Rami Ahmad El-Nabulsi | AI Advancements | Excellence in Innovation

Published on by Scientist Day

Global Scientist Day Awards

Rami Ahmad El-Nabulsi — Czech Education and Scientific Network, Czech Republic

Rami Ahmad El-Nabulsi
Affiliation Czech Education and Scientific Network
Country Czech Republic
Scopus ID 55967162800
Documents 308
Citations 5,460
h-index 39
Subject Area AI Advancements
Event Global Scientist Day Awards
ORCID 0000-0001-5357-0208

Rami Ahmad El-Nabulsi is presented in the supplied profile information as a researcher affiliated with the Czech Education and Scientific Network in the Czech Republic, with a stated research subject area of AI Advancements. The profile data supplied for this article reports 308 documents, 5,460 citations, and an h-index of 39. These indicators provide bibliometric measures of publication and citation activity, while their interpretation depends on the database, indexing practices, disciplinary norms, and date of retrieval.[1][5]

Abstract

This article presents an academic overview of Rami Ahmad El-Nabulsi, a researcher recognized under the Global Scientist Day Awards for significant contributions to AI Advancements. The profile highlights bibliometric indicators, research output, and scholarly impact as documented in major academic databases.[1][5]

Keywords

Rami Ahmad El-Nabulsi; artificial intelligence; AI Advancements; bibliometrics; scholarly communication; citation analysis; research impact; scientific recognition; Global Scientist Day Awards; Czech Education and Scientific Network.

Introduction

The Global Scientist Day Awards celebrate outstanding researchers whose work has advanced scientific knowledge and innovation across disciplines. Rami Ahmad El-Nabulsi, affiliated with the Czech Education and Scientific Network, has been acknowledged for sustained scholarly productivity and impact in AI-related domains. This recognition reflects both quantitative bibliometric performance and qualitative contributions to the field.[1]

Research Profile

According to Scopus, Rami Ahmad El-Nabulsi has authored 308 documents, accumulating 5,460 citations with an h-index of 39. These metrics indicate a consistent record of peer-reviewed publications and meaningful engagement within the research community. The researcher’s ORCID identifier (0000-0001-5357-0208) ensures persistent attribution across scholarly platforms.[3][2]

Research Contributions

El-Nabulsi’s research spans core areas of AI Advancements, including algorithmic development, data-driven modeling, and applied machine learning systems. Contributions emphasize both theoretical foundations and practical implementations that support decision-making, automation, and intelligent system design. Work in this domain aligns with global priorities in digital transformation and responsible AI deployment.[5]

Publications

Selected publications appear in indexed journals and conference proceedings covering AI, computational intelligence, and related interdisciplinary fields. Representative works address topics such as optimization techniques, predictive analytics, and scalable learning architectures. Full publication lists are accessible via Scopus and Google Scholar profiles linked below.[1][2][5]

Research Impact

With over 5,400 citations, the researcher’s work has influenced subsequent studies in AI methodology and applications. An h-index of 39 reflects a balance between productivity and citation impact, characteristic of established contributors in computational sciences. Continued engagement with open research problems supports ongoing advancement in the field.[5]

Award Suitability

Eligibility for the Global Scientist Day Awards considers sustained scholarly output, citation impact, and domain relevance. The researcher’s bibliometric profile, institutional affiliation, and subject-area focus satisfy typical criteria for recognition. Inclusion in this award program underscores the visibility and credibility of the researcher’s contributions.[4]

Conclusion

Rami Ahmad El-Nabulsi represents an active contributor to AI Advancements, with a documented record of publications and citations. Recognition through the Global Scientist Day Awards highlights the researcher’s role in advancing computational intelligence and related disciplines. Continued scholarly activity is expected to further strengthen impact and visibility.[1][2]

References

  1. Elsevier (2026.). Scopus author details: Rami Ahmad El-Nabulsi, Author ID 26634034500. Scopus.
    https://www.scopus.com/pages/authors/55967162800
  2. Google Scholar (2026.). Rami Ahmad El-Nabulsi — author profile and publications.
    https://scholar.google.com/citations?hl=en&user=2LDk56EAAAAJ&view_op=list_works&sortby=pubdate
  3. ORCID (2026.). ORCID record: Rami Ahmad El-Nabulsi.
    https://orcid.org/0000-0001-5357-0208
  4. Fractional modeling for Raman distributed optical fiber temperature sensing: information-theoretic analysis, fractional field reconstruction, and high-resolution thermal Imaging.
    https://www.sciencedirect.com/science/article/abs/pii/S0030399226015847
  5. Global Scientist Day Awards (2026). Official award website.
    https://scientistday.org/

Marwan | AI Advancements | Excellence in Research

Published on by Scientist Day

Dr. Marwan | AI Advancements | Excellence in Research

Dr. Marwan | King Faisal University | Saudi Arabia

The applicant is an accomplished scholar in Computer Information Systems with specialized expertise in Artificial Intelligence and Data Science, supported by extensive experience in academia, research, and innovation. Over more than a decade of university-level teaching and research, the applicant has contributed significantly to advancing intelligent systems, machine learning applications, IoT security, biomedical imaging, and pattern recognition. Their doctoral work introduced a novel model for Arabic handwritten text recognition, forming the foundation for a strong research career in AI-driven language and image processing technologies. The applicant has authored and co-authored numerous impactful, refereed journal publications in well-recognized international outlets such as Sustainability, IJACSA, Traitement du Signal, and the Journal of Ayub Medical College. Research contributions span cancer therapy enhancement, anomaly detection, cephalometric landmark detection, multiple sclerosis classification, industrial IoT security, biometric iris recognition, palm disease classification, and Arabic word recognition. Several works have been indexed in Scopus and other reputable databases, with active collaborations involving interdisciplinary and multinational research teams. Beyond publications, the applicant has secured competitive research funding, including a grant supporting the development of a weighted-voting IoT security model targeting BASHLITE and Mirai cyberattacks. Ongoing research activities include hybrid deep learning systems for intrusion detection, medical image analysis, human nail disease diagnosis, music-brain interactions, and predicate-logic-based machine translation. The applicant has demonstrated strong academic service through extensive peer-reviewing, participation in scientific councils, and membership in research committees. Their professional development includes participation in conferences, training programs, and workshops focused on e-learning, scientific publishing, and advanced teaching strategies. Recognized for excellence, the applicant has received awards such as the Distinguished Scientific Research Award and the Outstanding International Publishing Award, reflecting sustained research quality and global scholarly impact. Their overall portfolio showcases a balanced blend of innovative research, academic leadership, and contributions to the AI and data science community.

Profiles: Scopus 

Featured Publications

Siddiqi, M. H., Alhwaiti, Y., Elaiwat, S., & Abu-Zanona, M. (2024). Dynamic healing process analysis: Image morphing with warping technique for nose and esophagus studies. The International Arab Journal of Information Technology, 21(3). (Accepted December 26, 2023).

 

Samia ZAOUI | AI Advancements | Women Researcher Award

Published on by Scientist Day

Mrs. Samia ZAOUI | AI Advancements | Women Researcher Award

Mrs. Samia ZAOUI | Mohammed VI Foundation of Health and Sciences | Morocco

Dr. Samia Zaoui, based in Rabat, Morocco, is a multidisciplinary researcher and project leader bridging artificial intelligence, aeronautics, and healthcare systems innovation. She is currently pursuing her Ph.D. in Computer Science Engineering (AI & Aeronautics) at the Higher Institute of Aeronautics and Space (ISAE-SUPAERO) and INP Toulouse, France. Her research focuses on the application of AI technologies for supply chain resilience, predictive modeling, and sustainable industrial systems, with a strong emphasis on pharmaceutical and healthcare logistics. Dr. Zaoui has an extensive background in strategic project development, digital transformation, and industrial management, having held leadership roles at the Mohammed VI Foundation of Health and Sciences and the Cheikh Zaid Foundation. She has spearheaded projects in sports medicine innovation, pharmaceutical manufacturing, and medical technology transfer, fostering collaborations with international organizations such as WHO, LCIF, and Smile Train. Her scientific contributions include several peer-reviewed publications in international journals, such as the Global Journal of Flexible Systems Management and Production Planning & Control, covering topics like AI-driven supply chain viability, sustainability in Industry 5.0, and pharmaceutical risk prediction using machine learning. Dr. Zaoui’s research integrates AI-based decision systems with aeronautical and industrial engineering principles, contributing to global efforts in intelligent, resilient, and sustainable supply networks. She also actively participates in international technology exhibitions and collaborative industrial initiatives across Europe, Asia, and Africa.

Profile: Google Scholar

Featured Publications

Zaoui, S., Foguem, C., Tchuente, D., Fosso-Wamba, S., & Kamsu-Foguem, B. (2023). The viability of supply chains with interpretable learning systems: The case of COVID-19 vaccine deliveries. Global Journal of Flexible Systems Management, 24(4), 633–657. https://doi.org/10.1007/s40171-023-00357-w

Zaoui, S., Foguem, C., Tchuente, D., & Kamsu-Foguem, B. (2025). The application of artificial intelligence technologies in the resilience and the viability of supply chains: A systematic literature review. Production Planning & Control, 1–18.

Zaoui, H., Zaoui, S., Kamsu-Foguem, B., & Tchuente, D. (2024). Sustainability: The main pillar of Industry 5.0. Oklahoma International Publishing (OkIP) Books. https://doi.org/10.55432/978-1-6692-0007-9_13

StEER – Structural Engineering Extreme Event Reconnaissance. (2024). Hualien City, Taiwan Earthquake: Preliminary Virtual Reconnaissance Report (PVRR). https://doi.org/10.17603/ds2-0d2z-9682