Muhammad Riaz | Mathematics | Innovative Research Award

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Innovative Research Award

Muhammad Riaz

Central South University

Muhammad Riaz
Affiliation Central South University
Country Pakistan
Scopus ID 57611620500
Documents 192
Citations 5,056
h-index 39
Subject Area Mathematics
Event International Phenomenological Research Awards
ORCID 0000-0001-8115-9168

Muhammad Riaz is a Pakistani mathematics educator and researcher whose scholarly work focuses on pure mathematics, fuzzy algebra, aggregation operators, computational mathematics, and multi-criteria decision-making methodologies. His research has contributed to the development of advanced fuzzy frameworks including Fermatean fuzzy sets, cubic fuzzy sets, and Q-rung orthopair fuzzy models for addressing complex decision sciences applications.[1] Through a combination of academic research, mathematical modelling, and educational practice, he has developed a professional profile that bridges theoretical mathematics and practical decision-support systems.[2]

Abstract

This article presents an academic overview of Muhammad Riaz, highlighting his educational background, teaching experience, research achievements, and contributions to fuzzy mathematics and decision sciences. His work emphasizes the development of aggregation operators and fuzzy decision-making frameworks applicable to uncertainty modelling, computational intelligence, and multi-criteria decision-making problems. The profile also evaluates the relevance of his research record in the context of academic recognition and international research awards.[1]

Keywords

Pure Mathematics; Fuzzy Algebra; Fermatean Fuzzy Sets; Q-rung Orthopair Fuzzy Sets; Cubic Fuzzy Sets; Aggregation Operators; Multi-Criteria Decision Making (MCDM); Computational Mathematics; Decision Sciences; Mathematical Modelling.

Introduction

Muhammad Riaz has developed an academic career combining mathematics education and research. His interests lie in pure mathematics and fuzzy systems, with particular emphasis on modelling uncertainty in decision environments. He has contributed to theoretical and applied mathematical studies involving aggregation operators, fuzzy soft sets, intuitionistic fuzzy structures, and decision-support methodologies.[1]

Alongside his research activities, he has served as a high school mathematics teacher since 2017, providing instruction at secondary and higher secondary levels while mentoring students and participating in academic development activities. His educational philosophy integrates mathematical rigor with practical problem-solving skills.[2]

Research Profile

Riaz completed an MPhil in Pure Mathematics at Abdul Wali Khan University, Mardan, where his thesis focused on Fermatean Cubic Fuzzy Aggregation Operators and their applications in decision-making problems. The research proposed advanced aggregation methodologies and explored their extension toward Q-rung Orthopair Cubic Fuzzy frameworks for multi-criteria decision-making systems.[3]

  • Research specialization in fuzzy algebra and decision sciences.
  • Focus on aggregation operators under uncertainty.
  • Interest in computational mathematics and numerical methods.
  • Application of fuzzy systems in real-world decision environments.
  • Development of mathematical models for MCDM problems.

Research Contributions

The research contributions of Muhammad Riaz primarily involve the advancement of fuzzy decision-making methodologies. His published work explores circular intuitionistic fuzzy systems, picture fuzzy soft operators, neutrosophic decision models, and integrated decision-support frameworks applicable to transportation, healthcare, education, security screening, and information retrieval systems.[4]

  • Development of Fermatean fuzzy aggregation operators.
  • Research on circular intuitionistic fuzzy decision models.
  • Applications of fuzzy systems in healthcare decision analysis.
  • Optimization frameworks for transportation and routing problems.
  • Integration of advanced aggregation techniques into MCDM methodologies.

Publications

Muhammad Riaz’s notable publications include studies on airport security decision systems and neutrosophic group decision-making for wave energy plant location, published in Information Sciences and CAAI Transactions on Intelligence Technology, respectively.[4][5]

Selected recent publications demonstrate the breadth of Riaz’s research activity across fuzzy systems, computational intelligence, and decision sciences.[4]

Research Impact

The bibliometric indicators associated with Muhammad Riaz reflect a substantial research presence within mathematics and decision sciences. His Scopus profile reports 192 indexed documents, more than 5,000 citations, and an h-index of 39, indicating sustained scholarly influence across interdisciplinary domains involving fuzzy mathematics, optimization, and computational intelligence.[1]

His research outputs have been published in internationally recognized journals including Information Sciences, Applied Soft Computing, Scientific Reports, International Journal of Fuzzy Systems, and Measurement, contributing to the advancement of uncertainty modelling and intelligent decision-support systems.[4]

Award Suitability

Based on available academic indicators, publication record, and demonstrated contributions to fuzzy mathematics and decision sciences, Muhammad Riaz exhibits characteristics commonly associated with candidates for international academic recognition. His combination of educational service, mathematical research, and interdisciplinary applications supports consideration within award frameworks that emphasize scholarly productivity, research impact, and innovation.[1][4]

Additional strengths include sustained publication activity, development of advanced fuzzy aggregation methodologies, practical decision-making applications, and commitment to higher research objectives through doctoral-level advancement in pure mathematics.[3]

Conclusion

Muhammad Riaz represents a researcher whose academic work combines theoretical mathematical development with practical applications in decision sciences. Through contributions to fuzzy algebra, aggregation operators, and computational decision-making frameworks, he has established a scholarly profile characterized by interdisciplinary relevance and measurable research impact. His continuing commitment to advanced research and mathematics education aligns with the objectives of international research recognition initiatives.[1][2]

References

  1. Elsevier. (n.d.). Scopus author details: Muhammad Riaz, Author ID 57611620500. Scopus. https://www.scopus.com/authid/detail.uri?authorId=57611620500
  2. ORCID. (n.d.). Muhammad Riaz ORCID Profile. https://orcid.org/0000-0001-8115-9168
  3. Abdul Wali Khan University. (2020). Fermatean Cubic Fuzzy Aggregation Operators with Applications in Decision-Making Problems. MPhil Thesis.
  4. Riaz, M., Shahzadi, T., Saqlain, M., & Merigó, J. M. (2026). Integrated LOPCOW-AROMAN framework with softmax hamacher information aggregation: Enhancing airport security screening efficiency in uncertain environment. Information Sciences.
  5. Farid, H.M.A., Razzaq, A., Riaz, M., Senapati, T., & Moslem, S. (2026). Optimising Wave Energy Plant Location Through Neutrosophic Multi-Criteria Group Decision-Making. CAAI Transactions on Intelligence Technology.

Hassan Shahzad | Mathematics | Editorial Board Member

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Mr. Hassan Shahzad | Mathematics | Editorial Board Member 

Academic Officer at Capital University of Science and Technology | Pakistan

Mr. Hassan Shahzad is an applied mathematician with a strong academic and research foundation in computational modeling, fluid dynamics, and numerical analysis. He holds advanced qualifications in mathematics, with rigorous training in key areas such as heat and mass transfer, computational fluid dynamics, electromagnetic wave theory, perturbation methods, celestial mechanics, and general relativity. His background is strengthened by extensive coursework in complex analysis, differential geometry, ordinary and partial differential equations, analytical mechanics, numerical methods, and functional analysis. Professionally, he has served in academic roles where he managed departmental operations, supported curriculum planning, facilitated student guidance, and contributed to institutional committees, along with earlier experience teaching mathematics at secondary and higher-secondary levels. His research interests center on magnetohydrodynamics, nanofluid flows, non-Fourier heat flux models, entropy generation, hybrid nanofluids, and bioconvective and electromagnetic flow systems, with a strong emphasis on numerical simulation and theoretical analysis. He is proficient in MATLAB, LaTeX, C, and C++, and skilled in boundary value problem solving through shooting methods, finite difference schemes, perturbation techniques, and Bvp4c implementations. His scholarly contributions include publications in reputable international journals, with additional manuscripts under review and in revision, reflecting ongoing productivity and academic commitment. With 814 citations by 717 documents, 41 published documents, and an h-index of 16, his research standing demonstrates meaningful impact within the scientific community. Beyond technical expertise, he has contributed to organizing academic conferences, supporting departmental coordination, and fostering collaborative research environments. His long-term vision is to advance as a leading researcher by generating high-quality, innovative work that bridges classical and emerging mathematical problems. Mr. Hassan Shahzad remains dedicated to expanding the frontiers of applied mathematics, strengthening interdisciplinary collaboration, and contributing solutions to complex real-world phenomena through mathematical modeling, numerical computation, and analytical rigor.

Profle: Scopus | Orcid 

Featured Publications:

  • Hudz, N., Turkina, V., Alyokhina, T., Motyka, O., Chemerys, N., Rumynska, T., Lozynskyi, A., Jasicka-Misiak, I., & Kobylinska, L. (2025). Chemical variability and biological potential of Cornu aspersum mucus as a source for the development of new cosmetic and pharmaceutical products. Molecules, 30(21), 4197.

  • Pokajewicz, K., Lamaka, D., & Hudz, N. (2024). Volatile profile of bee bread. Scientific Reports, 14, 6870.

  • Shanaida, M., Mykhailenko, O., Lysiuk, R., Hudz, N., Balwierz, R., Shulhai, A., Shapovalova, N., Shanaida, V., & Bjørklund, G. (2025). Carotenoids for antiaging: nutraceutical, pharmaceutical, and cosmeceutical applications. Pharmaceuticals, 18(3), 403.

  • Hudz, N., & Filipska, A. (2017). Elements of standardization and quality control of laboratory batches of peritoneal dialysis solutions containing dextrose and sodium lactate. ScienceRise: Pharmaceutical Science.

  • Hudz, N., Ivanova, R., & Brindza, J. (2017). Approaches to the determination of antioxidant activity of extracts from bee bread and safflower leaves and flowers. Potravinarstvo Journal.

  • Hudz, N., Yezerska, O., & Shanaida, M. (2019). Application of the Folin-Ciocalteu method to the evaluation of Salvia sclarea extracts. Pharmacia Journal.

  • Hudz, N., Kobylinska, L., Pokajewicz, K., Horčinová-Sedláčková, V., Fedin, R., Voloshyn, M., Myskiv, I., Brindza, J., Wieczorek, P. P., & Lipok, J. (2023). Mentha piperita: Essential oil and extracts, their biological activities, and perspectives on the development of new medicinal and cosmetic products. Molecules, 28(21), 7444.

  • Stepaniuk, N., Stepaniuk, A., Hudz, N., & Havryliuk, I. (2024). The impact of mitochondrial dysfunction on the pathogenesis of atherosclerosis. Wiadomości Lekarskie Medical Advances, 77(1).

  • Hudz, N., Grygorieva, O., & Brindza, J. (2019). Methodological approach to the elaboration of the analytical procedure of the antioxidant activity determination of Schisandra chinensis extracts. Agrobiodiversity Improvement, Nutrition, and Health Life Quality, 5(2), 250-257.

  • Hudz, N., Yezerska, O., Grygorieva, O., & Brindza, J. (2019). Analytical procedure elaboration of total flavonoid content determination and antimicrobial activity of bee bread extracts. Acta Poloniae Pharmaceutica.

 

Ahmed Ghezal | Mathematics | Best Research Article Award

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Prof. Dr. Ahmed Ghezal | Mathematics | Best Research Article Award

Professor at Abdelhafid Boussouf University of Mila | Algeria

Prof. Dr. Ahmed Ghezal is a distinguished scholar recognized for his contributions to mathematical modeling, stochastic processes, and nonlinear difference equations. He completed advanced academic training in mathematics and related analytical fields, building a strong foundation for his research career. Prof. Ghezal has gained extensive experience through university-level teaching, scholarly publishing, and active participation in peer review across leading international journals. His research interests span fractional calculus, dynamical systems, statistical modeling, and the analysis of complex recursive structures, with applications across science and engineering. As a faculty member contributing to university research and academic development, he is known for producing impactful studies and supporting the advancement of mathematical sciences. Prof. Dr. Ahmed Ghezal continues to play a significant role in fostering high-quality research and expanding theoretical understanding within his discipline.

Citation Metrics (Scopus)

400

300

200

100

0

Citations
342

Documents
50

h-index
13


Citations


Documents


h-index



View Scopus Profile

Featured Publications

Jiangjun Peng | Mathematics | Best Researcher Award – 1961

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Assoc. Prof. Jiangjun Peng | Mathematics | Best Researcher Award 

Associate Professor at Northwestern Polytechnical University | China

Asso. Prof. Jiangjun Peng is a distinguished scholar at the School of Mathematics and Statistics, Northwestern Polytechnical University, whose academic journey has been defined by dedication to advancing high-dimensional data analysis and intelligent algorithms. With a career spanning both academia and industry, he has significantly contributed to the areas of tensor data analysis, deep learning, and hyperspectral image processing. His research outcomes have received recognition in leading international journals, often being cited widely across disciplines. Beyond his technical expertise, he has actively engaged with the academic community as a reviewer, speaker, and contributor to professional associations.

Profile:

Orcid | Google Scholar

Education:

Asso. Prof. Jiangjun Peng’s educational background is deeply rooted in applied mathematics and statistics. He completed his bachelor’s degree in computational mathematics at Northwestern University, securing a strong foundation in analytical and numerical methods. His postgraduate studies at Xi’an Jiaotong University included both master’s and doctoral degrees, where he trained under the guidance of eminent professors. His doctoral research emphasized robust mathematical models for image processing, supported by rigorous statistical frameworks. This academic pathway equipped him with the technical knowledge, critical thinking, and problem-solving skills that now shape his innovative approaches to high-dimensional data representation.

Experience:

Asso. Prof. Jiangjun Peng’s professional experience bridges academia, industry, and collaborative research institutions. He began his career contributing as a researcher at the Tencent Video Search Center, where he developed advanced algorithms for large-scale video analysis. Later, he expanded his expertise as an assistant researcher at the Chinese University of Hong Kong, focusing on smart city applications and computational methods. Currently serving as an associate professor at Northwestern Polytechnical University, he leads multiple funded projects in collaboration with government, academic, and industrial bodies. His cross-sectoral experience underscores his ability to translate theoretical models into impactful real-world applications.

Research Interest:

Asso. Prof. Jiangjun Peng’s research interests lie at the intersection of applied mathematics, artificial intelligence, and remote sensing. He is particularly focused on tensor data analysis, hyperspectral image processing, and deep learning methods for high-dimensional data. His work involves developing robust algorithms that improve data recovery, denoising, and representation under noisy or incomplete conditions. These contributions have advanced the fields of image security, medical imaging, and environmental monitoring. He is also passionate about bridging model-driven and data-driven methodologies, enabling new solutions that integrate theoretical mathematics with cutting-edge machine learning for scientific and industrial innovation.

Awards and Honors:

Asso. Prof. Jiangjun Peng has earned recognition through prestigious institutional and industry awards that reflect both academic excellence and applied research contributions. His early research was honored with multiple scholarships and university-level accolades, highlighting his scholarly potential. His innovative work at Tencent earned him an industry award for advancing video data applications, while his collaborative project with Huawei received the Huawei Spark Award, showcasing successful academia-industry synergy. More recently, he was selected among the Rising Stars of Northwestern Polytechnical University, a distinction reserved for outstanding young faculty whose work shapes the future of scientific and technological advancement.

Publications:

Title: Hyperspectral image restoration via total variation regularized low-rank tensor decomposition
Citation: 474
Year of Publication: 2017

Title: Enhanced 3DTV regularization and its applications on HSI denoising and compressed sensing
Citation: 188
Year of Publication: 2020

Title: Guaranteed tensor recovery fused low-rankness and smoothness
Citation: 108
Year of Publication: 2023

Title: Exact Decomposition of Joint Low Rankness and Local Smoothness Plus Sparse Matrices
Citation: 93
Year of Publication: 2022

Title: Classical scoring functions for docking are unable to exploit large volumes of structural and interaction data
Citation: 90
Year of Publication: 2019

Title: Fast Noise Removal in Hyperspectral Images via Representative Coefficient Total Variation
Citation: 65
Year of Publication: 2022

Title: Learnable representative coefficient image denoiser for hyperspectral image
Citation: 16
Year of Publication: 2024

Conclusion:

Asso. Prof. Jiangjun Peng stands as a highly impactful researcher, educator, and innovator whose career seamlessly integrates theoretical mathematics with practical technological applications. His contributions to tensor analysis, hyperspectral imaging, and deep learning have not only advanced scientific understanding but also enabled real-world breakthroughs in security, healthcare, and environmental monitoring. Through prestigious awards, widely cited publications, and influential collaborations with industry leaders, he has demonstrated both academic brilliance and societal relevance. His nomination for this award is a recognition of his exceptional potential to continue shaping the future of data science and applied mathematics.

Shantia Yarahmadian | Mathematics | Best Researcher Award

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Dr. Shantia Yarahmadian | Mathematics | Best Researcher Award 

Applied Mathematics at Mississippi State University | United States

Dr. Shantia Yarahmadian is an Associate Professor of Mathematics whose career bridges applied mathematics, biology, quantum computing, and engineering sciences. His professional journey reflects a strong dedication to interdisciplinary problem-solving, focusing on challenges that require innovative mathematical modeling. With extensive teaching, research, and mentoring experience, Dr. Shantia Yarahmadian has contributed significantly to advancing knowledge in mathematical biology, stochastic modeling, and computational sciences. His work has also extended into emerging fields such as quantum-resistant blockchain and artificial intelligence applications. He continues to shape the future of mathematics through impactful publications, editorial roles, and leadership in both academic and industry settings.

Profile:

Orcid | Google Shcolar

Education:

Dr. Shantia Yarahmadian’s academic foundation is firmly rooted in applied mathematics and engineering. He earned his Ph.D. in Applied Mathematics from Indiana University, where he developed expertise in nonlinear analysis and boundary layer theory. Before this, he completed a Master’s degree in Mathematics at Isfahan University of Technology, followed by a Bachelor’s degree in Electrical Engineering at the same institution. This progression from engineering fundamentals to advanced mathematical research equipped him with a versatile skill set, allowing him to navigate both theoretical frameworks and practical applications. His educational background laid the groundwork for his diverse research portfolio across mathematics, biology, and computing.

Experience:

Dr. Shantia Yarahmadian has held prominent academic and research positions across universities and industry. As Associate Professor at Mississippi State University, he has developed innovative teaching methods, supervised doctoral and master’s students, and advanced interdisciplinary collaborations. Previously, he served as Assistant Professor in the same department and undertook a Postdoctoral Fellowship in Biology, where he applied mathematical modeling to biomedical challenges. His earlier career included roles as Research Assistant and Associate Instructor, shaping his dual strengths in pedagogy and research. In addition to academia, he also contributes as an industry advisor in cyber security, emphasizing blockchain and quantum-safe technologies.

Research Interests:

Dr. Shantia Yarahmadian’s research spans multiple disciplines, unified by the application of mathematics to real-world problems. In mathematical biology, he models microtubules, tumor radiotherapy, and Alzheimer’s disease progression, contributing to healthcare innovation. His expertise in nonlinear partial differential equations and stochastic processes supports advanced simulations and predictive modeling. In signal processing, his work with wavelets and compressed sensing improves data analysis across engineering and biomedical applications. His contributions to quantum computing and quantum-resistant blockchain represent forward-thinking approaches to cybersecurity and data integrity. Dr. Shantia Yarahmadian’s research highlights the powerful role of mathematical modeling in solving pressing challenges in science and technology.

Awards and Honors:

Dr. Shantia Yarahmadian has received recognition for his excellence in research, teaching, and mentorship throughout his career. He has been honored with awards for outstanding graduate student mentorship and faculty contributions, demonstrating his dedication to fostering future scholars. His innovative research projects in mathematical biology and engineering applications have attracted competitive funding and institutional support. He has also received prestigious fellowships and teaching awards that highlight his dual strengths in research and education. These honors reflect his international reputation as a thought leader in applied mathematics and his commitment to advancing knowledge through impactful academic and professional service.

Publications:

Title: An Ito stochastic differential equations model for the dynamics of the MCF-7 breast cancer cell line treated by radiotherapy
Citation: 27
Year of Publication: 2016

Title: On the use of the genetic algorithm filter-based feature selection technique for satellite precipitation estimation
Citation: 26
Year of Publication: 2012

Title: On the use of a cluster ensemble cloud classification technique in satellite precipitation estimation
Citation: 22
Year of Publication: 2012

Title: Existence and stability of steady states of a reaction convection diffusion equation modeling microtubule formation
Citation: 20
Year of Publication: 2011

Title: The use of compressive sensing and peak detection in the reconstruction of microtubules length time series in the process of dynamic instability
Citation: 16
Year of Publication: 2015

Title: A Hybrid Differential Equations Model for the Dynamics of Single and Double Strand Breaks of Cancer Cells Treated by Radiotherapy: A Meaning for Tumor Life-Span
Citation: 14
Year of Publication: 2022

Title: A Mathematical Model for Amyloid-β Aggregation in the Presence of Metal Ions: A Timescale Analysis for the Progress of Alzheimer Disease
Citation: 14
Year of Publication: 2019

Conclusion:

Dr. Shantia Yarahmadian stands out as a distinguished scholar whose career demonstrates a perfect balance between research innovation, academic mentorship, and cross-disciplinary collaboration. His contributions to mathematical biology, stochastic modeling, quantum computing, and engineering highlight his versatility and forward-thinking approach. By bridging theoretical mathematics with applied sciences, he has produced insights that benefit healthcare, cybersecurity, and data science. His impactful publications, global collaborations, and record of mentorship illustrate a sustained commitment to advancing knowledge and training the next generation of researchers. Dr. Shantia Yarahmadian is an exceptional candidate for award recognition in mathematics and interdisciplinary research.