Nafiseh Soleymani | Multi-View Data | Best Researcher Award

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Dr. Nafiseh Soleymani | Multi-View Data | Best Researcher Award

Nafiseh Soleymani | Azad University of Mashhad | Iran

Dr. Nafiseh Soleymani is a computer scientist and Ph.D. candidate at Azad University of Mashhad, Iran, specializing in data science, machine learning, multi-view data analysis, and unsupervised learning. Her research focuses on developing efficient methods for analyzing high-dimensional and multi-view datasets, emphasizing non-negative matrix factorization (NMF), clustering algorithms, and feature selection techniques. With a strong technical foundation in programming (C++, C#, Matlab) and database systems, she combines theoretical research with applied computational methods. Dr. Soleymani’s studies contribute to improving data representation, dimensionality reduction, and classification performance in complex data environments, making her work valuable to the fields of artificial intelligence, bioinformatics, and big data analytics.

Profile: Google Scholar 

Featured Publications

Soleymani, N., Moattar, M. H., & Sheibani, R. (2025). Dealing with high dimensional multi-view data: A comprehensive review of non-negative matrix factorization approaches in data mining and machine learning. Computer Science Review, 58, 100788. Citation count: —.

Soleymani, N., Moattar, M. H., & Sheibani, R. (2025). Corrigendum to “Dealing with high dimensional multi-view data: A comprehensive review of non-negative matrix factorization approaches in data mining and machine learning.” Computer Science Review, 100841. Citation count: —.

Soleymani, N., & Moattar, M. H. (2018, February). An approach based on resampling and feature selection to improve the classification of microarray data. 2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS), 61–64. IEEE. Citation count: 2.

Moattar, M. H., & Soleymani, N. (2019). Twin support vector machine-based clustering for feature selection in microarray data classification problem. Journal of Information Technology in Engineering Design, 12(1), 30–39. Citation count: —.

Raghavendran Prabakaran | Fractional Differential Equations | Best Researcher Award

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Dr. Raghavendran Prabakaran | Fractional Differential Equations | Best Researcher Award

Researcher | Vel Tech Rangarajan Dr. Sagunthala R\&D Institute of Science and Technology | India

Dr. Raghavendran Prabakaran is an emerging mathematician specializing in fractional differential equations, integral transforms, control theory, and their applications in artificial intelligence and cryptography. With over 60 research contributions, including SCI and Scopus-indexed journal papers, conference presentations, book chapters, and patents, his work demonstrates both theoretical depth and applied innovation. His research focuses on the development and analysis of mathematical models for complex systems, emphasizing existence, stability, and controllability results in fractional calculus. Through rigorous analytical approaches and novel transform methods, Dr. Raghavendran advances the understanding of fractional integro-differential systems, contributing to both pure and applied mathematics. His growing citation impact across Scopus, Web of Science, and Google Scholar reflects his rising influence in computational and applied mathematical research.

Profiles: Scopus | Orcid | Google Scholar 

Featured Publications

Raghavendran, P., Gunasekar, T., Balasundaram, H., Santra, S. S., & Baleanu, D. (2024). Solving fractional integro-differential equations by Aboodh transform. Journal of Mathematics and Computer Science, 34, —. Citation count: 34.

Gunasekar, T., Raghavendran, P., Santra, S. S., & Sajid, M. (2024). Existence and controllability results for neutral fractional Volterra–Fredholm integro-differential equations. Journal of Mathematics and Computer Science, 34(4), 361–380. Citation count: 33.

Gunasekar, T., Raghavendran, P., Santra, S. S., & Sajid, M. (2024). Analyzing existence, uniqueness, and stability of neutral fractional Volterra–Fredholm integro-differential equations. Journal of Mathematics and Computer Science, 33(4), 390–407. Citation count: 29.

Gunasekar, T., Raghavendran, P., Santra, S. S., Majumder, D., & Baleanu, D. (2024). Application of Laplace transform to solve fractional integro-differential equations. Journal of Mathematics and Computer Science, 33(3), 225–237. Citation count: 26.

Gunasekar, T., & Raghavendran, P. (2024). The Mohand transform approach to fractional integro-differential equations. Journal of Computational Analysis and Applications, 33(1), 358–371. Citation count: 25.

Oluwanife Falebita | Mathematics Education | Best Researcher Award

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Dr. Oluwanife Falebita | Mathematics Education | Best Researcher Award

Oluwanife Falebita | University of Zululand | South Africa

Dr. Oluwanife S. Falebita is an accomplished scholar in Mathematics Education and Artificial Intelligence in STEM learning, with a Ph.D. from Ekiti State University, Nigeria. Her research focuses on AI integration in education, examining factors such as technological readiness, self-efficacy, attitudes, and anxiety among students and educators. She has contributed to advancing digital pedagogy in African higher education, emphasizing AI adoption, gender equity, and innovative teaching strategies for improved learning outcomes. Through her interdisciplinary work, Dr. Falebita explores the intersection of education technology, emotional factors, and inclusive learning, shaping the evolving landscape of AI-enhanced mathematics education across developing regions.

Profiles: Scopus | Orcid | Goole Scholar 

Featured Publications

Falebita, O. S., & Kok, P. J. (2025). Artificial intelligence tools usage: A structural equation modeling of undergraduates’ technological readiness, self-efficacy and attitudes. Journal for STEM Education Research, 8(2), 257–282. Citation count: 45.

Falebita, O. S., & Kok, P. J. (2024). Strategic goals for artificial intelligence integration among STEM academics and undergraduates in African higher education: A systematic review. Discover Education, 3(1), 151. Citation count: 31.

Falebita, O. S. (2024). Assessing the relationship between anxiety and the adoption of artificial intelligence tools among mathematics preservice teachers. Interdisciplinary Journal of Education Research, 6, 1–13. Citation count: 19.

Azeez, F. A., Osiesi, M. P., Aribamikan, C. G., Nubia, W. D., Odinko, M. N., & Falebita, O. S. (2024). Exclusion of the female child from primary education: Exploring the perceptions and experiences of female learners in northern Nigeria. Education 3–13, 1–20. Citation count: 18.

Olofin, S. O., & Falebita, O. S. (2020). Kolawole’s problem-solving (KPS) method as a tool for quality teaching and evaluation in open and distance education. Online Submission, 1(3), 86–95. Citation count: 9.

Vasso Papadimitriou | Cost Estimation Models | Best Researcher Award

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Dr. Vasso Papadimitriou | Cost Estimation Models | Best Researcher Award

Researcher | Aristotle University of Thessaloniki | Greece

Dr. Vasso Papadimitriou is a forward-thinking researcher specializing in artificial intelligence applications in construction engineering, with a focus on cost estimation, digital construction, and sustainable project management. Her research bridges engineering design, machine learning, and construction technology, developing intelligent tools to enhance decision-making accuracy in building renovation and infrastructure projects.

Affiliated with the Aristotle University of Thessaloniki and the University of Macedonia, Dr. Papadimitriou’s work contributes to advancing AI-driven predictive models that improve efficiency and reduce uncertainty in project budgeting and execution. She applies methods such as Artificial Neural Networks (ANNs), Radial Basis Functions (RBFs), and TOPSIS to optimize renovation cost forecasting, aligning with the United Nations Sustainable Development Goals (SDG 9 and SDG 17).

Her research has been published in high-impact journals indexed in Scopus, Web of Science (SCI-Expanded, ESCI), and Google Scholar, with growing recognition for her innovative use of computational models in sustainable engineering and design. Through her comparative analyses and model development, Dr. Papadimitriou contributes to the digital transformation of the construction industry, shaping the future of AI-powered engineering solutions.

Profiles: Scopus | Orcid | Google Scholar | Web of Science 

Featured Publications

Papadimitriou, V. E., & Aretoulis, G. N. (2024). A final cost estimating model for building renovation projects. Buildings, 14(4), 1072. Citation count: 8.

Papadimitriou, V. E., Aretoulis, G. N., & Papathanasiou, J. (2024). Radial Basis Function (RBF) and Multilayer Perceptron (MLP) comparative analysis on building renovation cost estimation: The case of Greece. Algorithms, 17(9), 390. Citation count: 4.

Papadimitriou, V. E., & Aretoulis, G. N. (2025). An innovative approach regarding efficient and expedited early building renovation cost estimation utilizing ANNs and the TOPSIS methodology. Algorithms, 18(11), 696. Citation count: —.

Papadimitriou, V., & Aretoulis, G. (2023). Neural network models as a cost prediction tool to prevent building construction projects from a failure—A literature review. Proceedings of the Erasmus+ PROSPER Project International Scientific Conference. Citation count: 1.

 

Fatemeh Barati | Pure Mathematics | Women Researcher Award

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Dr. Fatemeh Barati | Pure Mathematics | Women Researcher Award

Post graduated student | Qom university | Iran

Dr. Fatemeh Barati is a mathematician specializing in Finsler geometry, differential geometry, and Lie algebroid structures. She earned her Ph.D. in Mathematics from Qom University, Iran, where her doctoral research titled “On Landsberg Curvature in Finsler Geometry” focused on geometric structures and curvature properties within Finsler spaces. Her work explores advanced topics in curvature theory, Finsler metrics, and geometric structures on manifolds, contributing to the development of modern differential geometry.

Dr. Barati’s earlier research in Lie algebroids and topological fiber bundle structures reflects her deep engagement with the algebraic and geometric foundations of mathematics. She has presented her research at multiple national conferences, including the Geometric and Topology Seminar (GTS7) and The Seminar on Geometry and Topology (Tabriz, Iran).

Her publications—featured in journals such as Differential Geometry and its Applications and Computational Methods for Differential Equations—address topics like L-reducible Finsler metrics, Kropina metrics, and Ricci-quadratic Randers metrics, advancing both theoretical understanding and mathematical classification in geometry.

Profile: Google Scholar 

Featured Publications

  1. Tayebi, A., & Barati, F. (2024). On weakly stretch Kropina metrics. Differential Geometry and its Applications, 93, 102118.
    Citations: —

  2. Najafi, B., Tayebi, A., & Barati, F. (2025). Classification of three-dimensional left-invariant Ricci-quadratic Randers metrics and its applications. Computational Methods for Differential Equations.
    Citations: —

  3. Tayebi, A., & Barati, F. (2023). On L-reducible spherically symmetric Finsler metrics. Differential Geometry and its Applications, 90, 102028.
    Citations: 5

  4. Barati, F. (2023). On class of square Finsler metrics. Journal of Finsler Geometry and its Applications, 4(2), 74–91.
    Citations: —

  5. Barati, F., & Farhangdoost, M. R. (2014). Nilpotent and solvable Lie algebroids. International Journal of Multidisciplinary and Scientific Emerging Research, 3(2).
    Citations: 1

 

George Efthimiou | Mathematical Engineering | Best Researcher Award

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Dr. George Efthimiou | Mathematical Engineering | Best Researcher Award

Research scientist | FLUENC | Greece

Dr. George C. Efthimiou is a distinguished researcher specializing in Computational Fluid Dynamics (CFD), environmental modeling, and exposure prediction in urban and industrial environments. He earned his Ph.D. in Mechanical Engineering (2013) from the University of Western Macedonia, Greece, where his doctoral work focused on the Prediction of Individual Exposure using Computational Fluid Dynamics Modelling under the supervision of Professor John G. Bartzis.

His multidisciplinary background, combining energy resource management and mechanical engineering, underpins a career devoted to advancing sustainability, atmospheric dispersion modeling, and risk assessment methodologies.

Dr. Efthimiou has held key research positions at leading Greek institutions, including:

  • Postdoctoral Research Fellow at the Nuclear & Radiological Sciences & Technology, Energy & Safety Division, N.C.S.R. DEMOKRITOS (2014–2019)

  • Research Associate at the Sustainability Engineering Laboratory (SEL), Aristotle University of Thessaloniki (2019–2024)

  • Research Scientist at the Advanced Renewable Technologies & Environmental Materials in Integrated Systems Laboratory, Centre for Research and Technology – Hellas (CERTH)

His scientific contributions span urban air quality modeling, hazardous pollutant dispersion, exposure assessment, and renewable energy systems. His studies have provided validated methodologies for predicting human exposure to airborne hazards and have influenced policy and safety assessments in both industrial and environmental contexts.

Dr. Efthimiou’s research has been featured in international conferences and peer-reviewed journals such as Toxics, Fluids, and the Journal of Hazardous Materials Advances, highlighting his role in bridging theoretical modeling with practical environmental applications.

Profiles: Scopus | Orcid | Google Scholar 

Featured Publications

  1. Efthimiou, G. C., Barmpas, F., Tsegas, G., & Moussiopoulos, N. (2021). Development of an algorithm for prediction of the wind speed in renewable energy environments. Fluids, 6(12), 461.
    Citations: 6

  2. Efthimiou, G. C., Andronopoulos, S., Venetsanos, A., Kovalets, I. V., & Kakosimos, K. (2016). Modification and validation of a method for estimating the location of a point stationary source of passive non-reactive pollutant in an urban environment. In Proceedings of the 17th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes (HARMO 2016).
    Citations: 6

  3. Efthimiou, G. C., Bartzis, J. G., Berbekar, E., Hertwig, D., Harms, F., & Leitl, B. (2015). Modelling short-term maximum individual exposure from airborne hazardous releases in urban environments. Part II: Validation of a deterministic model with wind tunnel experiments. Toxics, 3(3), 259–267.
    Citations: 6

  4. Bartzis, J. G., Sakellaris, I. A., & Efthimiou, G. C. (2022). On exposure uncertainty quantification from accidental airborne point releases. Journal of Hazardous Materials Advances, 6, 100080.
    Citations: 5

  5. Mertzanis, A., Goudelis, G., Efthimiou, G., & Kontogianni, A. (2010). The impact to the environment and the geomorphological processes as a result of human activity in littoral and inland wetlands in Greece. In Proceedings of the International Conference on Protection and Restoration of the Environment.
    Citations: 7

 

 

Engin Özkan | Number Theory | Best Researcher Award

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Prof. Dr. Engin Özkan | Number Theory | Best Researcher Award

Head of the Department of Mathematics | Marmara University | Turkey

Prof. Dr. Engin Özkan is a distinguished mathematician specializing in number theory, combinatorics, and polynomial structures of number sequences. His research explores the properties and transformations of Fibonacci, Pell, Jacobsthal, and Lucas-type sequences, along with their applications in finite groups and algebraic structures. Through his extensive academic career at leading institutions in Turkey and abroad, including Marmara University and The Ohio State University, he has contributed significantly to the development of generalized number sequences and their combinatorial representations. Prof. Özkan’s studies advance the theoretical foundations of sequence polynomials and trace formulas, bridging classical and modern mathematical theory.

Profiles: Scopus | Orcid | Google Scholar | Web of Science 

Featured Publications

  1. Taştan, M., & Özkan, E. (2021). Catalan transform of the k-Pell, k-Pell–Lucas and modified k-Pell sequence. Notes on Number Theory and Discrete Mathematics, 27(1), 198–207. Citation count: 25.

  2. Taştan, M., Özkan, E., & Shannon, A. G. (2021). The generalized k-Fibonacci polynomials and generalized k-Lucas polynomials. Notes on Number Theory and Discrete Mathematics, 27(2), 148–158. Citation count: 24.

  3. Kuloğlu, B., Özkan, E., & Shannon, A. G. (2022). The Narayana sequence in finite groups. Fibonacci Quarterly, 60(5), 212–221. Citation count: 22.

  4. Özkan, E., Uysal, M., & Kuloğlu, B. (2022). Catalan transform of the incomplete Jacobsthal numbers and incomplete generalized Jacobsthal polynomials. Asian-European Journal of Mathematics, 22501194. Citation count: 22.

  5. Özkan, E., & Uysal, M. (2021). Mersenne–Lucas hybrid numbers. Mathematica Montisnigri, 52, 17–29. Citation count: 21.

 

 

Vahid Goodarzimehr | Optimization | Best Researcher Award

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Assist. Prof. Dr. Vahid Goodarzimehr | Optimization | Best Researcher Award

Assistant professor | Shahid Chamran University of Ahvaz | Iran

Dr. Vahid Goodarzimehr is a pioneering researcher in computational mechanics, structural optimization, and metaheuristic algorithms, with his groundbreaking work inspired by Einstein’s theory of relativity. He introduced the Special Relativity Search (SRS) algorithm — a novel metaheuristic method that simulates relativistic physics to solve complex engineering and mathematical optimization problems. His research integrates artificial intelligence, optimization theory, and physics-based modeling to advance dynamic and structural design systems. With publications in top-tier Q1 journals such as Knowledge-Based Systems, Computer Methods in Applied Mechanics and Engineering, and Engineering Structures, Dr. Goodarzimehr has established himself as a leading innovator in physics-inspired computational optimization. His algorithms like SRS, MOSRS, and SABO have significantly influenced the next generation of engineering problem-solving tools.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

  1. Goodarzimehr, V., Shojaee, S., Hamzehei-Javaran, S., & Talatahari, S. (2022). Special relativity search: A novel metaheuristic method based on special relativity physics. Knowledge-Based Systems, 257, 109484. Citation count: 101.

  2. Omidinasab, F., & Goodarzimehr, V. (2020). A hybrid particle swarm optimization and genetic algorithm for truss structures with discrete variables. Journal of Applied and Computational Mechanics, 6(3), 593–604. Citation count: 64.

  3. Goodarzimehr, V., Topal, U., Das, A. K., & Vo-Duy, T. (2023). Bonobo optimizer algorithm for optimum design of truss structures with static constraints. Structures, 50, 400–417. Citation count: 37.

  4. Goodarzimehr, V., Talatahari, S., Shojaee, S., & Hamzehei-Javaran, S. (2023). Special relativity search for applied mechanics and engineering. Computer Methods in Applied Mechanics and Engineering, 403, 115734. Citation count: 35.

  5. Talatahari, S., Goodarzimehr, V., & Taghizadieh, N. (2020). Hybrid teaching-learning-based optimization and harmony search for optimum design of space trusses. Journal of Optimization in Industrial Engineering, 13(1), 177–194. Citation count: 32.

 

 

 

David Raju Thommandru | Mathematical Modeling | Mathematical Modeling Breakthrough Award

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Dr. David Raju Thommandru | Mathematical Modeling | Mathematical Modeling Breakthrough Award

Research scholar | VIT-AP University | India

Dr. T. David Raju is an Assistant Professor of Mathematics at R.K. College of Engineering & Technology, Kethanakonda, with over 15 years of academic experience. His research focuses on mathematical modeling, nonlinear dynamics, and ecological systems, particularly analyzing tipping points and time delays in complex biological interactions. His work bridges applied mathematics with ecology, contributing valuable insights into predator–prey dynamics under environmental stress. With a strong academic background (M.Phil., M.Sc., M.Ed.) and a Silver Medal from Andhra University, he combines teaching excellence with impactful research in applied nonlinear systems.

Profile: Scopus

Featured Publications

  1. T. David Raju (2025). Uncovering ecological thresholds: Effects of external stress driven tipping point and delay in predator–prey system. Chaos, Solitons & Fractals (Open Access).

 

 

 

Ilhem Kadri | Applied Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Ilhem Kadri | Applied Mathematics | Best Researcher Award

Associate Professor | University of Oran 1 – Ahmed Ben Bella | Algeria

Dr. Ilhem Kadri is an Associate Professor of Applied Mathematics at the University of Oran 1, Algeria, specializing in fractional calculus, nonlinear partial differential equations, and computational mathematics. She earned her Ph.D. in Applied Mathematics from the University of Jordan, following her master’s and bachelor’s degrees in mathematics from the University of Oran 1 Ahmed Ben Bella. Dr. Kadri’s academic and research trajectory reflects a deep commitment to advancing the analytical and numerical treatment of fractional and conformable differential equations, as well as exploring chaotic and nonlinear dynamical systems. Her scholarly contributions include numerous research articles in internationally recognized journals, such as the European Journal of Pure and Applied Mathematics, Mathematics, and Results in Nonlinear Analysis, where she has developed novel analytical and numerical frameworks including the Laplace Transform Decomposition Method, the Conformable Fractional Laplace Transform Method, and applications of fractional Fourier series and tensor product techniques. She has presented her work at several prestigious international conferences and symposia across Europe, Asia, and Africa, contributing to global dialogues on applied and computational mathematics. Dr. Kadri is also actively engaged in academic collaboration, scientific workshops, and professional development activities focused on enhancing research impact and innovation in mathematical sciences. Her expertise and scholarly output reflect a strong foundation in both theoretical and applied aspects of mathematics, positioning her as an influential contributor to the field of fractional calculus and nonlinear analysis.10 Citations, 4 Documents, 2 h-index.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Kadri, I.*, Al-Horani, M., & Khalil, R. (2022). Solution of non-linear fractional Burger’s type equations using the Laplace transform decomposition method. Results in Nonlinear Analysis, 5(2), 131–150. Citations: 12.

2. Kadri, I.*, Al Horani, M., & Khalil, R. (2023). Solution of fractional Laplace type equation in conformable sense using fractional Fourier series with separation of variables technique. Results in Nonlinear Analysis, 6(2), 53–59. Citations: 10.

3. Kadri, I.*, Horani, M., & Khalil, R. (2020). Tensor product technique and fractional differential equations. Journal of Semigroup Theory and Applications, Article ID 6. Citations: 5.

4. Ahmed, A. I., Elbadri, M., Alotaibi, A. M., Ashmaig, M. A. M., Dafaalla, M. E., & Kadri, I.* (2025). Chaos and dynamic behavior of the 4D hyperchaotic Chen system via variable-order fractional derivatives. Mathematics, 13(20), 3240.

5. Kadri, I.*, Saadeh, R. S., AlMutairi, D. M., Dafaalla, M. E., Berir, M., & Abdoon, M. A. (2025). Analytical and numerical investigation of a fractional order 4D chaotic system via Caputo fractional derivative. European Journal of Pure and Applied Mathematics, 18(3).