Natiq Akhmedov | Mathematics | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

NATIQ AKHMEDOV
Affiliation Azerbaijan State Economic University
Country Azerbaijan
Scopus ID 24392187600
Documents 29
Citations 139
h-index 7
Subject Area Mathematics
Event International Research Excellence and Best Paper Awards
ORCID 0000-0002-3071-2549

NATIQ AKHMEDOV

NATIQ AKHMEDOV of Azerbaijan State Economic University, Azerbaijan is recognized with the Best Paper Award for research excellence in the field of Mathematics. The recognized research, titled “Analysis of the three-dimensional elasticity theory problem for a radially inhomogeneous cylinder,” addresses a mathematical problem within three-dimensional elasticity theory involving a cylinder with radially varying material properties.

Abstract

This article recognizes NATIQ AKHMEDOV with the Best Paper Award for research excellence in Mathematics. The recognized research, titled “Analysis of the three-dimensional elasticity theory problem for a radially inhomogeneous cylinder,” focuses on the analysis of a three-dimensional elasticity theory problem associated with a cylinder whose material characteristics vary in the radial direction. The study represents a contribution to mathematical and theoretical approaches for understanding elasticity problems involving inhomogeneous cylindrical structures.

Keywords

Three-Dimensional Elasticity Theory, Mathematics, Radially Inhomogeneous Cylinder, Elasticity Problems, Mathematical Analysis, Inhomogeneous Materials, Cylindrical Structures, Continuum Mechanics, Elasticity Modeling, Mathematical Modeling.

Introduction

The awarded research, “Analysis of the three-dimensional elasticity theory problem for a radially inhomogeneous cylinder,” examines an important mathematical problem in the field of elasticity theory. Three-dimensional elasticity provides mathematical frameworks for describing the deformation and mechanical behavior of solid bodies, while radial inhomogeneity introduces additional complexity because material properties can change according to the radial coordinate

Research Profile

NATIQ AKHMEDOV is affiliated with Azerbaijan State Economic University, Azerbaijan and is associated with the subject area of Mathematics. According to the provided academic information, the researcher has 29 documents, 139 citations, and an h-index of 7. The Scopus Author ID is 24392187600, and the researcher’s ORCID identifier is 0000-0002-3071-2549.

Research Contributions

The recognized publication contributes to Mathematics through the analysis of a three-dimensional elasticity theory problem for a radially inhomogeneous cylinder. The research addresses the mathematical complexity associated with cylindrical bodies whose properties vary with radial position and contributes to the broader study of elasticity problems involving non-uniform material distributions.

Research Impact

The provided academic profile records 29 documents, 139 citations, and an h-index of 7 for NATIQ AKHMEDOV. These indicators reflect a sustained body of indexed research and citation activity within the researcher’s academic profile.

Award Suitability

The Best Paper Award recognizes research demonstrating academic quality, originality, scientific relevance, and meaningful contribution to its respective discipline. NATIQ AKHMEDOV’s recognized research aligns with these objectives through its analysis of a three-dimensional elasticity theory problem for a radially inhomogeneous cylinder within the field of Mathematics.

Conclusion

NATIQ AKHMEDOV has contributed to the field of Mathematics through research focused on three-dimensional elasticity theory and radially inhomogeneous cylindrical structures. The recognized publication, “Analysis of the three-dimensional elasticity theory problem for a radially inhomogeneous cylinder,” addresses a specialized mathematical problem involving spatially varying properties and provides a theoretical contribution to the analysis of elasticity in cylindrical systems.

External Links

References

  1. Scopus Author Profile: NATIQ AKHMEDOV, Author ID 24392187600. Scopus. https://www.scopus.com/pages/authors/24392187600
  2. ORCID Research Profile: NATIQ AKHMEDOV. ORCID. https://orcid.org/0000-0002-3071-2549
  3. Best Paper Awards. https://bestpaperawards.com/

Kangkan Choudhury | Mathematics | Best Paper Award

Published on by Best Paper Awards

Best Paper Award

Kangkan Choudhury
Affiliation University of Science and Technology Meghalaya
Country India
Scopus ID 57204730807
Documents 13
Citations 68
h-index 4
Subject Area Mathematics
Event International Research Excellence and Best Paper Awards
ORCID 0000-0003-2809-8428

Kangkan Choudhury

Kangkan Choudhury of the University of Science and Technology Meghalaya, India is recognized with the Best Paper Award for research excellence in the field of Mathematics. The recognized research, titled “MHD free convective heat and mass transfer flow passing through semi-infinite plate for Cu-water and TiO2-water nanofluids in presence of radiation embedded in porous medium,” investigates magnetohydrodynamic free-convective heat and mass transfer involving nanofluids, radiation effects, and porous media.

Abstract

This article recognizes Kangkan Choudhury for the Best Paper Award in recognition of research excellence in mathematics. The recognized paper, titled “MHD free convective heat and mass transfer flow passing through semi-infinite plate for Cu-water and TiO2-water nanofluids in presence of radiation embedded in porous medium,” focuses on mathematical modeling of magnetohydrodynamic free convection and heat and mass transfer in nanofluid flows. The study considers Cu-water and TiO2-water nanofluids, radiation effects, and porous-medium conditions, addressing important mathematical and transport-phenomena aspects of advanced fluid-flow systems.

Keywords

MHD Flow, Magnetohydrodynamics, Free Convection, Heat Transfer, Mass Transfer, Nanofluids, Cu-Water Nanofluid, TiO2-Water Nanofluid, Radiation, Porous Medium, Semi-Infinite Plate, Mathematical Modeling, Fluid Mechanics, Thermal Engineering, Mathematics.

Introduction

The recognized paper examines the mathematical behavior of magnetohydrodynamic free-convective heat and mass transfer through a semi-infinite plate under conditions involving nanofluids, radiation, and a porous medium. Magnetohydrodynamic flow combines fluid motion with magnetic-field effects, while nanofluids provide a framework for studying enhanced thermal transport through suspended nanoparticles.

Research Profile

Kangkan Choudhury is affiliated with the University of Science and Technology Meghalaya, India, and is associated with the subject area of Mathematics. The provided academic information records 13 documents, 68 citations, and an h-index of 4. The researcher’s Scopus Author ID is 57204730807, while the ORCID identifier is 0000-0003-2809-8428.

Research Contributions

The research contributes to the mathematical study of coupled heat and mass transfer phenomena by integrating several physical effects into a unified flow model. The consideration of magnetic-field effects, free convection, nanofluids, radiation, and porous-medium characteristics provides a multidimensional framework for analyzing complex transport behavior.

Research Impact

The provided academic profile records 13 documents, 68 citations, and an h-index of 4 for Kangkan Choudhury. These indicators provide a quantitative view of the researcher’s indexed scholarly output and citation activity.

The recognized research has relevance to mathematical modeling and applied transport phenomena. Its focus on nanofluid heat transfer, magnetohydrodynamics, radiation, and porous media connects mathematical analysis with areas of fluid mechanics, thermal systems, energy transport, and engineering applications.

Award Suitability

The Best Paper Award recognizes research demonstrating academic quality, originality, relevance, and meaningful contribution to its respective discipline. Kangkan Choudhury’s recognized research aligns with these objectives through its mathematical investigation of MHD free convection, heat and mass transfer, nanofluids, radiation, and porous-medium effects.

Conclusion

Kangkan Choudhury represents a research contribution in the field of Mathematics, particularly in mathematical modeling of fluid flow and coupled heat and mass transfer. The recognized paper, “MHD free convective heat and mass transfer flow passing through semi-infinite plate for Cu-water and TiO2-water nanofluids in presence of radiation embedded in porous medium,” brings together magnetohydrodynamic effects, nanofluid transport, radiation, and porous-medium characteristics within a mathematical framework.

External Links

References

  1. Scopus Author Profile: Kangkan Choudhury, Author ID 57204730807.
    Scopus.Scopus Author Profile
  2. ORCID Research Profile: Kangkan Choudhury.
    ORCID.ORCID Research Profile
  3. Best Paper Awards.
    Best Paper Awards

Sushant Yadav | Mathematical Modeling | Best Researcher Award

Published on by Best Paper Awards

Mr. Sushant Yadav | Mathematical Modeling | Best Researcher Award

Senior Research Fellow at Malaviya National Institute of Technology Jaipur, India

Mr. Sushant Yadav is a Ph.D. scholar in Mathematics at MNIT Jaipur, with a strong academic foundation from MNNIT Allahabad and the University of Delhi. His research revolves around Spiking Neural Networks, biologically inspired neural models, and their applications in AI and healthcare. With a passion for mathematical innovation in artificial intelligence, Sushant has contributed to notable publications in reputed journals and conferences. He possesses comprehensive skills in scientific computing, programming, and data analysis, making him a versatile researcher in the evolving field of computational mathematics and AI.

Publication Profile

Orcid

Google Scholar

Educational Details

  • Doctor of Philosophy in Mathematics (2021 – Present)
    Malaviya National Institute of Technology (MNIT), Jaipur, India
    CGPA: 8.67/10.00
  • Master of Science in Mathematics and Scientific Computing (2018 – 2020)
    Motilal Nehru National Institute of Technology (MNNIT), Allahabad, India
    CGPA: 7.05/10.00
  • Bachelor of Science (Hons.) in Mathematics (2015 – 2018)
    University of Delhi (DU), India
    CGPA: 6.7/10.00

Professional Experience

Mr. Sushant Yadav is a dedicated researcher and academic in the field of Applied Mathematics and Artificial Intelligence. He is currently pursuing his Ph.D. in Mathematics at MNIT Jaipur, where his research focuses on the intersection of Spiking Neural Networks (SNN) and biologically inspired computational models. Throughout his doctoral studies, he has actively contributed to cutting-edge research involving neuron models, plasticity mechanisms, and machine learning applications in healthcare and biological systems. His work involves developing new mathematical models and computational techniques to enhance AI systems’ performance and adaptability. With strong programming skills in Python, C/C++, and expertise in frameworks such as PyTorch, TensorFlow, and SnnTorch, he aims to bridge the gap between theoretical mathematics and AI applications.

Research Interest

  • Spiking Neural Networks (SNN)
  • Neuromorphic Computing
  • Artificial Intelligence and Machine Learning
  • Biologically Inspired Computation
  • Mathematical Modeling in Computational Neuroscience
  • Application of Machine Learning in Healthcare

Top Noted Publication

1. Comparative Analysis of Biological Spiking Neuron Models for Classification Task

  • Authors: S. Yadav, S. Chaudhary, R. Kumar
  • Conference: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
  • Publisher: IEEE
  • Pages: 1-6
  • Date: July 2023
  • DOI: https://doi.org/10.1109/ICCCNT57981.2023.10245626
  • Summary:
    This paper presents a comparative evaluation of various biological spiking neuron models with respect to their effectiveness in solving classification tasks. It focuses on models such as Leaky Integrate-and-Fire (LIF), Izhikevich, and Hodgkin-Huxley neurons, assessing their performance on benchmark datasets. The study provides insight into the suitability of each model for machine learning applications based on accuracy and computational efficiency.

2. Consciousness Driven Spike Timing Dependent Plasticity

  • Authors: S. Yadav, S. Chaudhary, R. Kumar
  • Journal: Expert Systems with Applications (Elsevier)
  • DOI: https://doi.org/10.1016/j.eswa.2025.126490
  • Preprint: arXiv preprint arXiv:2405.04546
  • Publication Year: 2024
  • Summary:
    This paper introduces a novel approach integrating consciousness-like behavior into the Spike Timing Dependent Plasticity (STDP) learning rule. The proposed mechanism enhances synaptic adaptability by incorporating contextual and attention-based weight adjustments, leading to improved learning outcomes in spiking neural networks (SNNs). The study demonstrates the effectiveness of this approach in enhancing performance in classification and pattern recognition tasks.

3. Machine Learning-Based Recognition of White Blood Cells in Juvenile Visayan Warty Pigs

  • Authors: S. Saxena, S. Yadav, B. Singh, R. Kumar, S. Chaudhary
  • Conference: 2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI)
  • Publisher: IEEE
  • Date: December 2023
  • Summary:
    This research proposes a machine learning framework for the automated recognition and classification of White Blood Cells (WBCs) in juvenile Visayan Warty Pigs, a rare and endangered species. The system employs image processing and supervised learning algorithms to enhance diagnostic accuracy and aid veterinarians in wildlife health monitoring.

4. Deep Learning Solutions for WBC Classification in Juvenile Visayan Warty Pigs

  • Authors: S. Saxena, S. Yadav, B. Singh, R. Kumar, S. Chaudhary
  • Conference: 2023 IEEE Engineering Informatics
  • Publisher: IEEE
  • Pages: 1-6
  • Date: November 2023
  • Summary:
    This paper presents a deep learning-based approach leveraging Convolutional Neural Networks (CNNs) to classify White Blood Cells in juvenile Visayan Warty Pigs. The study demonstrates improved classification accuracy compared to traditional image processing techniques, showcasing the potential of deep learning in veterinary diagnostics and wildlife conservation.

Conclusion:

Mr. Sushant Yadav is a highly promising researcher with a robust foundation in mathematical modeling, spiking neural networks, and biologically inspired AI. His research contributions, particularly his innovative work on STDP and white blood cell classification using machine learning, position him as a deserving candidate for the Best Researcher Award. While his profile is strong, further enhancing his publication impact, international collaborations, and real-world implementations would elevate his standing in the global research community.