Yasir Ramzan | Mathematics | Editorial Board Member

Editorial Board Member

Yasir Ramzan
Shanghai University,China

Yasir Ramzan
Affiliation Shanghai University
Country China
Scopus ID 56199594500
Documents 13
Citations 82
h-index 6
Subject Area Mathematics
Event International Academic Excellence Awards
ORCID 0009-0007-1948-5465

Yasir Ramzan is a researcher affiliated with Shanghai University, China, whose listed scholarly work covers mathematical modelling, epidemic dynamics, nonlinear optimization, and computational methods. His publication record includes studies of infectious-disease transmission and intervention strategies, alongside research into physics-informed neural networks (PINNs). These topics connect mathematical theory with computational approaches to complex scientific problems. The profile information presented here reflects the supplied researcher metrics and publication details; bibliographic records and author attribution should be checked against the linked scholarly sources

Abstract

Yasir Ramzan’s supplied publication list highlights the use of mathematical models to investigate infectious-disease transmission, potential health consequences, and intervention strategies. His listed work also considers optimization approaches for PINNs, a class of machine-learning methods that incorporates mathematical and physical constraints. Together, these themes demonstrate how mathematical analysis and computational modelling can support the study of complex systems. His supplied Scopus metrics report 13 documents, 82 citations, and an h-index of 6. [1]

Keywords

Mathematical modelling; epidemic dynamics; nonlinear optimization; infectious-disease modelling; physics-informed neural networks; computational mathematics; intervention strategies.

Introduction

Mathematical modelling provides a structured way to represent changing systems, examine relationships among variables, and evaluate possible outcomes under defined assumptions. In epidemiology, models can help explore transmission pathways and compare potential control measures. In computational science, optimization techniques can improve how numerical models are trained or evaluated. The publications supplied for Ramzan reflect both areas of inquiry, although individual findings and methods should be interpreted through the original articles rather than inferred from titles alone. [2]

Research Profile

Ramzan is affiliated with Shanghai University and is associated in the supplied information with Mathematics. His listed research spans mathematical frameworks for disease dynamics, optimization, and data-driven computational modelling. These areas draw on differential equations, numerical analysis, and algorithmic methods to represent systems and investigate how their behaviour changes under different assumptions. His author identifier and ORCID provide routes for checking publication attribution and profile information. [1]

Research Contributions

The supplied article titles indicate several research directions:

  • Epidemic modelling: mathematical analysis of MERS-CoV and Lassa virus transmission, including intermediate-host dynamics and intervention strategies. [2] [3]
  • Optimization and PINNs: comparative analysis of modelling methods and variable-dependent weighting strategies for physics-informed neural networks. [4]
  • Transmission-associated health risks: models examining Lassa fever, disability risks, and a reported rabineurodeficiency syndrome. [5] [6]

These topics suggest an emphasis on mathematical frameworks for describing transmission and evaluating model-based interventions. Detailed claims about effectiveness or clinical implications require examination of each paper’s methods, assumptions, and results.

Publications

Selected works from the supplied publication information include:

  1. “Analysis of a Deterministic Model for MERS-CoV Transmission Involving an Intermediate Host and Pragmatic Control Interventions.” Iranian Journal of Science and Technology, Transactions of Electrical Engineering (2026). https://doi.org/10.1007/s40998-026-01208-x [2]
  2. “A systematic comparative analysis of modeling methods and variable-dependent weight optimization strategy for PINNs.” Chaos, Solitons & Fractals (2026). https://doi.org/10.1016/j.chaos.2026.118163 [4]
  3. “A mathematical framework for integrating epidemic dynamics and intervention strategies to mitigate hearing loss from lassa virus.” International Journal of Biomathematics (2026). https://doi.org/10.1142/S179352452550175X [3]
  4. “A nonlinear optimization framework for a Lassa fever model capturing zoogenic transmission and disability risks.” European Physical Journal Plus (2025). https://doi.org/10.1140/epjp/s13360-025-06902-z [5]
  5. “Decoding the transmission and subsequent disability risks of rabineurodeficiency syndrome without recuperation.” Scientific Reports (2025). https://doi.org/10.1038/s41598-025-01066-3 [6]

Research Impact

The supplied bibliometric snapshot records 13 documents, 82 citations, and an h-index of 6. These figures provide a limited quantitative view of publication and citation activity at the time the profile data were collected. Citation counts and h-index values may change as databases update, and differences in coverage can produce different results across platforms. They should therefore be read alongside the substance, reproducibility, and relevance of the research. [1]

Award Suitability

Ramzan’s listed work offers relevant material for consideration in an academic recognition context focused on Mathematics and interdisciplinary computational research. His supplied publications address modelling, optimization, and health-related applications. Any formal assessment for the International Academic Excellence Awards should rely on the award’s published criteria, verified authorship, documented research contributions, and independent evaluation. This profile records research information and does not itself imply a particular award decision or outcome.

Conclusion

Yasir Ramzan’s supplied academic profile presents research at the intersection of mathematical modelling, infectious-disease dynamics, and computational optimization. The selected publications illustrate applications of quantitative methods to scientific questions, while the provided bibliometric figures offer a snapshot of scholarly visibility. Readers can consult the linked author profiles and original articles for updated metrics, complete bibliographic information, and the evidence needed to assess individual contributions.

References

  1. Elsevier. (n.d.). Scopus author details: Yasir Ramzan, Author ID 56199594500. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56199594500
  2. “Analysis of a Deterministic Model for MERS-CoV Transmission Involving an Intermediate Host and Pragmatic Control Interventions.” (2026). Iranian Journal of Science and Technology, Transactions of Electrical Engineering.
    https://doi.org/10.1007/s40998-026-01208-x
  3. “A mathematical framework for integrating epidemic dynamics and intervention strategies to mitigate hearing loss from lassa virus.” (2026). International Journal of Biomathematics.
    https://doi.org/10.1142/S179352452550175X
  4. “A systematic comparative analysis of modeling methods and variable-dependent weight optimization strategy for PINNs.” (2026). Chaos, Solitons & Fractals.
    https://doi.org/10.1016/j.chaos.2026.118163
  5. “A nonlinear optimization framework for a Lassa fever model capturing zoogenic transmission and disability risks.” (2025). European Physical Journal Plus.
    https://doi.org/10.1140/epjp/s13360-025-06902-z
  6. “Decoding the transmission and subsequent disability risks of rabineurodeficiency syndrome without recuperation.” (2025). Scientific Reports.
    https://doi.org/10.1038/s41598-025-01066-3