Mª del Carmen de Castro-Cabrera | Computer Science | Innovative Research Award

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Innovative Research Award

Mª del Carmen de Castro-Cabrera
University of Cádiz, Spain

Mª del Carmen de Castro-Cabrera
Affiliation University of Cádiz
Country Spain
Scopus 49862833800
Documents 18
Citations 58
h-index 4
Subject Area Computer Science
Event International Phenomenological Research Awards
ORCID 0000-0003-4622-5275

Mª del Carmen de Castro-Cabrera is an Associate Professor in the Department of Computer Science and Engineering at the University of Cádiz, Spain, and a member of the UCASE software engineering research group. Her documented research activity centers on software engineering, particularly software testing, metamorphic testing, model-based testing, and related computational methods. Her publication record also includes work involving educational technologies and collaborative learning. [1]

Abstract

Mª del Carmen de Castro-Cabrera’s academic profile reflects sustained engagement with software engineering research at the University of Cádiz. Her work addresses software testing and associated techniques, including metamorphic testing, test-case prioritization, model-based testing, and constraint-based approaches. Her research record also extends to educational innovation and collaborative learning, providing an interdisciplinary connection between software engineering research and higher-education practice. [2]

Keywords

Software engineering; Software testing; Metamorphic testing; Model-based testing; Test-case prioritization; Constraint programming; Service-oriented architectures; Educational innovation.

Introduction

The research profile of Mª del Carmen de Castro-Cabrera is situated within computer science and software engineering, with particular attention to methods for improving software quality and testing processes. Her work has included research on testing service compositions, metamorphic testing, test-case prioritization, and combinations of model-based testing with constraint programming. Bibliographic records also document contributions to educational technology and assessment in higher education. [3]

Research Profile

Mª del Carmen de Castro-Cabrera is associated with the UCASE software engineering research group at the University of Cádiz. Her research activity has included participation in regional and national research projects concerned with software architectures, software design, formal modeling, testing, service-oriented systems, search-based software engineering, and data-processing applications. University research records identify her as a university professor and document continued collaboration within software engineering research. [1]

Research Contributions

The research contributions focus on software engineering, including metamorphic testing, WS-BPEL service testing, test-case prioritization, model-based testing, and constraint-based approaches for software verification and quality assurance. [3] [4] Her research also includes educational technology, focusing on wiki-based learning assessment, educational innovation, and software-testing practices that support collaborative and self-assessment in higher education.. [2] [5]

Publications

Mª del Carmen de Castro-Cabrera’s publications address software testing, metamorphic testing, test-case prioritization, model-based testing, constraint programming, service-oriented architectures, and educational technologies. Representative publications include research on wiki-based learning assessment, test-case prioritization, metamorphic testing with constraint solvers, WS-BPEL compositions, and model-based testing combined with constraint programming. These works illustrate continuity between methodological software-engineering research and applied educational or systems contexts. [2] [3] [4] [5] [6]

Research Impact

The supplied bibliometric profile records 18 Scopus documents, 58 citations, and an h-index of 4 for author ID 49862833800. A separate Google Scholar profile supplied for the researcher reports 59 documents, 115 citations, and an h-index of 5. Because bibliometric databases apply different coverage and counting methods, these figures should be interpreted as database-specific indicators rather than interchangeable measures of research output. [1] Her publication record demonstrates research activity extending across software testing and educational applications. Bibliographic records also document continuing collaboration within the University of Cádiz software engineering environment, including publications on model-based testing, constraint programming, and metamorphic testing. [6]

Award Suitability

The Innovative Research Award category aligns with her documented research in software engineering, software testing, metamorphic testing, test-case prioritization, and model-based approaches. Her participation in multiple research projects and publications demonstrates sustained academic engagement across software engineering and educational technology, supporting consideration within an innovation-focused research recognition framework based on the supplied record.

Conclusion

Mª del Carmen de Castro-Cabrera’s academic profile integrates university teaching and research in software engineering. Her work includes software testing, metamorphic testing, model-based approaches, constraint programming, service-oriented systems, and educational technology. Participation in research projects and scholarly publications demonstrates sustained contributions to software quality, testing methodologies, and applied computer science research. [1] [6]

References

  1. Elsevier. (n.d.). Scopus author details: Mª del Carmen de Castro-Cabrera, Author ID 49862833800. Scopus. https://www.scopus.com/authid/detail.uri?authorId=49862833800
  2. Palomo-Duarte, M., Dodero, J. M., García-Domínguez, A., Neira-Ayuso, P., et al. (2014). Scalability of assessments of wiki-based learning experiences in higher education. Computers in Human Behavior, 31, 638–650. DOI: https://doi.org/10.1016/j.chb.2013.07.033
  3. de Castro-Cabrera, M. C., García-Domínguez, A., & Medina-Bulo, I. (2020). Trends in prioritization of test cases: 2017–2019. Proceedings of the 35th Annual ACM Symposium on Applied Computing, 2005–2011. DOI: https://doi.org/10.1145/3341105.3374036
  4. de Castro-Cabrera, M. C., García-Domínguez, A., & Medina-Bulo, I. (2019). Using constraint solvers to support metamorphic testing. 2019 IEEE/ACM 4th International Workshop on Metamorphic Testing, 32–39. DOI: https://doi.org/10.1109/MET.2019.00013
  5. Castro-Cabrera, C., & Medina-Bulo, I. (2011). An approach to metamorphic testing for WS-BPEL compositions. Proceedings of the International Conference on e-Business, 137–142. DOI: https://doi.org/10.5220/0003611401370142
  6. Castro-Cabrera, C., & Medina-Bulo, I. (2012). Application of Metamorphic Testing to a Case Study in Web Services Compositions. Communications in Computer and Information Science, 168–181. DOI: https://doi.org/10.1007/978-3-642-35755-8_13

Mohd Khaled Shambour | Computer Science | Best Paper Award

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Prof. Mohd Khaled Shambour | Computer Science | Best Paper Award  

Professor at Middle East University | Jordan

Prof. Mohd Khaled Shambour is an accomplished academic and researcher in the field of computer science, widely recognized for his contributions to intelligent systems and computational optimization. He holds advanced academic qualifications in computer science and intelligent system techniques and has gained extensive experience through senior academic and research roles within higher education and research institutions. His professional work reflects strong expertise in artificial intelligence, optimization techniques, metaheuristic algorithms, data science, scheduling, and timetabling, with a clear emphasis on solving complex real-world problems through innovative computational approaches. Prof. Mohd Khaled Shambour has produced a substantial body of high-impact scholarly work, authoring 40 research documents that have attracted 1,189 citations across 1,039 citing documents, resulting in an h-index of 16, underscoring both productivity and sustained research influence. His research is noted for methodological rigor, interdisciplinary relevance, and practical applicability, and he continues to contribute meaningfully to advancing knowledge, innovation, and academic excellence in computer science.

Citation Metrics (Verified)

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40

h-index
16

Featured Publications

JUN WON HO | Computer Engineering | Best Researcher Award

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Dr. JUN WON HO | Computer Engineering | Best Researcher Award

Research Fellow at Incheon National University, South Korea.

Dr. Jun Won-Ho 🎓 is a dedicated Research Fellow at Incheon National University, South Korea 🇰🇷. He earned his Ph.D. in Computer Engineering in February 2023 🧠, focusing on sleep pattern analysis in an unconscious, non-intrusive state 🛏️. His innovations aim to revolutionize sleep health through biosensor-based technologies 💡. With peer-reviewed publications in SCI-indexed journals 📚 and a patent on body weight estimation while lying in bed 🧾, Dr. Jun is making sleep monitoring accessible and home-based. His work bridges healthcare and engineering, offering practical solutions for sleep apnea detection 🩺 using biosensors and ambient signals 🌐.

Professional Profile:

ORCID

Suitability for Best Researcher Award – Dr. Jun Won-Ho

Dr. Jun Won-Ho is highly suitable for the Best Researcher Award due to his pioneering research at the intersection of biomedical engineering and computer science. Despite being an early-career researcher, he has demonstrated remarkable innovation and scientific productivity, especially in the field of non-intrusive sleep health monitoring. His Ph.D. and postdoctoral work have resulted in SCI-indexed journal publications, a granted patent, and the development of AI-based, contact-free technologies to address global health concerns like sleep apnea—showing both originality and real-world impact.

🎓 Education and Experience

  • 🎓 Ph.D. in Computer Engineering – Incheon National University (2023)

  • 🧪 Research Fellow – Incheon National University (Current)

  • 📄 Published in SCI-indexed journals – Including Sensors

  • 🛏️ Doctoral Research – Focused on unobtrusive sleep pattern analysis

  • 🔬 Ongoing Research – Development of self-screening technology for sleep apnea

  • 🧾 Patent Holder – System for estimating body weight while lying on a bed

🚀 Professional Development

Dr. Jun Won-Ho has significantly contributed to the field of sleep science and biomedical engineering 🧠. His journey began with a strong academic foundation in computer engineering 🎓, which he has transformed into impactful research focused on real-world health challenges 🩺. He has authored articles in SCI-indexed journals 📚 and currently works on a cutting-edge sleep apnea screening solution using biosensors and environmental data 🌙📊. His patented invention 🧾 and active engagement in non-contact health monitoring technologies reflect his innovative mindset and commitment to improving global health accessibility 🌍💡.

🧬 Research Focus Category

Dr. Jun Won-Ho’s research falls under the category of Biomedical Engineering and Sleep Science 🧠🛌. He is especially focused on unobtrusive health monitoring, developing systems that use biosensors, physiological signals, and environmental data to analyze sleep patterns and detect sleep disorders like apnea 😴🩺. His goal is to eliminate the need for intrusive clinical testing such as polysomnography 🧪 and instead offer home-based, AI-powered health solutions 🌐📲. His patented work on weight estimation during sleep complements his broader mission of advancing digital health technologies for continuous, contact-free care 🧾💡.

🏅 Awards and Honors

  • 🧾 Patent Granted – System for Estimating Body Weight While Lying on a Bed (KR 10-2556030)

  • 📄 SCI-Indexed Publications – Published 2 articles in renowned journals like Sensors

  • 📌 Ph.D. Achievement – Doctorate completed with impactful research in 2023

  • 🏆 Nominated for Best Researcher Award – For contributions to biomedical sleep technology

  • 🧠 Research Innovation Recognition – Development of non-contact sleep apnea screening system

Publication Top Notes

1. Detection of Sleep Posture via Humidity Fluctuation Analysis in a Sensor-Embedded Pillow

  • Published: April 30, 2025

  • Journal: Bioengineering

  • DOI: 10.3390/bioengineering12050480

  • Summary: This study introduces a novel method for detecting sleep posture by analyzing humidity fluctuations using sensors embedded in a pillow. The system monitors changes caused by respiration and perspiration, offering a non-invasive approach to sleep posture detection.

2. Sleep Pattern Analysis in Unconstrained and Unconscious State

  • Published: November 29, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22239296

  • Citation Count: 6

  • Summary: This research analyzes sleep patterns in individuals without physical constraints or active awareness. Utilizing various sensors, the study collects physiological and environmental data to classify sleep stages, providing insights into natural sleep behaviors.MDPI

3. Multi-Sensor Data Fusion with a Reconfigurable Module and Its Application to Unmanned Storage Boxes

  • Published: July 19, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22145388

  • Citation Count: 12

  • Summary: This paper presents a reconfigurable module for multi-sensor data fusion, applied to unmanned storage boxes. By integrating data from various sensors, the system enhances reliability and security in automated storage environments.

Conclusion

Dr. Jun Won-Ho exemplifies the qualities of a Best Researcher Award recipient through his innovative mindset, impactful biomedical applications, and commitment to global health technology advancement. His work is not only academically rigorous but also practically transformative, making essential health monitoring more accessible, affordable, and patient-friendly. He stands out as a rising star in biomedical engineering, well-deserving of this prestigious recognition.

Oluwafemi Oke | Cybersecurity | Best Researcher Award

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Dr. Oluwafemi Oke | Cybersecurity | Best Researcher Award

Lecturer at Near East University, Cyprus.

Oluwafemi Ayotunde Oke is a passionate researcher and lecturer specializing in Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. He holds a Ph.D. in Computer Information Systems from Near East University and has extensive experience in software development, IT engineering, and research assistance. His research focuses on AI-driven innovations in cardiology, finance, and healthcare. With numerous publications in high-impact journals, Oluwafemi actively contributes to international conferences, presenting groundbreaking insights. He is also a member of the Computer Information Systems Research and Technology Centre and has been nominated for prestigious research awards. ✨📊

Professional Profile:

ORCID Profile

Suitability for Best Researcher Award 🏆

Dr. Oluwafemi Ayotunde Oke is highly suitable for the Best Researcher Award due to his outstanding contributions to Artificial Intelligence (AI), Machine Learning (ML), and Cybersecurity. His research spans across multiple domains, including healthcare, finance, and smart cities, demonstrating the interdisciplinary impact of his work.

Education & Experience 🎓💼

📌 Ph.D. in Computer Information Systems – Near East University (2024)
📌 M.Sc. in Software Engineering – Babcock University (2020)
📌 B.Sc. in Computer Engineering (Technology) – Babcock University (2016)

👨‍🏫 Part-Time Lecturer – Near East University (2023-Present)
🔬 Research Assistant – Near East University (2022-Present)
🌍 Assistant Director of IT & Communications – National Association of Nigerian Students (2022-2024)
💻 IT Engineer – GIFA INC (2021)
🖥️ IT Developer – Yeni Bakis (2021)
🔧 Design Engineer – Daxlinks Global (2021)
📚 Graduate Research Assistant – Computer Professionals of Nigeria (2020)
🎧 Head of Audiovisuals – Taidob College (2018-2019)

Professional Development 🚀📚

Oluwafemi Oke continuously hones his expertise through global certifications and specialized training in AI, cybersecurity, and IT. He holds IBM certifications in AI, Machine Learning, and Cybersecurity 🏅 and has completed courses from Duke University and Yale University on Cybersecurity and Well-being. As a Huawei Certified Network Associate (HCIA), he has gained expertise in Big Data, Cloud Computing, and AI Security. His Android Developer and CompTIA certifications further strengthen his software engineering skills. Committed to academic growth, he actively engages in research memberships, workshops, and technology conferences, ensuring he stays ahead in the ever-evolving tech landscape. 🔍💡

Research Focus 🔬📊

Oluwafemi Oke’s research is centered around Artificial Intelligence (AI) and its transformative impact on various fields. His work in Natural Language Processing (NLP), Electrocardiogram (ECG) image classification, and AI-driven financial services showcases the power of AI in improving healthcare, finance, and education. 💙🧠 He has conducted bibliometric studies on AI in financial services, examined AI’s role in cardiology, and explored machine learning in conversational systems. 🌍📈 His research also extends to AI’s role in smart cities, IoT-based water management, and climate change predictions. Through innovative AI solutions, he aims to revolutionize healthcare, security, and financial technologies. 🤖💰

Awards & Honors 🏆🎖️

🏅 International Research Awards on Cybersecurity and Cryptography (Nominee, ID 1896)
📜 2024 Best Ph.D. Thesis Award – Electronics Journal
🎓 Member, Computer Information Systems Research and Technology Centre
🏆 Multiple Research Publications in SSCI/SCI-Expanded Journals
🌍 Presenter at Prestigious International Conferences

Publication Top Notes

  1. Building Tomorrow Green and Sustainable Imperatives in Smart City Development (2025) | Book Chapter
    📌 Authors: Oluwafemi Ayotunde Oke, Nuriye Sancar, Nadire Cavus
    📌 DOI: 10.1007/978-3-031-72479-4_38

  2. A Systematic Review on the Impact of Artificial Intelligence on Electrocardiograms in Cardiology (2025-03) | Journal Article
    📌 Authors: Oluwafemi Ayotunde Oke, Nadire Cavus
    📌 Journal: International Journal of Medical Informatics
    📌 DOI: 10.1016/j.ijmedinf.2024.105753

  3. Artificial Intelligence for Computer Vision: Bibliometric Analysis (2024-03) | Preprint
    📌 Authors: Oke O, Cavus N
    📌 DOI: 10.21203/rs.3.rs-4098674/v1

  4. The Role of AI in Financial Services: A Bibliometric Analysis (2024-01-19) | Journal Article
    📌 Authors: Oluwafemi Ayotunde Oke, Nadire Cavus
    📌 Journal: Journal of Computer Information Systems
    📌 DOI: 10.1080/08874417.2024.2304545

  5. The Impact of Artificial Intelligence in Foreign Language Learning Using Learning Management Systems: A Systematic Literature Review (2023-06-30) | Journal Article
    📌 Authors: Оке Олувафемі Айотунде, Дашти Ісміль Джаміль, Надір Кавус
    📌 Journal: Information Technologies and Learning Tools
    📌 DOI: 10.33407/itlt.v95i3.5233