year: 2018

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

Fang Yang – Transportation Engineering – Best Researcher Award

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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