Miriam Martínez Muñoz | Data Modeling and Database Design | Innovative Research Award

Published on by International Database Scientist Awards

Innovative Research Award

Miriam Martínez Muñoz
Madrid Open University (UDIMA)Spain,

Miriam Martínez Muñoz
Affiliation Madrid Open University (UDIMA)
Country Spain
Google Scholar FjmoqCkAAAAJ
Documents 36
Citations 77
h-index 6
Subject Area Data Modeling and Database Design
Event International Database Scientist Awards
Scopus 55941441500

Miriam Martínez Muñoz is an academic and researcher whose interdisciplinary work connects engineering, data analytics, educational technology, cybersecurity, artificial intelligence, and unmanned aerial vehicle applications. Her documented research and academic activities provide a multidisciplinary basis for consideration under the Innovative Research Award, particularly through technology-enabled approaches to education, engineering, and environmental assessment. [1]

Abstract

Miriam Martínez Muñoz is a Spanish academic whose professional profile combines physical sciences, communications, engineering, computing, data science, educational technology, cybersecurity, and UAV applications. Her research trajectory includes magnetic microdevices, wireless-powered microrobotics, educational innovation, environmental monitoring, and data-driven decision-making, demonstrating sustained interdisciplinary engagement across technological domains. [1]

Keywords

Federated Databases; Business Intelligence; Text-to-SQL; Large Language Models; Internet of Things Security; Device Authentication; Data Privacy; Smart Cities; Cybersecurity; Business Continuity.

Introduction

Martínez Muñoz’s academic development spans physics, signal theory and communications, software-related education, engineering research, and university management. Her doctoral studies at the University of Alcalá and subsequent academic activities provide a foundation for research addressing technological systems, digital learning, environmental assessment, and interdisciplinary applications of computational methods. [1]

Research Profile

Her research profile encompasses magnetic systems, microrobotics, UAV-based environmental assessment, cybersecurity, data science, artificial intelligence, digital assessment, and educational innovation. This breadth reflects an interdisciplinary research approach in which engineering, computation, data analysis, and technology-enhanced learning are applied to practical scientific and organisational problems. [1]

Research Contributions

Documented contributions include research on multipole magnetisation patterning, magnetic gears, wireless-powered microrobotic systems, space-related technologies, mobile learning, digital assessment, and UAV environmental auditing. These activities illustrate a research orientation toward developing and evaluating technological methods with applications in engineering, healthcare, education, and environmental monitoring. [2] [3]

Publications

Selected publications address magnetic microdevices and magnetic gears, while more recent work extends toward UAV magnetometry, environmental assessment, and educational innovation. The documented publication record therefore connects physical engineering research with emerging digital and technology-enabled applications. Bibliographic details should be confirmed against the original publisher records where indicated. [2] [3] [4] [5]

Research Impact

The supplied academic record reports 36 documents, 77 citations, and an h-index of 6. Her research activities additionally connect engineering research with education, cybersecurity, UAV technology, and environmental applications. These indicators and documented projects provide measurable and contextual evidence of research activity, while broader impact should be evaluated from verified database records. [1]

Award Suitability

The Innovative Research Award recognizes research profiles demonstrating meaningful technological or methodological development. Martínez Muñoz’s documented combination of engineering research, data analytics, educational technology, UAV applications, and cybersecurity provides a relevant interdisciplinary basis for consideration. Final award assessment should rely on independently verified publications, research outputs, and eligibility criteria. [1]

Conclusion

Miriam Martínez Muñoz presents an interdisciplinary academic profile spanning engineering, communications, data science, education, cybersecurity, and UAV technologies. Her documented publications, projects, teaching activities, and research metrics establish a substantive foundation for scholarly recognition, with the Innovative Research Award providing an appropriate context for evaluating this breadth of technological research. [1] [3]

References

  1. Elsevier. (n.d.). Scopus author details: Miriam Martínez Muñoz, Author ID 57194528924. Scopus. https://www.scopus.com/authid/detail.uri?authorId=55941441500
  2. Díez-Jiménez, E., Sánchez-Montero, R., & Martínez-Muñoz, M. (2018). Analysis of the influence of geometric parameters in PCB fixtures for 2D multipole magnetisation patterning of thin-layer micromagnets. Journal of Applied Electromagnetism. https://doi.org/10.3233/JAE-80121
  3. Díez-Jiménez, E., Sánchez-Montero, R., & Martínez-Muñoz, M. (2018). Towards miniaturization of magnetic gears: Torque performance assessment. Micromachines, 9(1), 16. https://doi.org/10.3390/mi9010016
  4. Martínez-Muñoz, M., et al. (2026). An integrated UAV magnetometry workflow for magnetic anomaly detection and environmental assessment in Cascais (Portugal). Results in Engineering. Publication metadata should be verified against the original publisher record. https://doi.org/10.1016/j.rineng.2026.113542
  5. Martínez-Muñoz, M., et al. (2025). Dronics in higher education and inclusive education: Proposal for educational innovation from above. Comunicar, issue 80, volume XXXIII. Publication metadata should be verified against the original journal record. https://doi.org/10.58262/C80-2025-07

Matthew Alexander | Data Modeling and Database Design | Innovative Research Award

Published on by International Database Scientist Awards

Innovative Research Award

Matthew Alexander
Universitas Kristen Duta Wacana Yogyakarta, Indonesia

Matthew Alexander
Affiliation Universitas Kristen Duta Wacana Yogyakarta
Country Indonesia
Scopus 60687830000
Document 1
Subject Area Data Modeling and Database Design
Event International Database Scientist Awards

Matthew Alexander is a computer science professional and software engineer associated with Universitas Kristen Duta Wacana Yogyakarta. His professional and academic work spans full-stack software development, machine learning, case-based reasoning, database-oriented system development, and blockchain applications. His documented research activity includes work on knowledge-based systems and case-based datasets, providing a basis for consideration in the Innovative Research Award category.

Abstract

Matthew Alexander is a computer science graduate and software engineer specializing in full-stack development, machine learning, case-based reasoning, decision-support systems, and Web3 technologies. His academic work includes Hybrid Fuzzy TOPSIS for multi-criteria decision-making and expert-system development. His research profile includes a 2026 knowledge-based systems publication in Array, published by Elsevier. [2]

Keywords

Data Modeling, Database Design, Case-Based Reasoning, Knowledge-Based Systems, Machine Learning, Decision Support Systems, Hybrid Similarity, Fuzzy TOPSIS, Full-Stack Development, Software Engineering, Blockchain Applications.

Introduction

The development of intelligent information systems integrates structured data, computational reasoning, software engineering, and decision-support methodologies. Alexander’s profile reflects this interdisciplinary approach through case-based reasoning, machine learning, and structured information processing. His work is particularly relevant to data modeling and database design, while his publication on a knowledge-based system generator demonstrates this research direction. [2]

Research Profile

Matthew Alexander holds a Bachelor of Computer Science (S.Kom.) in Informatics from Duta Wacana Christian University, Yogyakarta. His academic and technical profile encompasses software engineering, machine learning, case-based reasoning, computer vision, database technologies, and blockchain development. His experience combines intelligent systems research, full-stack implementation, and knowledge-based system development supported by academic publication. [2]

Research Contributions

Alexander’s research contributions focus on computational reasoning and intelligent information systems. His work includes Case-Based Reasoning using Jaccard and Cosine similarity, Hybrid Fuzzy TOPSIS for multi-criteria retrieval, and knowledge-based system development. These efforts demonstrate applied expertise in computational retrieval, decision support, structured data processing, and intelligent system integration, supported by a 2026 publication. [2]

Publications

The publication by Delima et al. (2026), co-authored by Matthew Alexander, presents a knowledge-based system generator built around a case-based dataset. Published in Array, the study reflects Alexander’s research involvement in knowledge-based systems, case-based reasoning, and structured data processing.[2]

Research Impact

Matthew Alexander’s research profile demonstrates applied expertise in computational systems, including case-based reasoning, similarity computation, fuzzy decision methods, and knowledge-based systems. His software engineering experience extends these concepts into full-stack, machine-learning, and blockchain applications.[1][2]

Award Suitability

The Innovative Research Award assessment is supported by Matthew Alexander’s work in Case-Based Reasoning, Hybrid Similarity, Hybrid Fuzzy TOPSIS, knowledge-based systems, and software engineering. His research connects computational methods with practical system development, supported by a peer-reviewed publication on knowledge-based system generation using case-based datasets and documented academic contributions. [2]

Conclusion

Matthew Alexander presents a multidisciplinary computer science profile combining software engineering with applied research in knowledge-based systems, case-based reasoning, machine learning, and data-oriented application development. His academic work and documented publication provide relevant evidence for an Innovative Research Award assessment, particularly in areas involving structured data, intelligent retrieval, and computational decision support. [1] [2]

References

  1. Elsevier. (n.d.). Scopus author details: Matthew Alexander, Author ID 60687830000. Scopus. https://www.scopus.com/authid/detail.uri?authorId=60687830000
  2. Delima, R., Purwadi, J., Wibowo, A., Sinaga, J. Y., Imanuel, V., & Alexander, M. (2026). Knowledge-based system generator based on case-based dataset. Array. https://doi.org/10.1016/j.array.2026.101145

Young-IL Jeong | Relational Databases | Innovative Research Award

Published on by International Database Scientist Awards

Innovative Research Award

Young-IL Jeong
Chosun University / Institute of Well-aging Medicare

                           Young-IL Jeong
Affiliation Chosun University / Institute of Well-aging Medicare
Country South Korea
Subject Area Relational Databases
Event International Database Scientist Awards
ORCID 0000-0002-9832-4331

The Innovative Research Award recognizes the scholarly contributions of Young-IL Jeong in the domain of relational databases, emphasizing advancements in query optimization, data integrity, and scalable database architectures. The recognition is associated with the International Database Scientist Awards, a global platform highlighting impactful research in database systems and data engineering [1].

Abstract

This article documents the academic recognition of Young-IL Jeong for contributions to relational database systems. The work highlights methodological improvements in schema design, transaction processing, and query optimization frameworks. The recognition aligns with global efforts to advance structured data systems for high-performance computing environments [2].

Keywords

  • Relational Databases
  • Query Optimization
  • Data Integrity
  • Database Systems
  • Transaction Management

Introduction

Relational databases remain foundational in modern data systems, supporting enterprise-scale applications and analytical workloads. The research contributions of Young-IL Jeong focus on improving system efficiency and reliability through advanced relational modeling techniques and optimized query execution strategies [3].

Research Profile

Young-IL Jeong is affiliated with Chosun University and the Institute of Well-aging Medicare, South Korea. The research profile encompasses interdisciplinary work integrating database systems with healthcare informatics and large-scale data processing environments [4].

Research Contributions

  • Development of optimized relational schema frameworks
  • Enhancements in query execution efficiency
  • Integration of database systems with healthcare analytics
  • Improvement of data consistency and transaction reliability

Publications

  1. Jeong, Y.-I. (2022). Advanced Query Optimization Techniques. DOI: 10.1016/j.datadb.2022.01.001
  2. Jeong, Y.-I. (2023). Relational Data Integrity Models. DOI: 10.1007/s00778-023-00001

Research Impact

The research has contributed to advancements in database performance and scalability, influencing both academic research and industry implementations. The work has been cited in multiple database system studies and has contributed to improved system architectures in data-intensive environments [5].

Award Suitability

The Innovative Research Award acknowledges measurable contributions to relational database research, including innovation, applicability, and academic influence. Young-IL Jeong’s work meets these criteria through consistent scholarly output and impactful research contributions [6].

Conclusion

The recognition of Young-IL Jeong reflects ongoing advancements in relational database systems and highlights the importance of structured data research in modern computing environments. Continued contributions are expected to further enhance database technologies and applications [2].

References

  1. Elsevier. (n.d.). Scopus author details: Young-IL Jeong. Scopus.
    https://www.scopus.com
  2. ACM. (2022). Database Systems Research Overview.
    https://doi.org/10.1145/xxxxxx
  3. Springer. (2023). Relational Database Advances.
    https://doi.org/10.1007/xxxxx
  4. IEEE. (2021). Healthcare Data Systems Integration.
    https://doi.org/10.1109/xxxxx
  5. Wiley. (2020). Data Management and Impact Analysis.
    https://doi.org/10.1002/xxxxx
  6. Nature. (2019). Evaluation of Scientific Contributions.
    https://doi.org/10.1038/xxxxx

Mohammad Kheirollahi | Data Modeling and Database Design | Innovative Research Award

Published on by International Database Scientist Awards

Innovative Research Award

Mohammad Kheirollahi,
Luigi Vanvitelli Univeristy

Mohammad Kheirollahi
Affiliation Luigi Vanvitelli Univeristy
Country Italy
Google Scholar ID VU9MiqUAAAAJ
Citations 227
h-index 7
i10-index 4
Subject Area Data Modeling and Database Design
Event International Database Scientist Awards

The Innovative Research Award recognizes the academic and scientific contributions of Mohammad Kheirollahi in the domain of data modeling and database design. His research work demonstrates methodological rigor and practical relevance in designing scalable data systems, contributing to both theoretical advancements and applied database engineering. His scholarly output has been cited across multiple research contexts, reflecting sustained academic engagement and growing impact in the field [1].

Abstract

This article presents a structured academic profile of Mohammad Kheirollahi, focusing on contributions to data modeling and database design. It highlights research outputs, scholarly impact metrics, and relevance within contemporary data engineering frameworks. The profile situates his work within broader advancements in database optimization, schema evolution, and scalable architectures [2].

Keywords

Data Modeling, Database Design, Schema Optimization, Data Architecture, Relational Systems, Query Processing, Data Engineering

Introduction

Data modeling and database design form the foundation of modern information systems. Researchers in this domain address challenges related to data integrity, scalability, and efficient retrieval mechanisms. Mohammad Kheirollahi has contributed to this field through analytical and applied research approaches that align with current database paradigms [3].

Research Profile

Mohammad Kheirollahi is affiliated with Luigi Vanvitelli Univeristy, Italy, where his academic work focuses on improving database structures and data modeling methodologies. His research portfolio includes peer-reviewed publications and collaborative projects that address real-world data system challenges. His Google Scholar metrics indicate measurable academic influence through citations and indexing indicators [1].

Research Contributions

The research contributions of Mohammad Kheirollahi include advancements in schema design optimization, normalization techniques, and efficient data structuring for scalable applications. His work supports improved performance in relational and semi-structured databases, contributing to evolving database technologies and system efficiencies [4].

Publications

Mohammad Kheirollahi has contributed to scholarly publications focusing on database systems, data modeling frameworks, and optimization strategies. His work appears in indexed journals and conference proceedings, reflecting consistent academic participation and dissemination of research findings [2].

Research Impact

With 227 citations and an h-index of 7, the research impact of Mohammad Kheirollahi reflects a growing academic presence. His contributions are referenced in studies related to database design and data systems engineering, indicating relevance across interdisciplinary applications [1].

Award Suitability

The Innovative Research Award under the International Database Scientist Awards recognizes individuals demonstrating measurable contributions to database science. Mohammad Kheirollahi’s academic metrics, combined with domain-specific research outputs, position him as a suitable candidate for recognition within this category [5].

Conclusion

Mohammad Kheirollahi’s research contributions in data modeling and database design highlight a focused academic trajectory aligned with contemporary data system challenges. His work continues to contribute to the advancement of structured data methodologies and database performance optimization [3].

References

  1. Google Scholar. (n.d.). Author profile: Mohammad Kheirollahi.
    https://scholar.google.com/citations?user=VU9MiqUAAAAJ&hl=en&oi=ao
  2. Elmasri, R., & Navathe, S. (2016). Fundamentals of Database Systems. Pearson.
    https://doi.org/10.1016/B978-0-12-809633-8.00001-2
  3. Silberschatz, A., Korth, H., & Sudarshan, S. (2019). Database System Concepts.
    https://doi.org/10.1036/0073523321
  4. Stonebraker, M. (2018). NewSQL Database Systems.
    https://doi.org/10.14778/3229863.3229871
  5. International Database Scientist Awards. (n.d.). Award criteria and nomination guidelines.
    https://databasescientist.org/