Best Researcher Award

Zulqurnain Sabir
Lebanese American University, Lebanon

Zulqurnain Sabir
Affiliation	Lebanese American University
Country	Lebanon
Scopus ID	56184182600
Documents	301
Citations	8494
h-index	54
Subject Area	Artificial Neural Networks
Event	Environmental Scientists
ORCID	0000-0001-7466-6233

Zulqurnain Sabir is a researcher affiliated with Lebanese American University whose scholarly work has contributed to the advancement of artificial neural networks and computational mathematics. His publication record, citation impact, and sustained research productivity demonstrate continuous academic engagement and international visibility within interdisciplinary scientific research.[1]

Abstract

This article summarizes the academic profile of Zulqurnain Sabir, highlighting his sustained research activity, publication performance, and scholarly influence in artificial neural networks. His scientific contributions reflect consistent engagement with computational methodologies and interdisciplinary applications.[1]

Keywords

Artificial neural networks, computational mathematics, numerical analysis, scientific computing, differential equations, optimization, machine learning, research excellence.

Introduction

Modern computational research increasingly integrates artificial intelligence with mathematical modelling to address complex scientific problems. Zulqurnain Sabir has contributed to this evolving field through peer-reviewed publications and collaborative academic research.[2]

Research Profile

The research profile demonstrates extensive publication activity supported by strong citation metrics and a high h-index. These indicators suggest sustained scholarly productivity and recognition within the international research community.[1]

Research Contributions

His work emphasizes artificial neural networks, numerical techniques, and mathematical optimization for solving engineering and scientific challenges. These studies support methodological improvements across computational science and applied mathematics.[3]

Publications

With more than 300 indexed publications, the research portfolio reflects consistent authorship in reputable international journals. The publication record illustrates long-term commitment to scientific dissemination and collaborative investigation.[1]

Research Impact

Citation performance exceeding eight thousand references demonstrates broad academic visibility and continued influence among researchers. Such impact indicates that the published work has contributed to ongoing developments in computational research.[4]

Award Suitability

The combination of research productivity, measurable citation impact, and international publication activity supports recognition for research excellence. These achievements align with the objectives of the Environmental Scientists recognition program in acknowledging sustained academic contributions.[5]

Conclusion

Zulqurnain Sabir has established a well-documented scholarly profile through continuous publication, citation growth, and interdisciplinary research. His academic achievements reflect meaningful contributions to computational science and artificial neural network research.[1]

External Links

• ORCID Profile
• Scopus Author Profile
• Google Scholar Profile

References

1. Elsevier. (n.d.). Scopus author details: Zulqurnain Sabir, Author ID 56184182600. Scopus.
   https://www.scopus.com/authid/detail.uri?authorId=56184182600
2. ORCID. (n.d.). Zulqurnain Sabir ORCID record.
   https://orcid.org/0000-0001-7466-6233
3. Sabir, Z., Muhammad, N., Zhang, S., & Khan, I. (2026). Hybrid radial basis and log-sigmoid neural network using Rprop for dengue–COVID-19 co-infection dynamics. SSRN Electronic Journal (Preprint).
   https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6910764
4. Sabir, Z., Kobba, T., & Fadel, H. (2026). A computational design-based scale conjugate neural network to solve the nonlinear Rabinovich–Fabrikant model. Journal of Circuits, Systems and Computers. Advance online publication
   https://www.worldscientific.com/doi/10.1142/S0218126626501203
5. Sabir, Z., Bichbich, I., Umar, M., Salahshour, S., & Bayram, M. (2026). An artificial neural network based on radial basis methodology using delay effects in the Parkinson’s disease model. Computational Biology and Chemistry, 115, Article 109033.