Zi-an Fan | Mathematics | Best Paper Award

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Best Paper Award

Zi-an Fan
Affiliation Hubei Engineering University
Country China
Scopus ID 57201460000
Documents 7
Citations 15
h-index 3
Subject Area Mathematics
Research Paper Normalized solutions for Kirchhoff-Choquard equation with a local perturbation
Event   International Research Excellence and Best Paper Awards
ORCID 0000-0002-1632-6377

Zi-an Fan — Hubei Engineering University

Zi-an Fan is affiliated with Hubei Engineering University in China and is associated with research in Mathematics. The research paper titled “Normalized solutions for Kirchhoff-Choquard equation with a local perturbation” highlights a mathematical topic involving nonlinear equations and the study of normalized solutions. According to the supplied academic information, Fan has 7 Scopus-indexed documents, 15 citations, and an h-index of 3. This profile presents the researcher’s publication information and mathematical research interests in connection with the Best Paper Award. [1]

Abstract

This profile presents Zi-an Fan of Hubei Engineering University, China, in the field of Mathematics. The featured paper, “Normalized solutions for Kirchhoff-Choquard equation with a local perturbation,” concerns the mathematical analysis of a nonlinear equation involving Kirchhoff and Choquard terms with a local perturbation. The supplied Scopus metrics report 7 documents, 15 citations, and an h-index of 3. These indicators provide a quantitative overview of the researcher’s indexed scholarly output. Further details from the full paper are needed to describe its methods, principal theorems, and conclusions accurately. [1]

Keywords

Best Paper Award, Zi-an Fan, Mathematics, Hubei Engineering University, China, Nonlinear Analysis, Kirchhoff-Choquard Equation, Normalized Solutions, Local Perturbation, Nonlinear Partial Differential Equations, Mathematical Research, Variational Methods, Mathematical Modelling, Scholarly Publications, Research Excellence, Citation Analysis, h-index, Academic Recognition, Research Impact, Global Automobile Award. [1]

Introduction

Mathematics provides theoretical frameworks for understanding complex systems, equations, and quantitative relationships. Nonlinear analysis, in particular, investigates equations whose behaviour cannot be fully described by linear models. Zi-an Fan’s featured paper addresses a Kirchhoff-Choquard equation with a local perturbation, placing the work within the broader study of nonlinear mathematical equations. The researcher’s affiliation and supplied bibliometric information provide the basis for this academic profile. [1]

Research Profile

Zi-an Fan is affiliated with Hubei Engineering University in China and is listed under Mathematics for this profile. The supplied academic record includes 7 documents, 15 citations, and an h-index of 3. Fan’s featured paper focuses on normalized solutions for a Kirchhoff-Choquard equation under a local perturbation. These details identify the general mathematical subject of the work, while a comprehensive account of the researcher’s broader interests would require further verified publication information. [1]

Research Contributions

The featured paper examines normalized solutions associated with a Kirchhoff-Choquard equation containing a local perturbation. Kirchhoff-type equations and Choquard-type equations arise in nonlinear mathematical analysis and involve distinct structural features. The term “normalized solutions” indicates that the solution is considered under a specified constraint. The precise mathematical assumptions, proof techniques, existence results, and conclusions should be described from the full publication to ensure that the research contribution is represented accurately.

Publication Record

The supplied Scopus information lists 7 documents associated with Zi-an Fan, together with 15 citations and an h-index of 3. The featured publication is titled “Normalized solutions for Kirchhoff-Choquard equation with a local perturbation.” These metrics provide a snapshot of the indexed scholarly record at the time the information was supplied. The complete publication details, including co-authors, journal or conference, publication year, and DOI, should be confirmed through the relevant bibliographic record before being added to this page. [1]

Research Impact

Research impact in Mathematics can be assessed through the development of mathematical theory, the use of rigorous analytical methods, citations, and the relevance of results to subsequent studies. The supplied metrics indicate that Zi-an Fan’s indexed publications have received 15 citations and that the reported h-index is 3. These figures offer limited quantitative context and should be interpreted alongside the substance and significance of individual publications. A fuller assessment would require examining the featured paper and related research.

Award Recognition

This profile presents Zi-an Fan and the paper “Normalized solutions for Kirchhoff-Choquard equation with a local perturbation” in connection with the Best Paper Award and the Global Automobile Award event named in the supplied information. The listed award website is Best Paper Awards. An official announcement or award record should be consulted to confirm the award category, selection outcome, and event affiliation before describing the researcher as a confirmed award winner. [2]

Conclusion

Zi-an Fan of Hubei Engineering University, China, is profiled in the field of Mathematics through the supplied academic information and the paper on normalized solutions for a Kirchhoff-Choquard equation with a local perturbation. The reported research record includes 7 documents, 15 citations, and an h-index of 3. These details establish a concise overview of the researcher’s publication profile. Verified bibliographic information and official award documentation would strengthen the account of the paper’s contribution and any associated recognition.

External Links

References

  1. Scopus. (n.d.). Scopus Author Profile: Zi-an Fan.
    https://www.scopus.com/authid/detail.uri?authorId=57201460000
  2. Best Paper Awards. (n.d.). Official website.
    https://bestpaperawards.com/

Jaydeep Pandya | Mathematics | Best Researcher Award

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Dr. Jaydeep Pandya | Mathematics | Best Researcher Award 

PhD | Maharaja Krishnakumarsinhji Bhavnagar University | India

 

Dr. Jaydeep A. Pandya is a dedicated mathematician and emerging research talent whose strong academic foundation and focused expertise make him a highly suitable candidate for a Best Researcher Award in Mathematics, particularly in the domains of Operations Research and Transportation Modelling. A gold medalist in M.Sc. Mathematics from M.K. Bhavnagar University and a Ph.D. scholar specializing in refinements to transportation models, he demonstrates consistent academic rigor and research excellence. His research portfolio includes four published papers in reputed Scopus-, ABDC-, and peer-reviewed journals, addressing probabilistic frameworks, transportation barriers, atmospheric and external cost factors, and optimization methods in logistics systems. Dr. Pandya has presented more than twelve research papers across prestigious national and international conferences at institutions including Kurukshetra University, JECRC University, Thapar Institute of Engineering & Technology, VIT Tamil Nadu, Gauhati University, and Bharatiya Vidya Bhavan, reflecting strong scholarly engagement and subject command. He has also contributed to academic literature through a conference proceedings publication in the field of sustainable development. Beyond research, he is actively involved in academic governance as a member of IQAC, Board of Studies, and Anti-Ragging Committee, demonstrating leadership and institutional commitment. His continuous learning mindset is evident through multiple NPTEL/SWAYAM certifications from leading Indian institutions such as IITs and central universities in fields like operations research, statistics, real analysis, and academic writing. With technical proficiency in LaTeX, MS Excel, data handling, and mathematical modelling tools, he brings both analytical and computational strengths. Recognized early with the Prof. A.R. Rao Gujarat Ganit Mandal encouragement award, Dr. Pandya’s career objective aligns with innovative, impactful academic research and student development. His strong publication record, scholarly presentations, interdisciplinary orientation, and commitment to advancing mathematical solutions for real-world transportation systems collectively position him as a deserving and promising candidate for the Best Researcher Award.

Profiles: ORCID | ResearchGate

Featured Publications

Pandya, J. A. (2024). A study of uncertainty and probability in transportation problem. Utilitas Mathematica, 121, 1–10.

Pandya, J. A. (2025). A probabilistic framework for evaluating efficiency gains in Vogel’s approximation method. Journal of Informatics Education and Research, 5, 1–12.

Pandya, J. A. (2023). Impact of atmospheric barriers on transportation efficiency. International Journal of Interdisciplinary Organizational Studies, 18, 15–25.

Pandya, J. A. (2023). Analytical study on external transportation cost in linear programming problems. International Journal of Innovative Research & Growth, 12, 32–40.

Pandya, J. A. (2024). One Day National Conference on Green Energy and Sustainable Development. Conference Proceedings, Department of Physics, Shri R. R. Lalan College, Bhuj, 78–85. (ISBN 978-81-931638-9-4)

 

Dr. Jaydeep A. Pandya’s research advances the efficiency and intelligence of transportation and logistics systems through innovative mathematical modelling and optimization techniques. His work bridges theoretical mathematics with real-world applications, improving decision-making in infrastructure planning, urban mobility, and resource optimization. By addressing uncertainty and dynamic barriers in transportation networks, his contributions support smarter cities, sustainable development, and data-driven industrial innovation.

 

Sushant Yadav | Mathematical Modeling | Best Researcher Award

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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.