Meteb Altaf | Biomedical Engineering | Innovative Research Award

Published on by Robotics and Automation
Research Profile
Researcher Meteb Altaf
Affiliation King Abdulaziz City for Science and Technology
Country Saudi Arabia
Scopus ID 56326358500
Documents 20
Citations 257
h-index 9
Subject Area Biomedical Engineering
Event International Robotics and Automation Awards
ORCID 0000-0002-3256-3233

Best Researcher Award

Meteb Altaf
King Abdulaziz City for Science and Technology, Saudi Arabia

Innovative Research Award presents an academic overview of Meteb Altaf, a researcher affiliated with King Abdulaziz City for Science and Technology, Saudi Arabia. His scholarly activities are associated with Biomedical Engineering and related interdisciplinary technologies involving healthcare innovation, automation, intelligent systems, and biomedical instrumentation. Bibliometric indicators available through Scopus demonstrate a consistent publication record and measurable citation impact that reflects sustained contributions to the scientific literature.[1]

Abstract

This article summarizes the academic profile, scholarly productivity, and research achievements of Meteb Altaf. His work contributes to Biomedical Engineering through multidisciplinary approaches that combine engineering principles with healthcare technologies. The available bibliometric indicators, including publications, citations, and h-index, illustrate a sustained record of scientific productivity and international research visibility.[1]

Keywords

Biomedical Engineering, Medical Technology, Healthcare Innovation, Intelligent Systems, Robotics, Automation, Biomedical Devices, Scientific Research, Engineering Applications, Innovation.

Introduction

Biomedical Engineering integrates engineering methods with biological and medical sciences to improve healthcare technologies and clinical practice. Researchers working in this discipline contribute to diagnostic systems, medical devices, computational healthcare, and automation technologies that support modern medicine. Within this academic environment, Meteb Altaf has established a publication record recognized through international indexing databases and citation metrics.[2]

Research Profile

Meteb Altaf is affiliated with King Abdulaziz City for Science and Technology in Saudi Arabia. According to available Scopus bibliometric information, the researcher has authored twenty indexed publications, accumulated 257 citations, and achieved an h-index of 9. These indicators demonstrate continued engagement with internationally indexed research in Biomedical Engineering and associated interdisciplinary scientific fields.[1]

Research Contributions

The research contributions associated with Meteb Altaf include the development and application of engineering methodologies that support healthcare technologies, biomedical instrumentation, intelligent computational systems, and innovation in engineering solutions. Such multidisciplinary research encourages collaboration between engineering, medicine, and technology while promoting practical solutions for healthcare challenges. These activities align with current international priorities in robotics, automation, and biomedical innovation.[3]

Publications

The researcher’s scholarly publications collectively demonstrate engagement in Biomedical Engineering through peer-reviewed scientific literature. The indexed publication portfolio contributes to knowledge dissemination, supports scientific collaboration, and provides a measurable academic record through citation databases. Persistent publication activity reflects ongoing participation in international research communities.[1]

Research Impact

Citation indicators suggest that the published research has received recognition from the broader scientific community. Citation counts and h-index values are commonly used as complementary measures of scholarly influence and research visibility. Although quantitative metrics represent only one aspect of academic evaluation, they provide evidence of research dissemination and scholarly engagement within the field.[4]

Award Suitability

Based on the available academic indicators, publication record, citation performance, and contributions to Biomedical Engineering, Meteb Altaf demonstrates characteristics consistent with consideration for the Innovative Research Award presented through the International Robotics and Automation Awards. Evaluation for such recognition may consider originality, scientific quality, publication impact, interdisciplinary collaboration, and sustained research productivity alongside established assessment criteria.[5]

Conclusion

Meteb Altaf’s academic profile reflects measurable research productivity within Biomedical Engineering through internationally indexed publications, citation impact, and interdisciplinary scientific contributions. The available evidence supports recognition of continued scholarly activity and participation in research addressing engineering applications for healthcare and technological advancement.[1]

External Links

References

  1. Elsevier. (n.d.). Scopus Author Details: Meteb Altaf, Author ID 56326358500. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56326358500
  2. World Health Organization. (n.d.). Medical Devices and Biomedical Engineering.
    https://www.who.int
  3. IEEE. (2021). Biomedical Engineering and Intelligent Healthcare Technologies.
    DOI: https://doi.org/10.1109/JBHI.2021.3057598
  4. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences.
    DOI: https://doi.org/10.1073/pnas.0507655102
  5. International Robotics and Automation Awards. (2026). Innovative Research Award Evaluation
    https://roboticsandautomation.org/

Guihua Xu | Nursing Robots | International Robotics and Automation Awards

Published on by Robotics and Automation

Innovative Research Award

Researcher: Guihua Xu
Institution: School of Nursing, Nanjing University of Chinese Medicine

Researcher Information
Affiliation School of Nursing, Nanjing University of Chinese Medicine
Country China
Scopus ID 55629892300
Documents 118
Citations 1977
h-index 23
Subject Area Nursing Robots
Event International Robotics and Automation Awards
ORCID 0009-0002-2623-4991

Guihua Xu is a researcher affiliated with the School of Nursing, Nanjing University of Chinese Medicine, China. The research profile reflects scholarly contributions in nursing robotics, intelligent healthcare technologies, and interdisciplinary healthcare innovation. Through sustained academic productivity, peer-reviewed publications, and measurable citation impact, the researcher has contributed to the advancement of evidence-based nursing science and healthcare automation.[1]

Abstract

Guihua Xu has established an academic record characterized by research in nursing robotics, intelligent healthcare systems, and patient-centered technological innovation. The publication portfolio demonstrates interdisciplinary collaboration involving nursing science, clinical practice, and healthcare engineering while maintaining measurable scholarly visibility through citations and research dissemination.[2]

Keywords

Nursing Robots, Intelligent Healthcare, Clinical Nursing, Medical Robotics, Healthcare Innovation, Digital Health, Artificial Intelligence, Nursing Science, Patient Care Technology, Healthcare Automation.

Introduction

Contemporary healthcare increasingly integrates robotics and intelligent technologies to improve patient outcomes and clinical efficiency. Researchers working in this multidisciplinary field contribute to evidence-based practice by evaluating technological applications within nursing environments. Guihua Xu’s academic work aligns with these developments through publications addressing healthcare innovation and nursing practice.[3]

Research Profile

According to the provided academic metrics, the research profile includes 118 indexed publications, 1,977 citations, and an h-index of 23. These indicators demonstrate sustained scholarly productivity and continuing influence within nursing-related research domains.[1]

Research Contributions

The research contributions encompass nursing robotics, healthcare technology implementation, digital clinical practice, patient safety, interdisciplinary collaboration, and evidence-based healthcare innovation. These activities contribute to the broader development of technology-assisted nursing and healthcare delivery systems.[4]

Publications

The publication portfolio consists of peer-reviewed journal articles indexed within major scholarly databases. Collectively, these publications demonstrate continuing engagement with healthcare innovation, nursing science, and clinical research while supporting knowledge dissemination through internationally recognized academic journals.[2]

Research Impact

Citation performance and publication activity indicate that the research has attracted scholarly attention across healthcare disciplines. Such impact reflects continued academic engagement and contributes to advancing nursing research, healthcare technologies, and evidence-informed clinical practice.[1]

Award Suitability

The documented publication record, citation metrics, interdisciplinary research activities, and contributions to nursing robotics provide a strong academic foundation for consideration under the Innovative Research Award category presented during the International Robotics and Automation Awards. The profile demonstrates sustained scholarly achievement consistent with the objectives of recognizing impactful scientific research.[5]

Conclusion

Guihua Xu has developed a research profile characterized by measurable scholarly productivity, interdisciplinary healthcare research, and contributions to nursing robotics. Continued publication activity and research dissemination support ongoing advancements in intelligent healthcare technologies and nursing science.[5]

External Links

References

  1. Elsevier. (n.d.). Scopus Author Details: Guihua Xu, Author ID 55629892300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=55629892300&source=sd
  2. ORCID. (n.d.). Guihua Xu Research Profile.
    https://orcid.org/0009-0002-2623-4991
  3. International Journal of Nursing Studies. Healthcare technology and nursing innovation.
    DOI:https://doi.org/10.1016/j.ijnurstu.2022.104298
  4. International Robotics and Automation Awards. Award information and evaluation framework.
    https://roboticsandautomation.org/
  5. Crossref. Digital Object Identifier springer
    https://link.springer.com/article/10.1186/s12984-025-01675-z

Keyan He | Autonomous Robot Navigation | Innovative Research Award

Published on by Robotics and Automation

Innovative Research Award

Research Profile
Researcher Keyan He
Affiliation National University of Defense Technology
Country China
Scopus ID 56304883200
Documents 14
Citations 54
h-index 4
Subject Area Autonomous Robot Navigation
Event International Robotics and Automation Awards
ORCID 0000-0001-6426-7626

Keyan He
National University of Defense Technology

Keyan He is a researcher affiliated with the National University of Defense Technology, China, whose academic work focuses on CSLAM and multi-navigation technologies. His scholarly activities contribute to the advancement of autonomous robotic systems, intelligent navigation, and integrated localization methods applicable to complex environments. According to publicly available bibliographic records, his publications have received academic recognition through citations and demonstrate continuing engagement with robotics and navigation research.[1]

Abstract

The Innovative Research Award recognizes researchers whose scholarly work demonstrates originality, technical rigor, and measurable academic contribution. Keyan He’s research emphasizes CSLAM and multi-navigation technologies that support robotic perception, localization, and autonomous operation in dynamic environments. His publication record and citation performance indicate active participation in advancing robotics-related research and interdisciplinary navigation systems.[1]

Keywords

CSLAM, Multi-navigation, Robotics, Autonomous Systems, Localization, Mapping, Sensor Fusion, Intelligent Navigation, Artificial Intelligence, Mobile Robotics

Introduction

Modern robotics increasingly relies on reliable localization, mapping, and navigation techniques capable of operating under uncertain environmental conditions. Research involving collaborative SLAM, multi-navigation strategies, and sensor integration plays an essential role in improving robotic autonomy. Within this context, Keyan He contributes to research addressing these technical challenges through studies that integrate navigation algorithms and intelligent robotic systems.[2]

Research Profile

The available academic record identifies Keyan He as an active contributor to robotics and navigation research. His Scopus profile lists fourteen indexed documents with fifty-four citations and an h-index of four, reflecting a growing body of scholarly work. His research primarily investigates CSLAM methodologies, integrated navigation frameworks, and robotic perception technologies that support autonomous platforms.[1]

Research Contributions

  • Research on collaborative simultaneous localization and mapping technologies.
  • Development of multi-navigation frameworks for autonomous robotic systems.
  • Integration of multiple sensing approaches to improve localization accuracy.
  • Advancement of intelligent navigation algorithms applicable to complex operational environments.
  • Contribution to robotics literature through peer-reviewed scientific publications.[3]

Publications

The published research portfolio includes studies in robotics, localization, mapping, intelligent navigation, and related engineering applications. These publications collectively contribute to the growing body of knowledge supporting autonomous robotic platforms and integrated navigation technologies. Representative works are accessible through Scopus indexing and associated DOI records.[4]

Research Impact

Citation indicators suggest that the research has attracted measurable scholarly attention within robotics and navigation communities. The combination of indexed publications, citation activity, and continuing research output demonstrates meaningful engagement with contemporary developments in intelligent robotic systems and localization technologies. Such contributions support ongoing innovation in autonomous navigation research.[1]

Award Suitability

Based on publicly available scholarly indicators and the documented focus on CSLAM and multi-navigation research, Keyan He demonstrates characteristics aligned with the objectives of the Innovative Research Award presented during the International Robotics and Automation Awards. His research addresses significant technological challenges in autonomous robotics while contributing to scientific knowledge through peer-reviewed publications and recognized academic dissemination.[5]

Conclusion

Keyan He’s research profile reflects sustained academic involvement in robotics, CSLAM, and multi-navigation technologies. His publication record, citation metrics, and research themes illustrate continued contributions to intelligent robotic navigation and autonomous system development. These achievements provide an appropriate academic basis for recognition through the Innovative Research Award.

References

  1. Elsevier. (n.d.). Scopus author details: Keyan He, Author ID 56304883200. Scopus.
    https:/www.scopus.com/authid/detail.uri?authorId=56304883200
  2. ORCID. (n.d.). Research activities and academic profile of Keyan He.
    https://orcid.org/0000-0001-6426-7626
  3. IEEE. Representative robotics research publication.
    DOI:https://doi.org/10.1109/LRA.2021.3057560
  4. Crossref. Scholarly publication metadata indexed through DOI services.
    https://link.springer.com/article/10.1007/s10791-025-09607-0
  5. International Robotics and Automation Awards. Official Award Website.
    https://roboticsandautomation.org/

Athanasios Sypsas | Reinforcement Learning in Robotics | Innovative Research Award

Published on by Robotics and Automation

Innovative Research Award

Research Profile
Researcher Athanasios Sypsas
Affiliation Hellenic Open University
Country Greece
Scopus ID 56516889900
Documents 12
Citations 69
h-index 3
Subject Area Reinforcement Learning in Robotics
Event International Robotics and Automation Awards
ORCID 0000-0001-8301-4763

Athanasios Sypsas
Hellenic Open University, Greece

Athanasios Sypsas is a researcher affiliated with the Hellenic Open University, Greece, whose scholarly work focuses on reinforcement learning, intelligent educational systems, and virtual learning environments. His research examines the integration of machine learning methodologies into immersive educational platforms, emphasizing adaptive learning experiences and autonomous decision-making models. His publication record, indexed in Scopus, reflects contributions to educational technology and artificial intelligence applications that support interactive and personalized digital learning.[1] [2]

Abstract

The academic work of Athanasios Sypsas investigates the application of reinforcement learning techniques within educational virtual environments to improve learner engagement, adaptive instruction, and intelligent tutoring systems. His research combines principles from artificial intelligence, educational technology, and interactive simulation to enhance digital learning experiences. The research portfolio demonstrates interdisciplinary collaboration and contributes to the growing body of literature on AI-assisted education.[2][3]

Keywords

Reinforcement Learning, Educational Technology, Artificial Intelligence, Virtual Learning Environments, Intelligent Tutoring Systems, Adaptive Learning, Human-Computer Interaction, Digital Education, Machine Learning, Robotics Education.

Introduction

Modern educational technologies increasingly rely on artificial intelligence to personalize learning pathways and improve learner outcomes. Athanasios Sypsas  has contributed to this evolving discipline by exploring reinforcement learning methodologies that enable educational systems to adapt dynamically to user interactions. His work aligns with contemporary developments in intelligent educational software and virtual learning environments.[2][4]

Research Profile

According to indexed scholarly records, Athanasios Sypsas has authored 12 publications with 69 citations and an h-index of 3. His academic activities emphasize reinforcement learning, adaptive educational systems, and virtual environments, demonstrating sustained engagement in interdisciplinary research that combines computer science with educational innovation.[1]

Research Contributions

His contributions include investigations into intelligent decision-making algorithms, adaptive educational simulations, and reinforcement learning strategies that optimize instructional processes within digital environments. These studies support broader efforts to integrate AI technologies into modern education while maintaining pedagogical effectiveness and measurable learning outcomes.[3][4]

Publications

The publication portfolio encompasses peer-reviewed conference papers and journal articles focusing on reinforcement learning applications, intelligent educational environments, and virtual simulation technologies. These publications contribute to discussions surrounding AI-enabled educational innovation and computational learning methodologies.[3]

Research Impact

Citation metrics indicate that the research has been referenced by subsequent scholarly works within educational technology and artificial intelligence literature. The combination of publications, citations, and interdisciplinary subject focus reflects ongoing academic engagement in developing intelligent learning environments and computational education research.[1][4]

Award Suitability

The research profile demonstrates relevance to the objectives of the International Robotics and Automation Awards through its emphasis on intelligent systems, reinforcement learning, and autonomous decision-making within educational virtual environments. These areas intersect with robotics, automation, and artificial intelligence, supporting recognition within interdisciplinary innovation-focused academic award programs.[2][4]

Conclusion

Athanasios Sypsas has developed a scholarly profile centered on reinforcement learning and virtual educational technologies. His research contributes to advancing intelligent educational systems through computational methodologies that support adaptive learning and interactive digital environments. The documented publication metrics and interdisciplinary research focus illustrate continued participation in contemporary artificial intelligence and educational technology research.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Athanasios Sypsas, Author ID 56516889900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56516889900
  2. ORCID. (n.d.). ORCID record for Athanasios Sypsas.
    https://orcid.org/0000-0001-8301-4763
  3. Springer. (2020). Advances in Intelligent Systems and Computing. DOI:
    https://doi.org/10.1007/978-3-030-49663-0
  4. Sutton, R. S., & Barto, A. G. (2018). Reinforcement Learning: An Introduction (2nd Edition).
    DOI: https://doi.org/10.1109/TNN.1998.712192

Israel Ogra | Artificial Intelligence | Innovative Research Award

Published on by Robotics and Automation

Innovative Research Award

Israel Ogra
UNESCO International Centre for Biotechnology

Israel Ogra
Affiliation UNESCO International Centre for Biotechnology
Country Nigeria
Scholar ID rfWR3R0AAAAJ
Documents 47
Citations 205
h-index 8
Subject Area Artificial Intelligence
Event International Robotics and Automation Awards

Israel Ogra, affiliated with the UNESCO International Centre for Biotechnology, Nigeria. The profile presents an overview of research accomplishments, publication contributions, citation impact, and the relevance of the candidate’s work to the objectives of the International Robotics and Automation Awards.[1]

Abstract

Israel Ogra has developed a scholarly portfolio characterized by interdisciplinary research activities associated with Artificial Intelligence and related computational technologies. Through peer-reviewed publications, collaborative scientific initiatives, and knowledge dissemination efforts, the researcher has contributed to advancing evidence-based methodologies and innovative applications relevant to automation, intelligent systems, and data-driven decision-making. Citation indicators and publication metrics demonstrate measurable academic engagement within the global research community.[2]

Keywords

Artificial Intelligence, Intelligent Systems, Robotics Research, Machine Learning, Computational Science, Automation Technologies, Scientific Innovation, Data Analytics, Knowledge Engineering, Research Excellence.

Introduction

The growing influence of Artificial Intelligence across academic, industrial, and societal domains has generated significant opportunities for interdisciplinary research and innovation. Researchers working in this field contribute to algorithmic development, intelligent automation, predictive modeling, and emerging technologies that support scientific progress. Israel Ogra’s academic record reflects sustained participation in these evolving research areas through publication activity, collaborative scholarship, and professional engagement.[1]

Research Profile

The research profile of Israel Ogra demonstrates a commitment to advancing scientific understanding through systematic investigation and scholarly communication. Affiliated with the UNESCO International Centre for Biotechnology, the researcher has contributed to publications addressing contemporary challenges and opportunities associated with Artificial Intelligence and computational innovation.[2]

  • Institutional Affiliation: UNESCO International Centre for Biotechnology.
  • Country of Academic Activity: Nigeria.
  • Research Domain: Artificial Intelligence.
  • Documents Indexed: 47.
  • Total Citations: 205.
  • h-index: 8.

Research Contributions

Research contributions attributed to Israel Ogra encompass the application of intelligent computational techniques, analytical frameworks, and technology-driven solutions. These efforts support scientific inquiry and facilitate knowledge transfer across multidisciplinary environments. The research output reflects an emphasis on innovation, methodological rigor, and practical relevance.[3]

  • Development and evaluation of AI-enabled analytical approaches.
  • Participation in interdisciplinary scientific collaborations.
  • Contribution to peer-reviewed scholarly literature.
  • Support for knowledge dissemination through academic publishing.
  • Promotion of innovation within emerging technology ecosystems.

Publications

The publication record includes peer-reviewed articles and scholarly contributions indexed within recognized academic databases. These publications contribute to the dissemination of research findings and support broader scientific dialogue within Artificial Intelligence and related disciplines.[1]

  1. Research articles addressing Artificial Intelligence applications and computational methodologies.
  2. Collaborative studies involving interdisciplinary scientific investigations.
  3. Conference and journal contributions supporting technological innovation.
  4. Academic outputs contributing to global scientific discourse.

Research Impact

Research impact may be assessed through citation activity, scholarly visibility, and contributions to knowledge advancement. With 205 citations and an h-index of 8, Israel Ogra’s work demonstrates measurable engagement from the academic community. Such indicators suggest that the research has informed ongoing scholarly discussions and contributed to the development of related investigations.[2]

The integration of Artificial Intelligence methodologies into contemporary scientific research continues to influence technological progress, industrial transformation, and educational development. Contributions within these areas provide value through evidence-based innovation and practical applicability.[3]

Award Suitability

The Innovative Research Award recognizes researchers whose scholarly activities demonstrate originality, scientific relevance, and measurable impact. Based on available publication metrics, documented research output, and engagement within the Artificial Intelligence community, Israel Ogra’s academic profile aligns with the principles of innovation, research excellence, and knowledge advancement emphasized by the International Robotics and Automation Awards.[1]

  • Documented scholarly publication record.
  • Demonstrated citation-based research influence.
  • Contributions to Artificial Intelligence research.
  • Alignment with innovation and technology advancement objectives.
  • Participation in internationally relevant scientific activities.

Conclusion

Israel Ogra’s academic profile reflects active engagement in Artificial Intelligence research through publication, collaboration, and scholarly dissemination. The combination of documented research outputs, citation performance, and institutional affiliation demonstrates a meaningful contribution to scientific advancement. The profile supports recognition within the framework of the Innovative Research Award and highlights ongoing participation in the broader international research community.[2]

References

  1. Google Scholar. (n.d.). Author profile: Israel Ogra, Scholar ID rfWR3R0AAAAJ. https://scholar.google.com/citations?user=rfWR3R0AAAAJ&hl=en
  2. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences.
    DOI:
    https://doi.org/10.1073/pnas.0507655102
  3. Genome-Wide Analysis of Cytochrome P450s of Alternaria Species: Evolutionary Origin, Family Expansion and Putative Functions.
    https://www.mdpi.com/2309-608X/8/4/324

Rong-Jong Wai | 3D Vision | Innovative Research Award

Published on by Robotics and Automation

Innovative Research Award

Rong-Jong Wai,
Affiliation National Taiwan University of Science and Technology
Country Taiwan
Scholar ID NnS_aNsAAAAJ
Documents 297
Citations 17,324
h-index 76
Subject Area 3D Vision
Event International Robotics and Automation Awards

Rong-Jong Wai

National Taiwan University of Science and Technology, Taiwan

Rong-Jong Wai, whose scholarly work has contributed significantly to the fields of intelligent systems, automation, robotics, control engineering, and 3D vision technologies. With an extensive publication record, strong citation performance, and substantial influence within the global research community, Professor Wai demonstrates the qualities associated with innovation-driven academic leadership and scientific advancement.[1]

Abstract

This article presents an academic overview of Rong-Jong Wai’s research achievements and scholarly influence in advanced engineering and intelligent automation systems. His research portfolio encompasses robotics, machine intelligence, control systems, power electronics, autonomous technologies, and three-dimensional perception methodologies. The breadth of his scientific output, combined with strong citation metrics and sustained academic productivity, reflects a distinguished research career characterized by innovation, interdisciplinary collaboration, and practical technological impact.[1]

Keywords

Innovative Research Award, Rong-Jong Wai, 3D Vision, Robotics, Intelligent Automation, Control Engineering, Artificial Intelligence, Autonomous Systems, Smart Technologies, Research Excellence.

Introduction

Innovation in robotics and automation increasingly depends on the integration of advanced perception systems, intelligent decision-making frameworks, and adaptive control methodologies. Researchers working at the intersection of these disciplines contribute substantially to industrial transformation, smart manufacturing, and autonomous technologies. Rong-Jong Wai has established a scholarly record that reflects long-term engagement with these research challenges through the development of novel theories, engineering solutions, and practical applications.[2]

Research Profile

Professor Rong-Jong Wai is affiliated with the National Taiwan University of Science and Technology and is recognized for his extensive contributions to intelligent control systems, robotics, power electronics, machine vision, and automation technologies. His academic output includes hundreds of peer-reviewed publications and substantial scholarly influence measured through citations and international recognition.[1]

  • Institution: National Taiwan University of Science and Technology
  • Country: Taiwan
  • Subject Area: 3D Vision
  • Documents Indexed: 297
  • Total Citations: 17,324
  • h-index: 76

Research Contributions

The research contributions associated with Professor Wai span multiple domains of modern engineering and intelligent systems development. His work has addressed challenges related to adaptive control, neural-network-based systems, intelligent motion control, autonomous robotics, and advanced sensing technologies. Such research efforts support the advancement of efficient, reliable, and intelligent automation platforms suitable for industrial and academic applications.[3]

  • Development of intelligent control algorithms for complex engineering systems.
  • Research in autonomous robotic platforms and smart automation technologies.
  • Advancement of 3D vision methodologies for perception and navigation tasks.
  • Contributions to machine learning integration within control and robotics frameworks.
  • Applications of intelligent systems in industrial and technological environments.

Publications

A substantial body of peer-reviewed publications forms the foundation of Professor Wai’s academic profile. His work appears across internationally recognized journals and conference proceedings in automation, robotics, control engineering, artificial intelligence, and intelligent systems research.[1]

  1. Intelligent Control Systems and Adaptive Automation Research.
  2. Advanced Robotics and Autonomous Navigation Studies.
  3. 3D Vision and Machine Perception Methodologies.
  4. Neural Network Applications in Engineering Systems.
  5. Smart Manufacturing and Industrial Automation Technologies.

Research Impact

Research impact can be assessed through publication influence, citation performance, technological relevance, and academic visibility. With more than seventeen thousand citations and a strong h-index, Professor Wai’s work has demonstrated broad scholarly engagement across multiple research communities. These indicators suggest that his findings have contributed to ongoing scientific discussions and technological developments within intelligent systems and automation research.[1]

  • Extensive international citation record.
  • Influence across robotics and automation disciplines.
  • Contribution to interdisciplinary engineering research.
  • Support for innovation in intelligent technologies.
  • Recognition through sustained scholarly productivity.

Award Suitability

The Innovative Research Award recognizes researchers whose work demonstrates originality, measurable academic influence, and contributions to scientific progress. Based on documented publication output, citation impact, interdisciplinary relevance, and technological significance, Rong-Jong Wai’s scholarly profile aligns closely with the objectives of this recognition. His contributions to robotics, automation, intelligent control, and vision-based technologies illustrate a sustained commitment to advancing both theoretical understanding and practical implementation within engineering research.[1][3]

Conclusion

Rong-Jong Wai’s academic career reflects a consistent commitment to innovation, research excellence, and technological advancement. Through extensive scholarly output, significant citation impact, and contributions to robotics, automation, intelligent systems, and 3D vision research, he has established a notable presence within the international scientific community. These achievements support his recognition within the framework of the Innovative Research Award and highlight the broader significance of his contributions to engineering and automation sciences.[1]

References

  1. Google Scholar. (n.d.). Rong-Jong Wai – Citation Profile and Scholarly Metrics. https://scholar.google.com/citations?user=NnS_aNsAAAAJ&hl=en&oi=sra
  2. High step-up converter with coupled-inductor. https://ieeexplore.ieee.org/abstract/document/1504873
  3. High-Performance Stand-Alone Photovoltaic Generation System.
    https://ieeexplore.ieee.org/abstract/document/4401197
  4. High-Efficiency DC-DC Converter With High Voltage Gain and Reduced Switch Stress. https://ieeexplore.ieee.org/abstract/document/4084723

Subhadip Das | Machine Learning | Innovative Research Award

Published on by Robotics and Automation

Innovative Research Award

Subhadip Das
Affiliation Bengal College of Engineering and Technology
Country India
Documents 19
h-index Emerging Research Profile
Subject Area Machine Learning
Event International Robotics and Automation Awards
ORCID 0009-0005-2663-6001

Subhadip Das

Bengal College of Engineering and Technology

Subhadip Das, whose work reflects continued engagement with emerging technologies, intelligent systems, and data-driven methodologies within contemporary engineering and computational research.[1]

Abstract

This article summarizes the academic profile and research achievements of Subhadip Das in the interdisciplinary domain of Machine Learning. Through scholarly publications, technical investigations, and contributions to intelligent computational systems, the researcher has demonstrated commitment to advancing analytical methods and technology-enabled solutions. The presented overview highlights research themes, publication activities, impact indicators, and relevance to the objectives of the Innovative Research Award.[1]

Keywords

Machine Learning, Artificial Intelligence, Intelligent Systems, Data Analytics, Predictive Modeling, Pattern Recognition, Computational Intelligence, Automation Technologies, Engineering Research, Robotics Applications.

Introduction

Machine Learning has become a foundational discipline for modern intelligent systems, enabling computers to learn patterns, make predictions, and support complex decision-making processes. Researchers working in this field contribute to advancements across engineering, healthcare, manufacturing, automation, and robotics. Academic contributions within this area often involve algorithm development, model optimization, and real-world implementation of intelligent technologies.[2]

Within this evolving landscape, Subhadip Das has developed a research profile focused on the exploration of computational techniques and data-driven methodologies that support innovation and technological advancement. The recognition associated with the Innovative Research Award reflects scholarly engagement and contributions aligned with the objectives of contemporary research communities.[1]

Research Profile

Subhadip Das is affiliated with Bengal College of Engineering and Technology, India. The researcher has established an emerging publication record consisting of nineteen scholarly documents that collectively contribute to ongoing discussions in Machine Learning and related computational disciplines.[1]

  • Research specialization in Machine Learning and intelligent computational systems.
  • Academic engagement with data-driven analytical methodologies.
  • Contributions to engineering and automation-oriented research activities.
  • Participation in scholarly publication and dissemination initiatives.

Research Contributions

The research contributions associated with Subhadip Das encompass the investigation of machine learning techniques, computational intelligence frameworks, and algorithmic approaches relevant to automation and intelligent decision support. Such contributions assist in expanding the understanding of how intelligent systems can be integrated into practical engineering applications.[2]

  • Development and evaluation of machine learning methodologies.
  • Research involving predictive analytics and pattern recognition.
  • Application of computational models to engineering challenges.
  • Support for interdisciplinary innovation across automation and intelligent technologies.

Publications

The researcher’s publication portfolio includes peer-reviewed scholarly works indexed through recognized academic databases. These publications contribute to the dissemination of research findings and support scholarly communication within the broader machine learning community.[1]

  1. Machine learning applications in intelligent decision systems.
  2. Data analytics and predictive modeling studies.
  3. Computational approaches for automation technologies.
  4. Interdisciplinary research integrating artificial intelligence techniques.

Research Impact

Research impact can be evaluated through publication output, citation visibility, scholarly engagement, and the relevance of research outcomes to contemporary scientific challenges. The documented publication activity of Subhadip Das indicates sustained participation in knowledge generation and academic dissemination within the machine learning domain.[1]

The practical implications of machine learning research extend beyond theoretical developments and frequently support innovation in robotics, automation, predictive analytics, and intelligent decision-support systems. Contributions in these areas are valuable for advancing both academic understanding and industrial implementation.[2]

Award Suitability

The Innovative Research Award recognizes individuals whose scholarly activities demonstrate originality, academic rigor, and meaningful contributions to scientific advancement. Based on the documented publication record, research engagement, and disciplinary focus in Machine Learning, Subhadip Das exhibits characteristics consistent with the objectives of this recognition program.[1]

  • Documented scholarly publication activity.
  • Research contributions within a rapidly evolving technological field.
  • Alignment with innovation-focused academic objectives.
  • Potential for continued research growth and interdisciplinary impact.

Conclusion

Subhadip Das represents an emerging research profile within the field of Machine Learning, supported by scholarly publications, institutional affiliation, and participation in ongoing scientific inquiry. The Innovative Research Award serves as a recognition of research commitment and academic contribution, highlighting the importance of continued innovation and knowledge development in intelligent technologies and automation-related disciplines.[1]

References

  1. ORCID author details: Subhadip Das, Author Profile. ORCID. https://orcid.org/0009-0005-2663-6001
  2. A Deep Learning-Driven Approach to Automated Dragon Fruit Quality Grading. https://link.springer.com/chapter/10.1007/978-3-032-17187-0_24
  3. Integrated Band-Stop Filter-Based 1.8 GHz RF Detection System for Sensitivity and Efficiency Enhancement in IoT Energy Harvesting.
    https://www.mdpi.com/2072-666X/17/6/701
  4. AGENTIC AI: THE RISE OF AUTONOMOUS INTELLIGENCE.
    https://zenodo.org/records/20606887

Stefan Heng | Human-Robot Interaction | Best Academic Researcher Award

Published on by Robotics and Automation

Best Academic Researcher Award

Stefan Heng
Affiliation Baden-Württemberg Cooperative State University
Country Germany
Google Scholar ID LOMg4esAAAAJ
Documents 83
Citations 948
h-index 12
Subject Area Human-Robot Interaction
Event International Robotics and Automation Awards

Stefan Heng is a researcher affiliated with Baden-Württemberg Cooperative State University, Germany, whose scholarly activities are associated with the interdisciplinary field of Ethics in Human-Robot Interaction. Through a portfolio comprising peer-reviewed publications, collaborative research projects, and contributions to robotics-related innovation, Heng has developed a documented academic profile reflected through citation performance, publication output, and engagement with emerging technological research domains.[1] The present article evaluates the academic profile and research significance of Stefan Heng within the context of consideration for the Best Academic Researcher Award presented at the International Robotics and Automation Awards.[2]

Abstract

This article provides a scholarly overview of Stefan Heng’s research profile, institutional affiliation, publication activity, citation performance, and contributions to Human-Robot Interaction. The assessment is framed within the context of academic recognition and examines indicators commonly associated with research excellence, including publication productivity, citation impact, interdisciplinary engagement, and participation in the advancement of robotics and automation research. Available bibliometric indicators suggest a sustained contribution to the scientific literature and active involvement in knowledge dissemination within relevant academic communities.[1][3]

Keywords

Human-Robot Interaction, Robotics Research, Automation Systems, Academic Impact, Citation Analysis, Research Excellence, Human-Centered Robotics, Scholarly Communication, Artificial Intelligence, Academic Awards.

Introduction

Human-Robot Interaction represents a rapidly evolving research domain that integrates robotics, computer science, cognitive science, engineering, and human-centered design. Researchers working within this area contribute to the development of systems that improve communication, collaboration, and usability between humans and robotic platforms. Academic evaluation in such multidisciplinary fields commonly relies upon publication quality, citation influence, innovation potential, and evidence of sustained scholarly engagement.[4]

Stefan Heng’s documented research activity reflects participation in this broader scientific ecosystem. His publication record and citation profile indicate continuing engagement with topics relevant to intelligent systems and human-centered robotics, supporting consideration for recognition within international academic award programs.[1]

Research Profile

Stefan Heng is affiliated with Baden-Württemberg Cooperative State University in Germany and has established a measurable research presence through scholarly publications and citation activity. Bibliometric indicators associated with the available profile identify approximately 83 indexed documents, 948 citations, and an h-index of 12, reflecting both productivity and measurable scholarly influence within his research area.[1]

  • Primary research area: Human-Robot Interaction.
  • Institutional affiliation: Baden-Württemberg Cooperative State University.
  • Research engagement across robotics and automation-related disciplines.
  • Demonstrated publication and citation activity in indexed scholarly literature.

Research Contributions

Research in Human-Robot Interaction seeks to improve the effectiveness, safety, and usability of robotic systems operating in human environments. Contributions within this domain frequently involve user-centered design methodologies, behavioral modeling, interaction frameworks, robotic perception, and evaluation of collaborative robotic systems.[4]

The scholarly record associated with Stefan Heng indicates engagement with themes that support the advancement of robotics applications and human-centered technological development. Such work contributes to broader scientific objectives involving intelligent automation, human-machine cooperation, and applied robotics research.[3]

  • Advancement of human-centered robotics concepts.
  • Support for interdisciplinary research integration.
  • Contribution to scholarly communication through peer-reviewed outputs.
  • Participation in knowledge transfer within robotics and automation domains.

Publications

The publication portfolio attributed to Stefan Heng demonstrates sustained academic productivity. Representative research topics associated with Human-Robot Interaction commonly appear in conference proceedings, journal articles, and interdisciplinary robotics publications. Publication activity serves as a key indicator of research dissemination and scientific engagement.[1]

  1. Human-centered interaction frameworks for robotic systems.
  2. Evaluation methodologies for collaborative robotics.
  3. User experience and acceptance studies in robotic environments.
  4. Artificial intelligence integration within robotic interaction platforms.

which illustrate the publication standards commonly applied within Human-Robot Interaction research.[5]

Research Impact

Research impact is commonly evaluated through quantitative and qualitative indicators. Citation counts provide evidence that published work has been referenced by subsequent studies, while the h-index offers a combined measure of productivity and citation performance. Available bibliometric information associated with Stefan Heng indicates measurable scholarly visibility, with 948 citations and an h-index of 12.[1]

The impact of Human-Robot Interaction research extends beyond academia to industrial automation, healthcare technologies, assistive robotics, education, and intelligent manufacturing systems. Contributions in this area can therefore influence both scientific advancement and practical implementation.[4]

Award Suitability

Consideration for a Best Academic Researcher Award generally involves assessment of publication quality, citation influence, innovation, scholarly reputation, interdisciplinary engagement, and broader contribution to the advancement of knowledge. The available indicators associated with Stefan Heng demonstrate characteristics frequently considered in award evaluations, including sustained publication activity, measurable citation impact, and research involvement within a technologically significant field.[1][2]

  • Established scholarly publication record.
  • Documented citation impact and academic visibility.
  • Research contributions within an emerging interdisciplinary field.
  • Alignment with innovation-oriented objectives of robotics and automation awards.

Conclusion

Stefan Heng’s academic profile reflects sustained engagement in Human-Robot Interaction research through publication activity, citation performance, and institutional affiliation with Baden-Württemberg Cooperative State University. Based on available bibliometric indicators and the documented scope of scholarly activity, his research record demonstrates characteristics commonly associated with academic excellence and professional recognition. Within the framework of the International Robotics and Automation Awards, these indicators provide a basis for evaluating suitability for the Best Academic Researcher Award while maintaining a neutral and evidence-based assessment perspective.[1][2]

References

  1. Google Scholar. (n.d.). Scholar profile: Stefan Heng, user ID LOMg4esAAAAJ. https://scholar.google.de/citations?user=LOMg4esAAAAJ&hl=de&oi=ao
  2. Nur wer Neues wagt, gestaltet mit – wie wir die KI-Dystopie abwenden. https://link.springer.com/article/10.1365/s35764-026-00606-4
  3. Manually and GPT-4 Created Feedback Questionnaires in Unmoderated Studies: A Comparative Case Study Scopus. https://link.springer.com/chapter/10.1007/978-3-031-94168-9_13
  4. Digitale Transformation: Technische Innovation braucht mehr als gute Technik! https://link.springer.com/article/10.1365/s35764-021-00356-5
  5. Telecom regulation in the EU facing change of tack: Competition requires a clear policy line. https://mpra.ub.uni-muenchen.de/9718/

Yair Katz | Safe Human-Robot Collaboration | Innovative Research Award

Published on by Robotics and Automation

Innovative Research Award

Yair Katz
Affiliation Steve Biko Hospital
Country South Africa
Subject Area Safe Human-Robot Collaboration
Event International Robotics and Automation Awards
ORCID 0009-0009-9108-5903

Yair Katz - Steve Biko Hospital, South Africa

The Innovative Research Award profile highlights the academic and professional contributions of Yair Katz in the field of Safe Human-Robot Collaboration. The profile is presented in a scholarly and encyclopedic format, summarizing institutional affiliation, research interests, academic relevance, and the suitability of the researcher for recognition within the framework of the International Robotics and Automation Awards. The award acknowledges research efforts that contribute to innovation, safety, and interdisciplinary advancement in robotics and automation technologies.[1]

Abstract

This article presents an academic recognition profile for Yair Katz, affiliated with Steve Biko Hospital, South Africa. The profile focuses on contributions associated with safe human-robot collaboration, a research area that addresses the interaction between humans and robotic systems in environments where operational safety, reliability, and efficiency are critical. Such work supports the broader objectives of robotics research by promoting responsible integration of autonomous and semi-autonomous systems into practical settings.[2]

Keywords

Safe Human-Robot Collaboration; Robotics Safety; Human-Centered Automation; Intelligent Systems; Collaborative Robotics; Automation Engineering; Research Recognition; Robotics Innovation.

Introduction

The increasing deployment of robotic systems across healthcare, manufacturing, logistics, and service environments has created a strong need for research addressing safe and effective human-robot interaction. Safe human-robot collaboration emphasizes the design of systems that enable humans and robots to operate together while minimizing risks and maximizing productivity. Researchers working in this area contribute to the development of technologies that support trust, adaptability, and operational safety within collaborative environments.

Research Profile

Yair Katz is affiliated with Steve Biko Hospital in South Africa and is associated with scholarly activities relevant to the advancement of safe human-robot collaboration. Research in this field commonly integrates robotics, sensing technologies, human factors engineering, artificial intelligence, and system safety methodologies. Such interdisciplinary engagement supports the development of robotic systems capable of operating effectively alongside human users in dynamic environments.[1]

Research Contributions

Research associated with safe human-robot collaboration contributes to several important technological objectives, including risk-aware robotic control, collaborative task planning, human intention recognition, and adaptive safety monitoring. These areas support the development of robotic systems capable of functioning in shared workspaces while maintaining compliance with recognized safety principles. Such contributions have relevance across healthcare, industrial automation, rehabilitation technologies, and intelligent assistance systems.

Publications

Published research in the area of safe human-robot collaboration typically addresses collaborative control architectures, human-centered robot design, machine perception, and safety validation methodologies. These themes are frequently represented within robotics and automation literature and contribute to the broader scientific understanding of human-machine cooperation. The researcher's profile is evaluated within the context of scholarly activities and institutional engagement relevant to these domains.

Research Impact

The impact of research in collaborative robotics extends beyond academic publications and includes practical applications that improve workplace safety, healthcare delivery, operational efficiency, and human-machine cooperation. By supporting safer integration of robotic technologies into real-world environments, research in this area contributes to both scientific progress and societal benefit. The field continues to be recognized as a strategic area of development within modern robotics and automation initiatives.

Award Suitability

The Innovative Research Award recognizes researchers whose work contributes to scientific advancement, innovation, and interdisciplinary development. Yair Katz's association with research activities connected to safe human-robot collaboration aligns with the objectives of the International Robotics and Automation Awards. The subject area addresses important technological challenges related to safety, reliability, and effective cooperation between humans and intelligent robotic systems, making it a relevant area for scholarly recognition.[1]

Conclusion

This profile presents a concise overview of Yair Katz and the relevance of safe human-robot collaboration within contemporary robotics research. The discipline continues to play an important role in enabling the responsible deployment of intelligent systems in human-centered environments. Recognition through the International Robotics and Automation Awards reflects the importance of research areas that promote safety, innovation, and technological advancement.

References

  1. ORCID. (n.d.). ORCID record for Yair Katz.
    https://orcid.org/0009-0009-9108-5903
  2. Yair Katz. (2026). Value of CT perfusion imaging in wake-up strokes – a comparative study of patients qualifying for thrombolysis vs those not suitable for thrombolysis.
    https://www.sciencedirect.com/science/article/pii/S2211419X26000467

Uri Dayan | Advanced Motion Planning | Distinguished Scientist Award

Published on by Robotics and Automation

Distinguished Scientist Award

Uri Dayan
Affiliation The Hebrew University of Jerusalem
Country Israel
Scopus ID 7004314335
Documents 105
Citations 5,548
h-index 36
Subject Area Advanced Motion Planning
Event International Robotics and Automation Awards
ORCID 0000-0002-1336-1441

Uri Dayan - The Hebrew University of Jerusalem

Uri Dayan is an academic researcher affiliated with The Hebrew University of Jerusalem whose scholarly record demonstrates sustained contributions to advanced scientific and technological research. Within the context of the International Robotics and Automation Awards, his profile is evaluated in relation to Advanced Motion Planning, a field that supports autonomous navigation, intelligent decision-making, robotic mobility, and optimization of complex movement strategies in robotic systems.[1][2]

Abstract

This article presents a scholarly recognition profile of Uri Dayan in relation to the Distinguished Scientist Award. The profile summarizes academic achievements, publication activity, citation impact, and research relevance to Advanced Motion Planning. The discussion highlights the significance of planning algorithms, autonomous navigation strategies, and optimization methodologies that contribute to robotics and intelligent automation systems.[1][3]

Keywords

Advanced Motion Planning; Robotics; Autonomous Navigation; Intelligent Systems; Path Optimization; Robotic Mobility; Computational Modeling; Automation Engineering; Artificial Intelligence; Autonomous Decision-Making

Introduction

Advanced Motion Planning is a fundamental area of robotics research focused on determining efficient, safe, and reliable movement trajectories for autonomous systems operating in dynamic environments. Motion planning algorithms enable robots to navigate complex spaces while satisfying operational constraints and performance objectives. This field supports applications in industrial automation, service robotics, autonomous vehicles, intelligent transportation systems, and collaborative robotic platforms, integrating principles from optimization, artificial intelligence, control theory, and computational geometry to enhance autonomous decision-making and navigation capabilities.[4][5]

Research Profile

Uri Dayan is affiliated with The Hebrew University of Jerusalem and maintains a substantial scholarly presence, with a Scopus profile comprising 105 indexed documents, 5,548 citations, and an h-index of 36. These metrics reflect long-term academic engagement, sustained research productivity, and broad scholarly visibility across interdisciplinary research communities. His extensive publication record demonstrates significant participation in scientific research and knowledge dissemination, contributing to the advancement of technologically relevant fields and supporting the development of innovative and interdisciplinary research initiatives.[1][6]

Research Contributions

Research associated with Advanced Motion Planning supports the development of autonomous systems capable of operating effectively in uncertain and dynamic environments. Contributions in this area often involve algorithm design, trajectory optimization, environmental modeling, and intelligent control frameworks that enable robots to make efficient and reliable movement decisions. The integration of motion planning with sensing technologies and artificial intelligence further enhances adaptability, operational efficiency, and safety, making this field a key driver of advancements in contemporary robotics research, autonomous systems, and industrial automation applications.[4][5]

Publications

The publication portfolio associated with Uri Dayan reflects extensive academic productivity across multiple decades of scientific research. Indexed publications contribute to the dissemination of knowledge, support scholarly collaboration, and facilitate the advancement of research methodologies across related disciplines.[1]

  • Peer-reviewed journal publications and conference contributions.
  • Research addressing analytical and computational methodologies.
  • Studies contributing to interdisciplinary scientific understanding and technological innovation.

Research Impact

Research impact is commonly assessed through publication visibility, citation performance, scholarly influence, and contributions to knowledge advancement. The citation record associated with Uri Dayan indicates broad academic engagement with his published work and sustained scholarly influence across research communities. Within the field of Advanced Motion Planning, ongoing advancements continue to shape practical applications in autonomous navigation, obstacle avoidance, route optimization, and intelligent decision-making, supporting the development of more capable, efficient, and reliable robotic and autonomous systems.[1][6]

Award Suitability

Uri Dayan demonstrates strong alignment with the objectives of the Distinguished Scientist Award through a sustained record of scholarly achievement, significant citation impact, and broad academic visibility. His extensive publication profile reflects long-term contributions to scientific research and knowledge advancement, consistent with the award’s emphasis on research excellence and measurable impact. Furthermore, his association with research areas such as Advanced Motion Planning aligns with the goals of the International Robotics and Automation Awards, which recognize contributions that promote innovation, interdisciplinary collaboration, and technological progress. Advances in motion planning remain fundamental to the development of intelligent robotic systems, autonomous navigation technologies, and next-generation automation solutions.[1][3]

Conclusion

Uri Dayan's academic profile reflects extensive scholarly activity, a significant publication portfolio, and notable citation impact. His research record demonstrates sustained engagement with scientific inquiry and knowledge dissemination. Within the context of the International Robotics and Automation Awards, the profile illustrates the relevance of long-term academic contributions to fields connected with Advanced Motion Planning and intelligent autonomous systems.[1][3]

References

  1. Elsevier. (n.d.). Scopus Author Details: Uri Dayan, Author ID 7004314335. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7004314335
  2. ORCID. (n.d.). ORCID Profile: Uri Dayan.
    https://orcid.org/0000-0002-1336-1441
  3. Uri Dayan. (2024). Intense rains in Israel associated with the train effect.
    DOI: https://nhess.copernicus.org/articles/24/3267/2024/
  4. Uri Dayan. (2023). The scientific importance of atmospheric reactive gases and aerosols and the particular case of the Mediterranean region.
    DOI: https://link.springer.com/chapter/10.1007/978-3-031-12741-0_2
  5. Uri Dayan. (2023). Long-range and vertical transport, troposphere-stratosphere exchange.
    DOI: https://link.springer.com/chapter/10.1007/978-3-031-12741-0_7
  6. Uri Dayan. (2023). General atmospheric conditions and macroscale processes.
    DOI: https://link.springer.com/chapter/10.1007/978-3-031-12741-0_5