Maciej Szkoda | Engineering and Technology | Best Research Article Award

Published on by Research Hypothesis

Assoc. Prof. Dr. Maciej Szkoda | Engineering and Technology | Best Research Article Award

Assoc. Prof. Dr. Maciej Szkoda | Engineering and Technology | Best Research Article Award | Head of the Department Transport | Cracow University of Technology | Poland

Assoc. Prof. Dr. Maciej Szkoda is a distinguished Polish rail transport engineer whose extensive academic, research, and professional accomplishments reflect deep expertise in rail vehicle construction, machine design, transport safety, RAMS evaluation, and Life Cycle Cost methodologies, positioning him as a leading figure in railway systems engineering. Assoc. Prof. Dr. Maciej Szkoda completed his Master of Science in Mechanical Engineering and later earned his Ph.D. in Technical Sciences from the Cracow University of Technology, specializing in rail vehicles, which laid the foundation for his progressive academic journey. His professional experience includes serving as University Professor, Manager of the Department of Rail Vehicles and Transport, Director of the Institute of Rail Vehicles, and Manager of multiple specialized departments and research laboratories, demonstrating exceptional leadership in academic administration and technical innovation. His research interests encompass rail vehicle reliability, availability, maintainability, and safety analysis, risk assessment in accordance with European railway regulations, technical–economic evaluations, and certification processes for locomotives and passenger rolling stock under TSI standards. He possesses strong research skills in RAMS modeling, failure analysis, compliance assessment, LCC modeling, safety case preparation, and approval procedures for new rail system designs, supported by over two hundred R&D projects conducted at national and international levels. Assoc. Prof. Dr. Maciej Szkoda has authored one hundred seventy-eight scientific publications disseminated through reputable journals, Scopus-indexed platforms, and major engineering conferences, with participation in more than two hundred fifty scientific events related to rail reliability, safety, and vehicle operation. His professional certifications include Internal Auditor for ISO 9001, Internal Auditor for ISO/IEC 17025 laboratory systems, and Quality Assistant certification, reflecting high technical competency and adherence to global quality standards. Throughout his career, he has contributed substantially to the advancement of railway engineering, supported student development, and provided expert analysis and evaluations for industry and governmental bodies. His achievements have positioned him as a respected academic and technical authority in railway systems, earning recognition through leadership appointments, project management roles, and extensive contributions to research-based decision-making. With a strong global engagement profile, Assoc. Prof. Dr. Maciej Szkoda continues to influence transport engineering advancements, promote safety-driven innovation, and strengthen interdisciplinary research, demonstrating excellence that underscores his suitability for prestigious academic and research honors.

Profile:  Scopus | ORCID 

Featured Publications

  1. Szkoda, M. (2025). Design and testing of the propulsion system of a prototype electric vehicle intended for people with disabilities. Transport Problems.

  2. Szkoda, M. (2024). A method for assessing the criticality of failures of railway vehicle components using the FMECA method. Transport Problems.

  3. Szkoda, M. (2024). Analysis of the impact of selected factors on damage to rolling bearings of rail vehicle wheelsets. Advances in Science and Technology Research Journal.

  4. Szkoda, M. (2023). Rail vehicle RAMS evaluation strategies for safety and performance optimization.

  5. Szkoda, M. (2022). Life cycle cost methodology in the assessment of modern rail transport systems.

  6. Szkoda, M. (2021). Risk assessment approaches for innovative railway vehicle design solutions.

  7. Szkoda, M. (2020). Technical and economic analyses supporting certification of locomotives and passenger rolling stock.

 

Rongshun Chen | Engineering and Technology | Best Researcher Award

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Prof. Rongshun Chen | Engineering and Technology | Best Researcher Award

Prof. Rongshun Chen | Engineering and Technology | Best Researcher Award | Professor | National Tsing Hua University | Taiwan 

Prof. Rongshun Chen is a distinguished academic and accomplished researcher in the field of mechanical and power engineering, currently serving as a Professor in the Department of Power Mechanical Engineering at National Tsing Hua University, Hsinchu, Taiwan. Prof. Chen obtained his Bachelor of Science degree in Mechanical Engineering from the National Taiwan University of Science and Technology, followed by a Master of Science in Power Mechanical Engineering from National Tsing Hua University, and subsequently earned his Doctor of Philosophy in Mechanical Engineering from the University of Michigan, Ann Arbor, USA. Throughout his extensive academic career, Prof. Chen has made significant contributions to the advancement of robotics, control systems, and thermal management technologies, with a focus on developing intelligent sensing mechanisms, adaptive control, and mechatronic system integration. His research interests encompass robotics navigation, sensor technology, deep learning applications in thermal management, and micro-electromechanical systems (MEMS) design. Prof. Chen’s expertise extends across several domains of applied mechanics and computational modeling, enabling the development of efficient systems for industrial automation and energy-efficient engineering applications. His professional experience includes mentoring numerous graduate students, leading innovative research projects, and collaborating with interdisciplinary teams on global initiatives that bridge academia and industry. Prof. Chen has consistently demonstrated outstanding research skills in designing hybrid solvers for multi-agent motion control, developing dual-mode tactile sensors, and implementing deep learning models for predictive thermal management in data centers. His scholarly work has been published in high-impact journals and presented at major international conferences such as IEEE and Elsevier platforms, earning recognition for scientific rigor and innovation. A committed educator and leader, Prof. Chen is also an active member of the IEEE and has served in multiple academic and technical committees, contributing to the broader engineering research community. He has received numerous honors for his outstanding teaching and research achievements and continues to inspire through his leadership in robotics and thermal control engineering. Prof. Rongshun Chen’s career embodies the synergy of technical mastery, visionary thinking, and a lifelong dedication to advancing engineering science for societal benefit. His academic influence, publication record, and international collaborations firmly establish him as a leading scholar committed to advancing the future of intelligent mechanical systems and sustainable innovation through research excellence and mentorship.

Profile: Scopus | Google Scholar

Featured Publications

  1. Chen, R. (2022). Wearable and wireless performance evaluation system for sports science with an example in badminton. Scientific Reports. 7 citations.

  2. Chen, R. (2023). A Dual Spiral-Coils Tactile Sensor with Novel Driving Modes for Inductive Force and Capacitive Proximity Sensing. Conference Paper. 3 citations.

  3. Chen, R. (2023). Implementation of a Monolithic SoC Environmental Sensing Hub Using CMOS-MEMS Technique. Conference Paper. 1 citation.

  4. Chen, R. (2023). Collision-Free Navigation for Multiple Robots in Dynamic Environment. Conference Paper. 2 citations.

  5. Chen, R. (2023). Rack Inlet Temperature Prediction Based on Deep Learning. Conference Paper. 5 citations.

  6. Chen, R. (2023). A Dual Sensing Modes Capacitive Tactile Sensor for Proximity and Tri-Axial Forces Detection. Conference Paper. 12 citations.