Abdelsalam Ahmed | Engineering | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Abdelsalam Ahmed
Affiliation Tanta University
Country Egypt
Scopus ID 56311161000
Documents 41
Citations 1,115
h-index 13
Subject Area Engineering
Event International Research Excellence and Best Paper Awards
ORCID 0000-0002-0854-4411

Abdelsalam Ahmed

Abdelsalam Ahmed of the Faculty of Engineering, Tanta University, Egypt, is recognized with the Best Paper Award for research in Engineering. His recognized paper,”Integration and Validation of an Embedded Electric Drive System for EV Conversion Kits: A Practical Industrial Case Study“focuses on the integration and validation of embedded electric-drive technology for electric vehicle conversion applications. His broader research activities include electric vehicles, hybrid electric vehicles, electrical drive systems, power electronics, advanced control, and energy-storage technologies.

Abstract

This article recognizes Abdelsalam Ahmed with the Best Paper Award for research in Engineering. His recognized work,“Integration and Validation of an Embedded Electric Drive System for EV Conversion Kits: A Practical Industrial Case Study”,addresses the engineering integration and validation of an embedded electric-drive system for electric vehicle conversion applications.The research is situated within the broader field of electric vehicle propulsion, where successful vehicle electrification requires coordination among electric machines, power-electronic converters, embedded control, energy storage, and vehicle-level operation.Ahmed’s related research includes electric vehicle drive systems and advanced control methods.  [1].

Keywords

Best Paper Award, Abdelsalam Ahmed, Engineering, Electric Vehicles, EV Conversion Kits, Embedded Electric Drive, Electric Drive Systems, EV Powertrain, Electric Motors, Power Electronics, Motor Control, Vehicle Electrification, Hybrid Electric Vehicles, Electrical Machines, Model Predictive Control, Energy Storage, Battery Systems, Vehicle Validation, EV Technology, Sustainable Mobility.

Introduction

Electric vehicle conversion is an important engineering pathway for applying electric propulsion technologies to existing vehicle platforms. The conversion process requires coordinated design and integration of electric machines, batteries, power converters, embedded controllers, protection systems, and vehicle interfaces. Ahmed’s published research includes work on predictive control for induction-motor drives.  [1].

Research Profile

Abdelsalam A. Ahmed is associated with the Electrical Power and Machines Engineering Department, Faculty of Engineering, Tanta University, Tanta, Egypt. Bibliographic records for his research identify work in electrical drives, model predictive control, induction-motor control, and related engineering applications [1][2]. His research profile is connected with the development and control of electrical-drive systems, with particular relevance to electric mobility, motor control, power electronics, and advanced control strategies.  [1].

Research Contributions

The recognized work contributes to the engineering development of EV conversion systems by focusing on the integration and validation of an embedded electric-drive architecture. Such systems require coordinated operation of the electric machine, drive electronics, embedded controller, energy source, and vehicle platform. Ahmed’s related publication on model predictive control demonstrates research experience in advanced control of induction-motor drives.  [1].

Publications

The supplied bibliometric record indicates 41 documents indexed under the specified Scopus author profile. The supplied profile also records 1,115 citations and an h-index of 13. A complete publication-level assessment would require examination of the individual Scopus records, including publication titles, abstracts, journals, co-authorship, citation relationships, and research topics. [1].

Research Impact

The supplied award information records 41 documents, 1,115 citations, and an h-index of 13. These values represent the bibliometric snapshot supplied for this award profile and should be understood as profile-level metrics that may change over time.His documented research on model predictive control contributes to the broader engineering literature on high-performance electrical drives. [1].

Award Recognition

Abdelsalam Ahmed is recognized with the Best Paper Award in Engineering for the research contribution represented by “Integration and Validation of an Embedded Electric Drive System for EV Conversion Kits: A Practical Industrial Case Study.”The award profile highlights the relevance of embedded electric-drive integration to vehicle electrification and EV conversion. Ahmed’s documented publication record also includes research on model predictive control and induction-motor drives, providing additional context for his work in electrical-drive engineering [1].

Conclusion

Abdelsalam Ahmed of the Faculty of Engineering, Tanta University, Egypt, is recognized with the Best Paper Award for research in Engineering. His recognized paper focuses on the integration and validation of an embedded electric-drive system for EV conversion-kit applications. His documented research includes electrical-drive control and model predictive control for induction-motor systems, while the supplied award profile identifies broader interests in electric vehicles, hybrid electric vehicles, power electronics, and energy-storage technologies.

External Links

References

  1. Ahmed, A. A., Koh, B. K., & Lee, Y. I. (2018).A comparison of finite control set and continuous control set model predictive control schemes for speed control of induction motors.IEEE Transactions on Industrial Informatics, 14(4), 1334–1346.
    DOI::https://doi.org/10.1109/TII.2017.2758393
  2. ORCID. (n.d.).ORCID record: Abdelsalam A. Ahmed.
    ORCID.https://orcid.org/0000-0002-0854-4411
  3. Elsevier. (n.d.).Scopus author details: Abdelsalam Ahmed, Author ID 56311161000.
    Scopus.https://www.scopus.com/authid/detail.uri?authorId=56311161000
  4. Best Paper Awards. (n.d.).International Research Excellence and Best Paper Awards.
    https://bestpaperawards.com/
  5. Seoul National University of Science and Technology. (n.d.).A comparison of finite control set and continuous control set model predictive control schemes for speed control of induction motors.Research Portal
    .https://pure.seoultech.ac.kr/en/publications/a-comparison-of-finite-control-set-and-continuous-control-set-mod/

Sumant Mishra | Engineering | Fast Cited Article Award

Published on by Best Paper Awards

Fast Cited Article Award

SUMANT MISHRA
Affiliation Indian Institute of Technology Mandi
Country India
Documents 2
Citations 9
h-index 1
Subject Area Engineering
Event International Research Excellence and Best Paper Awards
ORCID 0009-0008-9732-5405

SUMANT MISHRA

SUMANT MISHRA, affiliated with Indian Institute of Technology Mandi, India, is recognized with the Fast Cited Article Award for research in the field of Engineering. The recognized article, Bridging renewable energy sources with non-isolated DC-DC converters: challenges and innovations, focuses on renewable energy sources and non-isolated DC-DC converter technologies. The supplied academic information records 2 documents, 9 citations, and an h-index of 1. [1]

Abstract

This article presents the award profile of SUMANT MISHRA, affiliated with Indian Institute of Technology Mandi, India, and recognized with the Fast Cited Article Award in Engineering. The recognized research article is titled Bridging renewable energy sources with non-isolated DC-DC converters: challenges and innovations. The research topic connects renewable energy sources with non-isolated DC-DC converter technologies. The supplied academic profile records 2 documents, 9 citations, and an h-index of 1. [1]

Keywords

Fast Cited Article Award, Sumant Mishra, Engineering, Renewable Energy, Renewable Energy Sources, Non-Isolated DC-DC Converters, DC-DC Converter Technology, Power Electronics, Power Conversion, Renewable Energy Integration, Sustainable Energy Systems, Energy Conversion, Electrical Engineering, Renewable Power Systems, Converter Technology, Engineering Innovation, Sustainable Technology, Energy Technology, Research Excellence, Academic Research, Research Impact, Citation Impact, h-index, Indian Institute of Technology Mandi, IIT Mandi, Renewable Energy Technology, Power System Engineering, Energy Infrastructure.

Introduction

Renewable energy sources are an important component of contemporary energy systems. Their integration with electrical and power-conversion technologies requires appropriate approaches for voltage regulation, power management, and energy transfer. The recognized article, Bridging renewable energy sources with non-isolated DC-DC converters: challenges and innovations, addresses the relationship between renewable energy sources and non-isolated DC-DC converter technologies. The supplied information identifies the research as focusing on challenges and innovations within this area. [1]

Biography

SUMANT MISHRA is a researcher affiliated with the Indian Institute of Technology Mandi, India, with research activity identified in the field of Engineering. His award profile is associated with the research article Bridging renewable energy sources with non-isolated DC-DC converters: challenges and innovations, which focuses on renewable energy sources and non-isolated DC-DC converter technologies. The research profile supplied for this award records 2 documents, 9 citations, and an h-index of 1. These values provide a bibliometric snapshot of the supplied academic record and may change as scholarly databases are updated and additional citations are indexed. [1]

Research Profile

SUMANT MISHRA is affiliated with Indian Institute of Technology Mandi, India, and is associated with the subject area of Engineering.The supplied academic information records 2 documents, 9 citations, and an h-index of 1. These bibliometric values represent the information supplied for this award profile and may change over time. [1]

Search Contributions

The recognized article is positioned within the engineering domains of renewable energy, power electronics, and power conversion. Its focus on non-isolated DC-DC converters relates to technologies used for voltage conversion and electrical energy management.The supplied information does not include the complete article text, detailed methodology, experimental setup, datasets, or numerical findings. Therefore, specific technical results are not attributed beyond the information provided. [1]

Research Focus

The principal research focus identified in the supplied information is the integration of renewable energy sources with non-isolated DC-DC converters.The recognized article considers the challenges and innovations associated with this technological relationship, placing the research within the broader areas of renewable energy integration, power electronics, energy conversion, and engineering technology.

Research Impact

The supplied academic information records 9 citations across 2 documents, together with an h-index of 1. These bibliometric indicators provide a quantitative description of scholarly publication and citation activity associated with the supplied researcher profile. [1]

Award Recognition

The Fast Cited Article Award recognizes the research article identified in the supplied award information for its citation-related scholarly profile. SUMANT MISHRA is presented in the supplied award information as the researcher associated with the recognized article in the field of Engineering.The award information identifies Indian Institute of Technology Mandi as the researcher’s affiliation and provides ORCID identifier 0009-0008-9732-5405 as an additional scholarly identifier. [2]

Conclusion

SUMANT MISHRA of Indian Institute of Technology Mandi, India, is recognized with the Fast Cited Article Award in the field of Engineering. The supplied academic profile records 2 documents, 9 citations, and an h-index of 1. The research topic connects renewable energy technologies with power conversion systems and identifies challenges and innovations in non-isolated DC-DC converter applications. [1]

External Links

References

  1. Mishra, S., Ahmad, R., & Srivastava, A. (2025). Bridging renewable energy sources with non-isolated DC-DC converters: Challenges and innovations. Discover Electronics, 2, Article 69.
    https://link.springer.com/article/10.1007/s44291-025-00110-w
  2. ORCID.
    Sumant Mishra – ORCID record, identifier 0009-0008-9732-5405.
    https://orcid.org/0009-0008-9732-5405

  3. Enhancing voltage regulation of a zeta converter using PI and PID controllers: a comparative study under input voltage and load variation.
    https://link.springer.com/article/10.1007/s44291-025-00125-3

“`

Wenjie feng | Engineering | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Wenjie Feng
Affiliation Shijiazhuang Tiedao University
Country China
Scopus ID 12752270200 
Documents 216
Citations 3,303
h-index 30
Subject Area Engineering
Event International Research Excellence and Best Paper Awards

Wenjie Feng

Wenjie Feng of Shijiazhuang Tiedao University, China is recognized with the Best Paper Award for research excellence in the field of Engineering. The recognized research, titled “Subcritical growth of penny-shaped fatigue cracks in a superconducting cylinder induced by the axial periodic motion of a permanent magnet”, investigates the subcritical growth behavior of penny-shaped fatigue cracks in a superconducting cylinder under the influence of axial periodic motion generated by a permanent magnet. [2]

Abstract

This article recognizes Wenjie Feng with the Best Paper Award for research excellence in Engineering. The recognized paper, “Subcritical growth of penny-shaped fatigue cracks in a superconducting cylinder induced by the axial periodic motion of a permanent magnet”, focuses on the behavior of penny-shaped fatigue cracks in a superconducting cylinder subjected to axial periodic motion induced by a permanent magnet. [2]

Keywords

Best Paper Award, Wenjie Feng, Engineering, Shijiazhuang Tiedao University, Fatigue Crack Growth, Penny-Shaped Cracks, Superconducting Cylinder, Permanent Magnet, Axial Periodic Motion, Crack Propagation, Fracture Mechanics, Fatigue Mechanics, Structural Integrity, Superconducting Systems, Mechanical Engineering.

Introduction

The recognized research examines the subcritical growth of penny-shaped fatigue cracks in a superconducting cylinder under the influence of axial periodic motion of a permanent magnet. Fatigue crack propagation is an important engineering consideration because progressive crack growth can influence the durability, reliability, and structural integrity of engineered components. [2]

Research Profile

Wenjie Feng is affiliated with Shijiazhuang Tiedao University in China and is associated with the subject area of Engineering. The provided academic information records 216 documents, 3,303 citations, and an h-index of 30. [1]

Research Contributions

The recognized paper contributes to engineering research by examining the subcritical propagation of penny-shaped fatigue cracks within a superconducting cylinder. Its focus on crack growth under axial periodic motion provides a specific framework for considering fatigue behavior in a mechanically dynamic environment. [2]

Publications

The principal publication associated with this recognition is “Subcritical growth of penny-shaped fatigue cracks in a superconducting cylinder induced by the axial periodic motion of a permanent magnet.” The supplied information identifies this paper as the research basis for the Best Paper Award recognition in Engineering. [2]

Rsearch Impact

The provided academic information records 3,303 citations across 216 documents, together with an h-index of 30. [1] These indicators provide evidence of a substantial indexed scholarly record and significant citation activity associated with the researcher’s publications.

Award Suitability

The Best Paper Award recognizes research demonstrating academic quality, relevance, originality, and meaningful contribution to its respective discipline. The recognized work by Wenjie Feng aligns with these objectives through its focused investigation of fatigue crack growth in a superconducting cylinder subjected to axial periodic motion induced by a permanent magnet. [2]

Conclusion

Wenjie Feng is recognized with the Best Paper Award for research addressing subcritical fatigue crack growth in a superconducting cylinder under axial periodic motion induced by a permanent magnet. The recognized publication, “Subcritical growth of penny-shaped fatigue cracks in a superconducting cylinder induced by the axial periodic motion of a permanent magnet,” presents a focused engineering investigation of fatigue crack behavior. [2]

External Links

Reference

  1. Wenjie Feng – Scopus Author Profile.
    Scopus Author ID 12752270200.
    https://www.scopus.com/authid/detail.uri?authorId=12752270200
  2. Best Paper Awards – International Research Excellence and Best Paper Awards.
     https://bestpaperawards.com/

Zeren Yi | Guangxi University | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

ZEREN YI
Affiliation Guangxi University
Country China
Scopus ID 57210114621
Documents 13
Citations 133
h-index 6
Subject Area Engineering
Event Best Paper Awards
ORCID 0000-0002-1809-1962

ZEREN YI

ZEREN YI of Guangxi University, China is recognized with the Best Paper Award for research excellence in the field of Engineering [1]. The recognized research, titled “Hybrid H2/H∞ Interval Observer Design for a Class of MIMO Nonlinear Systems With Interference Noise,” addresses observer design for a class of multiple-input multiple-output nonlinear systems affected by interference noise.

Abstract

This article recognizes ZEREN YI with the Best Paper Award for research excellence in Engineering [1]. The recognized paper, “Hybrid H2/H∞ Interval Observer Design for a Class of MIMO Nonlinear Systems With Interference Noise,” focuses on the design of hybrid H2/H∞ interval observers for a class of MIMO nonlinear systems affected by interference noise. The work addresses observer-design challenges involving nonlinear system behavior, uncertainty, and interference effects.

Keywords

Best Paper Award, Zeren Yi, Engineering, Hybrid H2/H∞ Observer, Interval Observer, MIMO Nonlinear Systems, Nonlinear Systems, Interference Noise, Observer Design, Robust Control, State Estimation.

Introduction

The awarded research, “Hybrid H2/H∞ Interval Observer Design for a Class of MIMO Nonlinear Systems With Interference Noise,” addresses an important engineering problem involving state observation and estimation in nonlinear systems [2]. MIMO nonlinear systems can involve complex interactions among multiple inputs and outputs, while interference noise can affect the reliability of state estimation.

The study focuses on a hybrid H2/H∞ interval-observer framework for addressing observer-design challenges in the presence of interference noise. The combination of interval-observer concepts with H2 and H∞ performance criteria represents a relevant research direction in robust control and nonlinear systems engineering [3].

Research Profile

ZEREN YI is affiliated with Guangxi University, China and is associated with the subject area of Engineering. According to the provided academic information, the researcher has 13 documents, 133 citations, and an h-index of 6.

The researcher’s Scopus Author ID is 57210114621 [2]. The provided ORCID identifier is 0000-0002-1809-1962 [3]. These identifiers support the discoverability and identification of the researcher’s scholarly profile.

Research Contributions

The recognized paper contributes to Engineering through its focus on hybrid H2/H∞ interval observer design for MIMO nonlinear systems affected by interference noise [4]. The research combines nonlinear-system observation, interval estimation, and robust performance concepts within a unified observer-design problem.

The work highlights the importance of reliable state observation in nonlinear systems where interference noise may influence available system information. By concentrating on a hybrid H2/H∞ interval-observer approach, the study contributes to research concerning robust state estimation and system monitoring [4].

Research Impact

The provided academic profile records 13 documents, 133 citations, and an h-index of 6 for ZEREN YI [2]. These bibliometric indicators demonstrate an indexed publication record and measurable citation activity associated with the researcher’s academic profile.

The recognized research has particular relevance to engineering studies involving nonlinear systems, observer design, interval estimation, and interference-noise conditions. Its emphasis on hybrid H2/H∞ observer methodology provides a focused contribution to robust state estimation research [4].

Award Suitability

The Best Paper Award recognizes research demonstrating academic quality, relevance, originality, and meaningful contribution to its respective discipline [1]. ZEREN YI’s recognized research aligns with these objectives through its investigation of hybrid H2/H∞ interval observer design for MIMO nonlinear systems with interference noise.

The paper’s focus on nonlinear-system observation, interval estimation, robust performance, and interference-noise conditions represents a technically relevant research direction within Engineering [4].

Conclusion

ZEREN YI has contributed to the field of Engineering through research focused on nonlinear systems, observer design, interval estimation, and interference-noise conditions. The recognized publication, “Hybrid H2/H∞ Interval Observer Design for a Class of MIMO Nonlinear Systems With Interference Noise,” addresses a specialized engineering problem involving state observation and robust estimation in MIMO nonlinear systems [4].

With 13 documents, 133 citations, and an h-index of 6 according to the provided academic information, the researcher demonstrates an active scholarly record [2]. The Best Paper Award recognition highlights the technical relevance of the selected research within the engineering discipline [1].

External Links

References

  1. Best Paper Awards.
    International Research Excellence and Best Paper Awards Website
  2. Zeren Yi – Scopus Author Profile.
    Scopus Author ID: 57210114621
  3. Zeren Yi – ORCID Profile.
    ORCID: 0000-0002-1809-1962

Fei HE | Engineering | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Fei He
Affiliation Anhui University of Technology
Country China
Subject Area Engineering
Event Best Paper Awards
Research Gate Fei-He-21

Fei He

Fei He of Anhui University of Technology, China, is recognized in connection with the Best Paper Award for research concerning machine vision and its application to steelmaking processes. The associated publication, “Advances in the Application of Machine Vision in Steelmaking Processes,” presents a review of machine-vision technologies used across multiple stages of steel production, including hot metal pretreatment, converter steelmaking, secondary refining, and continuous casting. The article was published in steel research international, volume 97, issue 4, pages 1813–1830, in 2026, and was first published online on 8 November 2025. The article has DOI 10.1002/srin.202500769. [1]

Abstract

The Best Paper Award recognition highlights research by Fei He and co-authors on the application of machine vision within steelmaking processes. The recognized review examines the development of machine-vision hardware and analytical algorithms, covering the progression from traditional image-processing techniques and machine learning to contemporary deep-learning approaches. It further surveys applications across hot metal pretreatment, converter steelmaking, secondary refining, continuous casting, and related steel-production operations. The publication identifies machine vision as a technological component supporting process optimization, abnormal-condition prediction, product classification and grading, and increased automation in steel manufacturing. [1]

Keywords

Machine Vision, Steelmaking, Artificial Intelligence, Deep Learning, Machine Learning, Image Processing, Intelligent Steelmaking, Converter Steelmaking, Continuous Casting, Secondary Refining, Hot Metal Pretreatment, Industrial Automation, Metallurgical Engineering, Digital Twin.

Introduction

Machine vision has become an increasingly important technology in industrial automation because it enables visual information to be acquired and processed for monitoring, classification, measurement, and decision support. In steelmaking, where production involves high temperatures, complex physical environments, continuous material movement, and demanding quality requirements, machine-vision systems can provide additional sources of information for process monitoring and control. The recognized publication examines the development and application of these systems throughout the steelmaking production chain. [1]

Research Profile

Fei He is affiliated with Anhui University of Technology in China and is associated with research in engineering and metallurgical applications of computational and machine-vision technologies. The recognized publication lists Fei He as a corresponding author and identifies the School of Metallurgical Engineering at Anhui University of Technology as the institutional affiliation. [1]

Research Contributions

The principal contribution of the recognized publication is its systematic overview of machine-vision development in steelmaking. The authors describe the evolution from conventional image-processing methods to machine-learning and deep-learning algorithms and examine how these technologies can be incorporated into industrial steel-production environments. [1]

Publications

The principal publication associated with this recognition is a peer-reviewed review article published in steel research international:

  • Wang, X., He, F., Xu, C., Wu, T., Zhuang, X., Zhang, R., Xie, W., Liu, Y., & Li, H. (2026). Advances in the Application of Machine Vision in Steelmaking Processes. steel research international, 97(4), 1813–1830. DOI: https://doi.org/10.1002/srin.202500769. [1]

Research Impact

The recognized publication contributes to research on intelligent steel manufacturing by consolidating evidence concerning the use of machine vision across different stages of steel production. By connecting visual sensing with machine-learning and deep-learning algorithms, the review provides a structured account of how visual information can support monitoring, prediction, classification, and automation. [1]

Award Suitability

The Best Paper Award recognition is associated with scholarly work demonstrating relevance, methodological organization, research value, and contribution to an academic or professional field. The publication associated with Fei He addresses a clearly defined engineering topic and provides a broad review of machine-vision technologies and their applications within steelmaking. [1]

Conclusion

Fei He is associated with engineering research at Anhui University of Technology, with the recognized publication focusing on machine vision and intelligent steelmaking. The article provides a comprehensive review of the development of machine-vision hardware and algorithms and examines their applications throughout several stages of steel production. [1]

External Links

References

    1. Wang, X., He, F., Xu, C., Wu, T., Zhuang, X., Zhang, R., Xie, W., Liu, Y., & Li, H. (2026). Advances in the Application of Machine Vision in Steelmaking Processes. steel research international, 97(4), 1813–1830. First published online 8 November 2025. DOI: https://doi.org/10.1002/srin.202500769.

Priscilla Nelson | Engineering | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

The Body Underground: A Biological Framework for Infrastructure Health, Regulation and Resilience
Priscilla Nelson
Affiliation Colorado School of Mines
Country United States
Article Title The Body Underground: A Biological Framework for Infrastructure Health, Regulation and Resilience
Scopus ID 7402246675
Article Type Research Article
Article Views 673
Reference Count 24
Award Category Best Paper Award
Event International Research Excellence and Best Paper Awards
Google Scholar 3hezpIkAAAAJ&hl

The Best Paper Award recognizes scholarly contributions that advance disciplinary knowledge through originality, methodological rigor, and measurable academic impact. This recognition highlights the work of Priscilla Nelson of the Colorado School of Mines for her article, The Body Underground: A Biological Framework for Infrastructure Health, Regulation and Resilience. Published in MDPI in 2026, the study explores infrastructure systems through a biologically inspired framework that integrates resilience, regulation, and long-term performance evaluation, contributing to contemporary engineering research and interdisciplinary infrastructure science.[1]

Abstract

This award-recognized article presents an interdisciplinary framework that interprets infrastructure systems through biological principles of health, adaptation, regulation, and resilience. The study examines how engineering networks can be assessed similarly to living systems, emphasizing continuous monitoring, response mechanisms, and long-term sustainability. By integrating concepts from biology, systems engineering, and resilience science, the research offers a novel perspective on infrastructure management. The framework supports improved understanding of infrastructure behavior under stress and changing environmental conditions while encouraging proactive maintenance and adaptive governance strategies. The work contributes to emerging discussions surrounding resilient infrastructure planning and engineering innovation.[2]

Keywords

Infrastructure Health; Urban Systems; Community Resilience; Underground Systems.

Introduction

Modern infrastructure systems face increasing demands arising from urbanization, environmental variability, aging assets, and technological complexity. Traditional engineering approaches often evaluate infrastructure through isolated performance metrics, whereas contemporary resilience research emphasizes interconnected and adaptive system behavior. The article investigates how biological concepts can provide a useful analogy for understanding infrastructure health and long-term functionality, creating a foundation for more integrated approaches to engineering management and policy development.[2]

Research Profile

Priscilla Nelson is an engineering scholar associated with the Colorado School of Mines whose research interests encompass infrastructure systems, resilience engineering, sustainability, and interdisciplinary approaches to complex societal challenges. With a Scopus Author ID of 7402246675, 63 indexed documents, 793 citations, and an h-index of 12, her scholarly record reflects substantial engagement with infrastructure-related research and engineering innovation across multiple domains.[3]

Scientific Background

Biological systems maintain functionality through regulation, adaptation, feedback mechanisms, and recovery processes. Infrastructure networks similarly require monitoring, maintenance, and adaptive responses to disturbances. Previous resilience research has explored system dynamics and risk management, but fewer studies have directly employed biological frameworks to conceptualize infrastructure health. This article builds upon interdisciplinary scholarship by connecting biological theory with engineering practice, thereby expanding the conceptual tools available for infrastructure assessment and governance.[4]

Methodology

The study employs a conceptual and analytical methodology that synthesizes biological principles with engineering resilience literature. Through comparative examination of living organisms and infrastructure systems, the research identifies common characteristics related to health assessment, regulation, adaptation, and recovery. The framework is developed through interdisciplinary integration of theoretical sources and engineering perspectives, enabling the formulation of a structured model for interpreting infrastructure performance under changing conditions and external stresses.[2]

Key Findings

The article demonstrates that infrastructure systems can be understood more effectively when viewed as dynamic entities possessing characteristics comparable to biological organisms. The framework highlights the importance of continuous monitoring, adaptive management, and systemic feedback mechanisms. It further suggests that infrastructure resilience depends not only on physical robustness but also on regulatory capacity and organizational adaptability. These findings encourage broader adoption of interdisciplinary approaches within infrastructure planning and engineering decision-making processes.[2]

Scientific Contributions

A significant contribution of the research lies in its development of a biological framework for infrastructure health that bridges conceptual boundaries between engineering and life sciences. The work advances resilience theory by introducing new interpretative models for infrastructure assessment and management. It also encourages researchers and policymakers to consider infrastructure systems as adaptive networks requiring ongoing regulation, learning, and recovery mechanisms, thereby enriching discussions surrounding sustainable engineering and resilient urban development.[4]

Conclusion

The recognition of this publication through the Best Paper Award reflects its scholarly value and interdisciplinary significance within engineering research. By integrating biological concepts into infrastructure science, the article provides a distinctive framework for understanding resilience, health, and long-term system sustainability. Its conceptual contributions support future research, policy discussions, and practical applications aimed at enhancing infrastructure performance in increasingly complex and uncertain environments.[1]

References

  1. MDPI. (2026). The Body Underground: A Biological Framework for Infrastructure Health, Regulation and Resilience.
    https://doi.org/10.3390/urbansci10040201
  2. MDPI. (2026). Buildings Journal: Urban Science.
    https://www.mdpi.com/journal/urbansci
  3. Elsevier. (n.d.). Scopus author details: Priscilla Nelson, Author ID 7402246675. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7402246675
  4. Wiley Online Library. (2025). Beyond Equations: From Models to Materials to Society: Reframing the Future of Underground Engineering.
    https://doi.org/10.1002/jci3.70012
  5. Google Scholar. (n.d.). Scholar profile and citation metrics for Priscilla Nelson.
    https://scholar.google.com/citations?user=3hezpIkAAAAJ&hl=en

Xingyu Zhou | Engineering | Best Researcher Award

Published on by Best Paper Awards

Prof. Dr. Xingyu Zhou | Engineering | Best Researcher Award 

Assistant Professor | Beijing Institute of Technology | China

Dr. Zhou Xingyu, Assistant Professor at the Beijing Institute of Technology, is an accomplished researcher specializing in renewable energy and electric vehicles. He earned his Ph.D. in Vehicle Engineering from Chongqing University in 2020, following a Bachelor’s degree in Mechanical Design, Manufacturing, and Automation from the same institution. Dr. Zhou has extensive professional experience, including his current role as Assistant Professor at the School of Mechanical Engineering and Vehicle Engineering, Beijing Institute of Technology since March 2023, and a postdoctoral fellowship at the same institute from 2020 to 2023, where he contributed to the National Engineering Research Center for Electric Vehicles. His research interests focus on vehicle powertrain optimization, intelligent energy management, stochastic and data-driven modeling, and electric vehicle motion planning for enhanced energy efficiency. He has demonstrated expertise in multi-objective optimization, machine learning applications for powertrain design, and integration of fuel cell and hybrid electric vehicle systems. Dr. Zhou has led and participated in multiple high-impact research projects, including a National Natural Science Foundation of China Youth Project and key provincial and national projects on electric vehicle energy optimization and system integration. He has published 27 Scopus-indexed documents with 448 citations and an h-index of 11, in reputed journals such as Applied Energy, Journal of Power Sources, Journal of Cleaner Production, and IEEE Transactions on Vehicular Technology, serving frequently as corresponding author. His awards and honors include the Best Student Paper Award at the 2018 Italian Conference on Machines and Mechanisms. In addition, he contributes to the academic community as a reviewer for top journals and Guest Editor of Sustainability. Dr. Zhou Xingyu’s strong technical expertise, leadership in research projects, international collaborations, and commitment to sustainable innovation make him a highly deserving candidate for the Best Researcher Award, reflecting both outstanding academic achievements and meaningful contributions to advancing green mobility and energy-efficient transportation solutions globally.

Profiles: Scopus | ORCID

Featured Publications

Sun, C., Zhang, C., Sun, F., & Zhou, X. (2022). Stochastic co-optimization of speed planning and powertrain control with dynamic probabilistic constraints for safe and ecological driving. Applied Energy, 35, 119874.

Zhou, X., Sun, C., Sun, F., & Zhang, C. (2022). Commuting-pattern-oriented optimal sizing of electric vehicle powertrain based on stochastic optimization. Journal of Power Sources, 545, 23178.

Zhou, X., Sun, F., Zhang, C., & Sun, C. (2022). Stochastically predictive co-optimization of speed planning and powertrain controls for electric vehicles driving in random traffic environment safely and efficiently. Journal of Power Sources, 528, 231200.

Zhou, X., Sun, F., Sun, C., & Zhang, C. (2022). Predictive co-optimization of speed planning and powertrain energy management for electric vehicles driving in traffic scenarios: Combining strengths of simultaneous and hierarchical methods. Journal of Power Sources, 523, 230910.

Zhou, X., Sun, F., & Sun, C. (2021). Machine learning aided methods for reducing the dimensionality of the comprehensive energy economy optimization of fuel cell powertrains. Journal of Cleaner Production, 327, 129250.

Akshatha P S | Engineering | Best Researcher Award

Published on by Best Paper Awards

Assist. Prof. Dr. Akshatha P S | Engineering | Best Researcher Award

Senior Assistant Professor | New Horizon College of Engineering | India

Dr. Akshatha P. S is a Senior Assistant Professor in the Department of Artificial Intelligence and Machine Learning at New Horizon College of Engineering, Bengaluru, where she has established herself as a committed academician and an innovative researcher. She earned her Ph.D. in Computer Science and Engineering from Bangalore University in 2023, focusing her doctoral research on enhancing the security and reliability of MQTT protocols in IoT networks. With a strong educational foundation and passion for advancing technology, she has accumulated several years of professional experience in teaching, research, and academic coordination, mentoring students while contributing significantly to the growth of her institution. Her research interests span across Computer Networks, Internet of Things, Artificial Intelligence, secure communication systems, and blockchain integration, reflecting her dedication to solving real-world problems through emerging technologies. She possesses excellent research skills, demonstrated by her prolific output of over 49 publications in high-impact platforms including IEEE Q1 journals, Scopus-indexed conferences, and Springer book chapters, along with 12 patents filed in areas such as IoT, AI, and blockchain-based solutions. Beyond research and teaching, Dr. Akshatha has actively engaged in professional memberships with IEEE, ORCID, and Scopus, which highlight her academic presence, while her leadership in organizing workshops, delivering invited talks, and contributing to knowledge dissemination reflects her broader academic and societal impact. Recognized for her contributions, she has been honored with accolades in research and innovation, further strengthening her professional reputation. In conclusion, Dr. Akshatha P. S embodies the qualities of a forward-looking researcher and dedicated educator whose work bridges academia and industry, and with her growing global presence, research vision, and commitment to student development, she continues to emerge as an inspiring figure and a deserving candidate for prestigious recognitions and awards.

Profile: Scopus | ORCID

Featured Publications

  1. Akshatha, P. S., & Dilip Kumar, S. M. (2023). Analysis and evaluation of MQTT brokers for e-Healthcare applications. IEEE Transactions on Industrial Informatics.

  2. Akshatha, P. S., & Dilip Kumar, S. M. (2023). Context-aware enhancement of buffer utilization in MQTT-based IoT communication. International Journal of Communication Networks and Distributed Systems. (In press).

  3. Akshatha, P. S., Divyashree, S., & Dilip Kumar, S. M. (2023). Priority-enabled MQTT: A robust approach to emergency event messaging. Journal of Engineering and Applied Science, Springer. (In press).

  4. Akshatha, P. S., & Dilip Kumar, S. M. (2023). MQTT and blockchain sharding: An approach to user-controlled data access with improved security and efficiency. Blockchain: Research and Applications, Elsevier. (In press).

  5. Akshatha, P. S., Dilip Kumar, S. M., & Venugopal, K. R. (2022). MQTT implementations, open issues, and challenges: A detailed comparison and survey. International Journal of Sensors, Wireless Communications and Control, 12(8), 553–576.