Innovative Research Award
| Laila Aladwey | |
|---|---|
| Affiliation | Imam Mohammad Ibn Saud Islamic University |
| Country | Saudi Arabia |
| Scopus ID | 57223873822 |
| Documents | 18 |
| Citations | 176 |
| h-index | 7 |
| Subject Area | Innovation in Data Analysis |
| Event | Research Data Analysis Awards |
| ORCID | 0000-0003-4445-4138 |
Laila Aladwey
Imam Mohammad Ibn Saud Islamic University
Laila Aladwey is a researcher affiliated with Imam Mohammad Ibn Saud Islamic University, Saudi Arabia, whose scholarly work focuses on innovation in data analysis and related computational methodologies. Her publication record, citation performance, and sustained research activity demonstrate continued contributions to analytical research and interdisciplinary scientific development.[1]
Contents
Abstract
This article summarizes the academic profile of Laila Aladwey, highlighting research productivity, scholarly influence, and contributions within innovation in data analysis. The profile reflects measurable research indicators and recognized publication activity across peer-reviewed scientific literature.[2]
Keywords
Innovation in Data Analysis, Data Science, Computational Analytics, Machine Learning, Artificial Intelligence, Scientific Research, Information Systems, Research Evaluation.
Introduction
Innovation in data analysis supports evidence-based decision-making by combining computational techniques with domain knowledge. Researchers in this field contribute to improved analytical methods, data interpretation, and scientific advancement across multidisciplinary applications.[3]
Research Profile
Laila Aladwey has authored 18 indexed publications with 176 citations and an h-index of 7. These indicators illustrate consistent scholarly engagement and a growing academic presence within innovation-oriented data analysis research.[1]
Research Contributions
Her research contributes to analytical methodologies, intelligent data processing, and practical applications that support knowledge discovery. The published studies demonstrate interdisciplinary collaboration and methodological development aligned with current research priorities.[4]
Publications
The publication portfolio includes peer-reviewed journal articles indexed in internationally recognized databases. These works collectively strengthen research visibility while supporting ongoing scientific communication and academic collaboration.[2]
Research Impact
Citation metrics and publication performance indicate that the research has received measurable scholarly attention. Such indicators provide evidence of academic influence and continuing engagement within the broader research community.[5]
Award Suitability
Based on available scholarly metrics, publication quality, and demonstrated research activity, Laila Aladwey presents a profile consistent with recognition in academic excellence programs emphasizing innovation in data analysis and research contributions.[1]
Conclusion
The available bibliometric evidence reflects a productive academic career supported by peer-reviewed publications and recognized citation performance. Continued research activity is expected to further strengthen contributions to innovation in data analysis and interdisciplinary scientific research.
External Links
References
- Elsevier. (n.d.). Scopus author details: Laila Aladwey, Author ID 57223873822. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=57223873822 - ORCID. (n.d.). ORCID record for Laila Aladwey.
https://orcid.org/0000-0003-4445-4138 - Aladwey, L. M. A., Mkadmi, J. E., Necib, A., & Zehri, F. (2026). The relationship between corporate governance and stock returns: The moderating role of intellectual capital. Social Sciences & Humanities Open, 102489
- Aladwey, L. M. A. (2026). Does board diversity influence green revenue and firm value? Evidence from an emerging market. Emerging Science Journal, 10(1), 25
https://oipub.com/papers/401122932 - Aladwey, L., Elsayed, M. F. M., & Diab, A. (2025). Breaking barriers: Gender diversity, ESG, and corporate misconduct in the GCC region. Risks, 13(5), 97.
https://www.mdpi.com/2227-9091/13/5/97