Wael Alnahari | Federated Databases | Innovative Research Award

Published on by International Database Scientist Awards

Innovative Research Award

Wael Alnahari — King AbdulAziz University, Saudi Arabia

Wael Alnahari
Affiliation King AbdulAziz University
Country Saudi Arabia
Scopus 57223959943
Documents 4
Citations 34
h-index 3
Subject Area Federated Databases
Event International Database Scientist Awards
ORCID 0000-0001-5247-3713

Wael Alnahari is a Saudi computer and information systems researcher and PhD candidate at King AbdulAziz University whose scholarly work addresses federated databases, Internet of Things (IoT) security, and data management in smart-city environments. His research is indexed in Scopus [1]. This page summarizes his research profile in the context of the Innovative Research Award presented at the International Database Scientist Awards [5].

Abstract

This article presents an academic overview of Wael Alnahari, a researcher affiliated with King AbdulAziz University, Saudi Arabia. His work spans federated database systems, sovereignty-aware business intelligence, large language model evaluation for text-to-SQL tasks, and security and privacy in IoT and smart-city infrastructures. Bibliometric data from Scopus indicate four indexed documents, 34 citations, and an h-index of 3 [1]. The article reviews his research profile, principal contributions, selected publications, and relevance to the Innovative Research Award.

Keywords

Federated databases; business intelligence; text-to-SQL; large language models; Internet of Things security; device authentication; privacy; smart cities; cybersecurity; business continuity.

Introduction

Federated databases enable autonomous data sources to be queried without full centralization, which suits settings with strict governance and security constraints. Wael Alnahari, a PhD candidate at King AbdulAziz University with a cybersecurity master’s degree, combines database research with extensive professional cybersecurity leadership experience. His work is indexed in Scopus.[1].

Research Profile

Wael Alnahari’s research has progressed from IoT security, covering authentication, sensor-level requirements, and privacy risks [2][3][4], toward federated data architectures and language-model database querying. His background in business continuity and security risk management shapes the applied focus of his scholarship.

Research Contributions

Wael Alnahari’s contributions span IoT authentication using security keys [2], sensor security requirements [3], and smart-city privacy risks [4]. His recent work evaluates large language models for text-to-SQL generation [5] and proposes sovereignty-aware risk assessment infrastructure for federated business intelligence, known as SARAI [1].

Publications

Wael Alnahari’s Scopus-listed publications include conference papers on IoT device and server authentication using security keys [2], IoT sensor security requirements [3], and privacy concerns in smart cities [4], alongside an IEEE Access study on complexity-tiered text-to-SQL performance of large language models in smart-city decision support [5].

Research Impact

According to Scopus, Alnahari has four indexed documents, 34 citations, and an h-index of 3 [1]. For a researcher at an early stage of doctoral study, these indicators suggest that his earlier IoT security publications have been used by other scholars, while his recent database-focused work is still developing its readership. Bibliometric figures vary over time and across databases, and should be interpreted alongside the substance of the work.

Award Suitability

The International Database Scientist Awards recognize contributions to database science and related fields [5]. Alnahari’s nomination for the Innovative Research Award reflects his focus on federated databases, the link between data governance and cybersecurity, language-model-based query generation, and peer-reviewed publications. His practical experience in risk management and business continuity strengthens the applied relevance of his work.

Conclusion

Wael Alnahari is an emerging researcher whose work connects federated database systems, IoT security, and language-model-based data access. His Scopus-indexed publications, citation record, and interdisciplinary background provide a reasonable basis for consideration under the Innovative Research Award [1]. Continued doctoral research is expected to extend his contributions in sovereignty-aware and secure data infrastructures.

References

  1. Elsevier. (n.d.). Scopus author details: Wael Alnahari, Author ID 57223959943. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57223959943
  2. Alnahari, W., & Quasim, M. T. (2021). Authentication of IoT device and IoT server using security key. In 2021 International Congress of Advanced Technology and Engineering (ICOTEN) (pp. 1–9). https://doi.org/10.1109/ICOTEN52080.2021.9493492
  3. Alqarni, H., Alnahari, W., & Quasim, M. T. (2021). Internet of things (IoT) security requirements: Issues related to sensors. In 2021 National Computing Colleges Conference (NCCC) (pp. 1–6). https://doi.org/10.1109/NCCC49330.2021.9428857
  4. Alnahari, W., & Quasim, M. T. (2021). Privacy concerns, IoT devices and attacks in smart cities. In 2021 International Congress of Advanced Technology and Engineering (ICOTEN) (pp. 1–5). https://doi.org/10.1109/ICOTEN52080.2021.9493559
  5. Alnahari, W., Hasanin, T., & Jambi, S. (n.d.). Complexity-tiered text-to-SQL performance of large language models in smart-city decision support. IEEE Access. https://doi.org/10.1109/ACCESS.2026.3728618

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

Mawloud Titah | Knowledge Graphs | Innovative Research Award

Published on by International Database Scientist Awards

Innovative Research Award

Mawloud Titah — Associate Professor of Industrial Engineering, University of Oran 2 Mohamed Ben Ahmed, Algeria

Mawloud Titah
Affiliation University of Oran 2 Mohamed Ben Ahmed
Country Algeria
Scopus 57194528924
Documents 10
Citations 30
h-index 3
Subject Area Knowledge Graphs
Event International Database Scientist Awards
ORCID 0000-0002-0632-5450

Mawloud Titah is an Associate Professor at the Institute of Maintenance and Industrial Safety, University of Oran 2 Mohamed Ben Ahmed, and a researcher at the LISIDD laboratory in Algeria. His research focuses on knowledge engineering, ontologies, knowledge graphs and semantic reasoning for explainable decision support, particularly in healthcare equipment maintenance and pharmaceutical logistics. [1]

Abstract

Mawloud Titah’s research addresses knowledge-driven decision support through ontology engineering, semantic technologies and knowledge graphs. His work applies OWL, SWRL, SQWRL and SPARQL to healthcare problems including medical-device maintenance, equipment criticality and pharmaceutical logistics. The research emphasizes transparent knowledge representation, semantic interoperability and explainable reasoning for operational healthcare decision-support systems. [1]

Keywords

Knowledge graphs; knowledge engineering; ontology engineering; OWL; SWRL; SQWRL; SPARQL; semantic reasoning; healthcare decision support; medical-device maintenance; pharmaceutical logistics; knowledge representation; explainable decision support; CommonKADS; semantic interoperability.

Introduction

Mawloud Titah’s academic work connects industrial engineering with knowledge-based information systems. His research trajectory includes tacit-knowledge externalization and CommonKADS before extending toward semantic models for healthcare. This progression places formal knowledge representation at the centre of decision-support development, using structured ontologies and rule-based inference to make domain knowledge explicit and computationally queryable. [2]

Research Profile

Mawloud Titah is an Associate Professor and researcher at the Institute of Maintenance and Industrial Safety, University of Oran 2 Mohamed Ben Ahmed, and is associated with the LISIDD laboratory. His stated research interests include ontology-driven knowledge modelling, semantic reasoning, knowledge graphs and explainable decision support for healthcare systems, particularly maintenance, medical-device risk and pharmaceutical logistics. [1] His technical research uses OWL and OWL 2 ontologies, SWRL rules, SQWRL and SPARQL queries, with tools including Protégé Editor and GraphDB. Earlier work addressed knowledge acquisition and the formalization of tacit manufacturing knowledge through the CommonKADS methodology, providing a foundation for later knowledge-based applications. [2]

Research Contributions

Mawloud Titah’s research develops explainable knowledge-graph and ontology-driven frameworks for healthcare decision support. His contributions address risk-aware medical-device maintenance, equipment criticality assessment, and pharmaceutical logistics. By integrating OWL ontologies, semantic rules, SPARQL and knowledge graphs, his work supports transparent prioritisation, knowledge sharing, traceability and interoperability, providing structured approaches for practical and explainable healthcare management and decision-making.[3][4][5]

Publications

Mawloud Titah’s publications span knowledge engineering, healthcare maintenance, semantic technologies and tacit-knowledge management. His recent studies examine explainable knowledge graphs for medical-device maintenance and ontology-driven hospital equipment management, while earlier work addresses tacit-knowledge reuse. Together, these publications demonstrate a progression from knowledge externalization and management toward semantic, ontology-based approaches for explainable healthcare decision support and knowledge-driven systems.[3] [4][5][6]

Research Impact

The reported research impact is concentrated in the application of semantic knowledge technologies to operational healthcare problems. The combination of ontology engineering, knowledge graphs and rule-based inference provides a framework for representing maintenance and logistics knowledge in a form that can be queried and inspected. Scopus records supplied for this profile list 10 documents, 30 citations and an h-index of 3. [1]

Award Suitability

Mawloud Titah’s research profile is closely aligned with database and knowledge-graph research through its emphasis on formal knowledge representation, semantic querying, interoperability and structured healthcare information. His work connects knowledge graphs and ontologies with practical decision-support applications, making the profile relevant to recognition focused on database science, semantic data technologies and knowledge-driven systems. [1]

Conclusion

Mawloud Titah’s research represents an interdisciplinary pathway from industrial knowledge management to ontology-based and knowledge-graph-driven healthcare decision support. His publications address semantic modelling, explainable reasoning, equipment maintenance and pharmaceutical logistics, while his technical work employs established semantic-web standards and tools. The profile therefore demonstrates sustained engagement with structured knowledge and database-related technologies. [3] [4]

References

  1. Elsevier. (n.d.). Scopus author details: Mawloud Titah, Author ID 57194528924. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57194528924
  2. Titah, M., Aitouche, S., Mouss, M. D., & Soussa, A. (2017). Externalising and reusing tacit knowledge in manufacturing tasks. International Journal of Knowledge Management Studies, 8(3–4), 351–374. https://doi.org/10.1504/IJKMS.2017.087078
  3. Titah, M., & Bouchaala, M. A. (2026). An explainable knowledge graph framework for risk-aware maintenance of medical devices. Network Modeling Analysis in Health Informatics and Bioinformatics, 15, 179. https://doi.org/10.1007/s13721-026-00827-y
  4. Titah, M., & Bouchaala, M. A. (2024). An ontology-driven model for hospital equipment maintenance management: A case study. Journal of Quality in Maintenance Engineering, 30(2), 409–433. https://doi.org/10.1108/JQME-10-2023-0097
  5. Bouzidi, K. R., Titah, M., & Mekki, I. E. K. (2026). ODTIC-KG: A knowledge graph framework for proactive oncology drug inventory management in hospitals. International Journal of Medical Informatics, 106677. https://doi.org/10.1016/j.ijmedinf.2026.106677
  6. Titah, M., & Hachemi, K. (2024). Improvement of human performance in healthcare systems by taking into account physician behavior. Journal of Health Organization and Management, 38(6), 888–904. https://doi.org/10.1108/JHOM-01-2024-0029

Saeid Rezaei | Query Optimization | Innovative Research Award

Published on by International Database Scientist Awards

Innovative Research Award

Saeid Rezaei — Bu-Ali Sina University, Iran
Saeid Rezaei
Affiliation Bu-Ali Sina University
Country Iran
Google Scholar rnUbxhAAAAAJ
Documents 32
Citations 275
h-index 8
Subject Area Query Optimization
Event International Database Scientist Awards
Scopus 56982653700

Saeid Rezaei is a researcher and lecturer affiliated with Bu-Ali Sina University in Iran. His academic profile combines industrial engineering, operations research, supply chain and logistics, sustainable development, optimization, decision-making, and data-oriented analytical methods. His documented publications include studies of sustainable closed-loop supply chains, cross-docking, reverse logistics, competitive networks, and virtual alliances.[1]

Abstract

Saeid Rezaei’s academic work is situated primarily within industrial engineering and operations research, with research interests spanning supply chain and logistics, sustainable development, multi-objective decision-making, game theory, production planning, transportation planning, and data analysis. His publication record includes research on sustainable closed-loop supply chains, cross-docking operations, reverse logistics, competitive supply networks, and virtual alliances.[1][2]

Keywords

Industrial Engineering; Query Optimization; Operations Research; Supply Chain Management; Sustainable Supply Chains; Closed-Loop Supply Chains; Cross-Docking; Reverse Logistics; Multi-Objective Decision Making; Game Theory; Data Analysis; Production Planning; Logistics.

Introduction

Saeid Rezaei’s academic profile reflects an interdisciplinary approach to industrial engineering and decision sciences. His stated interests include supply chain and logistics, competitive planning, sustainable development, operations research, production and service strategy, transportation planning, and engineering economy. These areas provide a methodological context for his published studies of network design and optimization.[1][2]

Research Profile

Saeid Rezaei holds a Ph.D. in Industrial Engineering from the Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran. His professional background includes university lecturing and industry consulting, with research interests spanning supply chain and logistics, operations research and optimization, multi-objective decision-making, game theory, sustainable development, production planning, data analysis, and computational methods. His technical skills include GAMS, MATLAB, Python, RapidMiner, SPSS, Microsoft Project, and engineering and statistical methods.

Research Contributions

Saeid Rezaei’s documented research contributions address sustainable closed-loop supply chain network design, cross-docking, reverse logistics, competitive supply networks, and partnership structures. One study develops a comprehensive approach combining sustainable closed-loop network design with cross-docking operations, while later work examines competitive and sustainable decisions across multi-echelon supply chains.[1][2]

Publications

Saeid Rezaei’s publications focus on sustainable supply chain networks, closed-loop logistics, cross-docking operations, reverse logistics, competitive supply networks, and virtual alliances. His research examines optimization-based approaches to sustainable production, multi-echelon supply chains, strategic decision-making, and partnership structures. His scholarly work has appeared in international journals, including Computational and Mathematical Organization Theory, Environment, Development and Sustainability, Production Engineering, and Journal of Cleaner Production, demonstrating continued contributions to quantitative modeling, supply chain optimization, sustainability, and operations research. [2][3][4][5][6]

Research Impact

The supplied Google Scholar profile records 32 documents, 275 citations, and an h-index of 8. These figures are profile-level bibliometric indicators and should be interpreted according to the indexing coverage, date of retrieval, and citation practices of the underlying database.[1]

Award Suitability

For the International Database Scientist Awards, the supplied profile provides documented evidence of research activity in optimization, quantitative decision-making, data analysis, and computational approaches. His publication record also demonstrates sustained work on network optimization and analytical supply-chain models, providing research areas that can be considered in the context of an Innovative Research Award nomination.[1][6]

Conclusion

Saeid Rezaei’s documented academic profile combines industrial engineering, operations research, optimization, supply chain management, sustainability, and data analysis. His selected publications provide evidence of research on closed-loop networks, cross-docking, reverse logistics, competitive supply networks, and virtual alliances, while the supplied scholarly metrics provide additional bibliometric context.[1][2][6]

References

  1. Google Scholar. (n.d.). Saeid Rezaei, Google Scholar profile, user ID rnUbxhAAAAAJ. https://scholar.google.com/citations?user=rnUbxhAAAAAJ&hl=en
  2. Rezaei, S., & Kheirkhah, A. (2018). A comprehensive approach in designing a sustainable closed-loop supply chain network using cross-docking operations. Computational and Mathematical Organization Theory, 24(1), 51–98. https://doi.org/10.1007/s10588-017-9247-3
  3. Rezaei, S., & Maihami, R. (2020). Optimizing the sustainable decisions in a multi-echelon closed-loop supply chain of the manufacturing/remanufacturing products with a competitive environment. Environment, Development and Sustainability, 22(7), 6445–6471. https://doi.org/10.1007/s10668-019-00491-5
  4. Kheirkhah, A., & Rezaei, S. (2016). Using cross-docking operations in a reverse logistics network design: A new approach. Production Engineering, 10(2), 175–184. https://doi.org/10.1007/s11740-015-0646-3
  5. Rezaei, S., & Kheirkhah, A. (2017). Applying forward and reverse cross-docking in a multi-product integrated supply chain network. Production Engineering, 11(4), 495–509. https://doi.org/10.1007/s11740-017-0743-6
  6. Rezaei, S., & Behnamian, J. (2021). A survey on competitive supply networks focusing on partnership structures and virtual alliance: New trends. Journal of Cleaner Production, 287, 125031. https://doi.org/10.1016/j.jclepro.2020.125031

Upasana Haldar | Transaction Management | Innovative Research Award

Published on by International Database Scientist Awards

Innovative Research Award

Upasana Haldar
Affiliation Indian Institute of Technology Kharagpur
Country India
ORCID ID 0009-0005-2207-1103
Scopus ID 60586555200
Citations 2
h-index 2
i10-index 1
Subject Area Transaction Management
Event International Database Scientist Awards

Upasana Haldar
Indian Institute of Technology Kharagpur

Upasana Haldar is a researcher affiliated with the Indian Institute of Technology Kharagpur, India, whose scholarly work contributes to the field of transaction management and database systems. Through academic investigations focused on data consistency, reliability, and information management methodologies, the researcher has demonstrated engagement with contemporary database science challenges. The profile presented here summarizes academic contributions, research interests, publication activities, and the relevance of these achievements to the Innovative Research Award under the International Database Scientist Awards program.[1]

Abstract

This article presents a scholarly overview of Upasana Haldar’s academic profile, emphasizing research interests associated with transaction management, database reliability, and data-centric computing environments. The profile highlights academic achievements, publication contributions, citation performance, and research relevance within the broader context of database science. The assessment is structured in a manner consistent with academic recognition documentation and provides insight into the researcher’s suitability for professional distinction through the Innovative Research Award.[1]

Keywords

Transaction Management, Database Systems, Data Consistency, Distributed Databases, Data Integrity, Information Systems, Database Optimization, Academic Research, Database Reliability, Data Science.

Introduction

Database technologies continue to serve as foundational components of modern information infrastructures. Transaction management remains one of the most critical research domains within database science due to its direct influence on consistency, concurrency control, fault tolerance, and reliable data processing. Researchers working in this field contribute to the development of systems capable of maintaining data integrity across increasingly complex computing environments.[2]

Research Profile

Upasana Haldar is associated with the Indian Institute of Technology Kharagpur, one of India’s leading institutions for engineering, technology, and scientific research. The researcher’s academic interests are centered on transaction management and database-related methodologies that support robust information systems. Research activities contribute to understanding the mechanisms required for maintaining data consistency and operational reliability in modern computing environments.[1]

Research Contributions

Research contributions in transaction management typically address challenges associated with concurrency control, transaction scheduling, recovery mechanisms, distributed processing, and consistency preservation. Work in this domain supports reliable operations across enterprise systems, cloud platforms, and data-intensive applications.[2][3]

Publications

The available author profile indicates scholarly publication activity within database-related research domains. Publications associated with transaction management contribute to the scientific understanding of database reliability, consistency mechanisms, and advanced information processing techniques.[1]

Area Research Focus
Transaction Management Consistency, concurrency, and transactional reliability.
Database Systems Data storage, retrieval, and optimization methodologies.
Information Management Efficient handling and governance of structured information.

Research Impact

Research impact may be assessed through citation performance, scholarly dissemination, institutional affiliations, and influence on subsequent studies. The available metrics indicate a citation count of two, an h-index of two, and an i10-index of one, demonstrating measurable recognition of published work within academic literature.[1][2]

Award Suitability

The Innovative Research Award recognizes researchers who demonstrate meaningful academic contributions, methodological innovation, and commitment to advancing scientific knowledge. Upasana Haldar’s research engagement in transaction management and database systems aligns with the objectives of the International Database Scientist Awards program.[4]

Conclusion

Upasana Haldar’s academic profile reflects engagement with significant topics in transaction management and database science. Through research activities associated with the Indian Institute of Technology Kharagpur, the researcher contributes to scholarly discussions concerning data reliability, consistency, and information system performance. The profile demonstrates emerging academic impact and supports recognition through the Innovative Research Award under the International Database Scientist Awards framework.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Upasana Haldar, Author ID 60586555200. Scopus Author Profile.
    https://www.scopus.com/pages/authors/60586555200
  2. ORCID author details: Upasana Haldar, Author ID 0009-0005-2207-1103.
    https://orcid.org/0009-0005-2207-1103
  3. Integrating Battery-as-a-Service (BaaS) in mobility electrification: A structured review and future research agenda.
    https://www.sciencedirect.com/science/article/pii/S0967070X26001587
  4. International Database Scientist Awards. (n.d.). Award Program Overview and Recognition Framework.
    https://databasescientist.org/