Nasrin Samadyar | Numerical Analysis | Best Researcher Award

Best Researcher Award

Nasrin Samadyar – Kermanshah University of Technology, Iran

Nasrin Samadyar
Affiliation Kermanshah University of Technology
Country Iran
Scopus ID 57190257270
Documents 44
Citations 1,676
h-index 30
Subject Area Numerical Analysis
Event Global Network Awards
ORCID 0000-0001-8556-8508

Nasrin Samadyar is a researcher affiliated with Kermanshah University of Technology, Iran, and her publications address numerical algorithms for differential and integral equations, combining approximation theory, meshfree techniques, and computational analysis to investigate problems arising across applied mathematics and engineering.

Abstract

Nasrin Samadyar’s research examines numerical methods for stochastic, fractional, and nonlinear differential and integral equations. Her published work explores radial basis functions, meshfree approximation, finite difference schemes, operational matrices, and orthogonal polynomial techniques. These approaches convert complex mathematical models into tractable algebraic systems and support computational investigation of solutions, stability, convergence, and error behavior. Applications include stochastic advection–diffusion processes, Fredholm integral equations, and time-fractional wave models. Her publication record reflects sustained engagement with computational mathematics and numerical analysis, particularly methods designed for multidimensional problems, irregular domains, and models involving uncertainty or fractional-order dynamics in applied scientific settings and reproducibility assessment. [1]

Keywords

Numerical Analysis, Fractional Differential Equations, Stochastic Differential Equations, Meshfree Methods, Radial Basis Functions, Finite Difference Methods, Stochastic Integral Equations, Fredholm Integral Equations, Orthogonal Polynomials, Computational Mathematics, Fractional Stochastic Advection–Diffusion, Sine–Gordon Equations, Operational Matrices, Numerical Approximation, Mathematical Modelling. [4]

Introduction

Nasrin Samadyar’s publications contribute to computational approaches for mathematical problems that are challenging analytically. Her research addresses fractional differential equations, stochastic integral equations, and nonlinear models through numerical approximation. The work combines formulation with implementation, emphasizing accuracy, convergence, and treatment of domains in applied mathematics and engineering research and related disciplines scholarship. [2]

Research Profile

Nasrin Samadyar is affiliated with Kermanshah University of Technology in Iran and is identified in databases through Scopus and ORCID records. Her research areas include numerical analysis, applied mathematics, stochastic processes, and computational modelling. Publication topics feature fractional equations, meshfree methods, radial basis functions, and polynomial-based numerical techniques across journals. [1]

Research Contributions

Nasrin Samadyar’s research contributions include numerical schemes for fractional stochastic advection–diffusion equations, stochastic Fredholm integral equations, and time-fractional Sine–Gordon models. Her co-authored studies combine finite difference discretization with radial basis function approximations, while other work develops operational matrices and orthogonal polynomial methods for integral and integro-differential equations and convergence analysis.

Publications

Nasrin Samadyar’s publication record includes studies on stochastic integral equations, fractional differential models, and meshfree computational methods. Representative articles examine two-dimensional Fredholm equations, fractional stochastic advection–diffusion, and Sine–Gordon equations. The publications demonstrate recurring use of radial basis functions, finite difference schemes, and polynomial approximation in numerical analysis across several years. [3] [4] [5]

Research Impact

Nasrin Samadyar’s research supports computational mathematics by presenting numerical strategies for equations with stochastic, fractional, or multidimensional characteristics. The cited literature situates this work within numerical analysis and mathematical modelling. Potential scientific and engineering applications include transport phenomena, wave propagation, and other complex systems represented through differential or integral equations. [4]

Award Suitability

Nasrin Samadyar’s research output aligns with recognition in numerical analysis through its focus on computational methods for fractional and stochastic equations. Publication themes demonstrate methodological contributions, collaborative scholarship, and applications to mathematical modelling. A balanced award assessment should carefully consider verified publications, citation indicators, research quality, and documented originality and influence where appropriate. [1]

Conclusion

Nasrin Samadyar’s profile reflects continuing work in numerical analysis, stochastic modelling, and computational methods for fractional equations. Her publications describe approaches combining approximation techniques with numerical discretization to study challenging mathematical systems. The profile provides a basis for evaluating contributions through independently verifiable scholarly records and supporting evidence for reviewers.[3] [4]

References

  1. Elsevier. (n.d.). Scopus author details: Nasrin Samadyar, Author ID 57190257270. Scopus.https://www.scopus.com/authid/detail.uri?authorId=57190257270
  2. ORCID. (n.d.). Nasrin Samadyar: ORCID researcher record.https://orcid.org/0000-0001-8556-8508
  3. Samadyar, N., & Mirzaee, F. (2020). Numerical solution of two-dimensional stochastic Fredholm integral equations on hypercube domains via meshfree approach. Journal of Computational and Applied Mathematics, 377, 112875.https://doi.org/10.1016/j.cam.2020.112875
  4. Mirzaee, F., & Samadyar, N. (2020). Combination of finite difference method and meshless method based on radial basis functions to solve fractional stochastic advection–diffusion equations. Engineering with Computers, 36, 1673–1686.https://doi.org/10.1007/s00366-019-00789-y
  5. Mirzaee, F., Rezaei, S., & Samadyar, N. (2021). Numerical solution of two-dimensional stochastic time-fractional Sine–Gordon equation on non-rectangular domains using finite difference and meshfree methods. Engineering Analysis with Boundary Elements, 127, 53–63.https://doi.org/10.1016/j.enganabound.2021.03.009

Prof Dr. Zhenyu Zhao | Computational Mathematics | Best Researcher Award

Prof Dr. Zhenyu Zhao | Computational Mathematics | Best Researcher Award

Prof Dr. Zhenyu Zhao, Shandong University of Technology, China

Prof. Dr. Zhenyu Zhao is a distinguished professor at Shandong University of Technology in Zibo, China, since October 2019, following a notable academic tenure at Guangdong Ocean University, where he served as a professor and associate professor from 2008 to 2019. He completed his postdoctoral research at Fudan University (2010-2012) and earned his Doctor of Science degree at Shanghai University (2004-2008), along with a Master of Science from Hebei University of Technology (2001-2004). A dedicated researcher, Prof. Zhao has led significant projects, including a National Natural Science Foundation of China initiative and an innovation project in Guangdong, securing substantial funding for both. His commitment to mathematics and statistics not only advances scholarly research but also inspires the next generation of students in his field.

Professional Profile

Scopus

Suitability for the Best Researcher Award:

Prof. Zhenyu Zhao’s long-standing contributions to the field of applied mathematics, his successful leadership in significant national research projects, and his impactful publications make him a strong candidate for the Best Researcher Award. His work on numerical differentiation and inverse problems, along with his innovative application of regularization methods, highlights his role as a leader in advancing computational mathematics. His ability to secure research funding and his influence in mathematical research through highly cited publications further underscore his importance in the academic community.

Academic Background:

Prof. Dr. Zhenyu Zhao is a distinguished professor at Shandong University of Technology in Zibo, China, since October 2019. He previously served at Guangdong Ocean University in Zhanjiang, China, where he held professorship roles from December 2015 to September 2019 and served as an associate professor from October 2008 to November 2015. He completed his postdoctoral research at Fudan University in Shanghai (2010-2012) and earned his Doctor of Science degree at Shanghai University (2004-2008). Additionally, he holds a Master of Science degree from Hebei University of Technology (2001-2004).

Research Contributions:

Prof. Zhao has actively contributed to the field through several significant research projects, including a National Natural Science Foundation of China project (2013-2015) with total funding of 220,000 RMB and an innovation project in Guangdong (2018-2022) that received 600,000 RMB in funding.

Impact and Legacy:

With a strong commitment to mathematics and statistics, Prof. Zhao continues to inspire students and advance research in his field, showcasing excellence in both education and scholarly contributions. 🌟

Publication Top Notes:

  • Title: Numerical differentiation for two-dimensional scattered data on arbitrary domain based on Hermite extension with an implicit iteration process
    • Publication Year: 2022
    • Citations: 1
  • Title: A numerical differentiation method based on Legendre expansion with super order Tikhonov regularization
    • Publication Year: 2021
    • Citations: 2
  • Title: A Hermite extension method for numerical differentiation
    • Publication Year: 2021
    • Citations: 5
  • Title: Identifying an Unknown Source in the Poisson Equation with a Super Order Regularization Method
    • Publication Year: 2020
    • Citations: 3
  • Title: Numerical differentiation for two-dimensional functions by a Fourier extension method
    • Publication Year: 2020
    • Citations: 8