Mumtaz Khan | Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Mumtaz Khan | Mathematics | Best Researcher Award

Chuxiong Normal university | China

Assoc. Prof. Dr. Mumtaz Khan is a well-established researcher in applied mathematics and thermal–fluid sciences, with significant contributions to magnetohydrodynamics, nanofluid heat transfer, fractional calculus, and advanced numerical modeling. He has authored 37 scholarly documents, which have received 743 citations from 509 citing publications, demonstrating strong visibility and influence in the scientific community, with an h-index of 17. His research integrates fractional-order modeling, hybrid nanofluids, non-Newtonian fluid dynamics, porous media flow, and heat and mass transfer under complex physical effects such as magnetic fields, thermal radiation, slip conditions, and chemical reactions. He has published extensively in high-impact international journals, including Mathematical Methods in the Applied Sciences, Case Studies in Thermal Engineering, Ain Shams Engineering Journal, and ZAMM. His recent work also incorporates artificial neural networks and optimization techniques to enhance predictive accuracy in transport phenomena, contributing valuable theoretical and computational insights for engineering and energy-related applications.

 

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Featured Publications

Raziyeh Erfanifar | Mathematics | Research Excellence Award

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Dr. Raziyeh Erfanifar | Mathematics | Research Excellence Award

Shahid Beheshti University | Iran

Dr. Raziyeh Erfanifar is a researcher in applied mathematics and computational engineering whose work centers on high-order iterative methods, nonlinear equations, matrix and tensor computations, and their applications in control theory, signal processing, image processing, data mining, and fractional calculus. The research contributions emphasize the development of efficient, inversion-free, and high-convergence iterative algorithms for solving nonlinear systems, algebraic Riccati equations, nonlinear matrix and tensor equations, and computing Moore–Penrose and Drazin inverses. A significant portion of the work advances fixed-point theory, weight-splitting strategies, Newton-type schemes, and parametric multi-step methods, with rigorous convergence analysis and efficiency evaluation. These methods have been successfully applied to problems in electrical engineering, vibration and control systems, differential equations, tensor equations with Einstein products, data whitening, and numerical simulation. The scholarly output includes 36 peer-reviewed journal articles published in leading journals such as Journal of the Franklin Institute, Journal of Complexity, Computational and Applied Mathematics, Circuits, Systems, and Signal Processing, Applied Numerical Mathematics, and Engineering Computations. According to Google Scholar metrics, this body of work has received 274 citations, with an h-index of 11 and an i10-index of 11, reflecting sustained impact and strong visibility in numerical analysis, computational mathematics, and engineering applications.

 

Citation Metrics (Google Scholar)

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Featured Publications

Several efficient iterative algorithms for solving nonlinear tensor equation
X + AT*N X−1*N A = I with Einstein product
– Computational and Applied Mathematics, 2024

Splitting iteration methods to solve non-symmetric algebraic Riccati matrix equation
YAY − YB − CY + D = 0
– Numerical Algorithms, 2023

Davron Juraev | Mathematics | Best Researcher Award

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Prof. Dr. Davron Juraev | Mathematics | Best Researcher Award

Turon University | Uzbekistan

Prof. Dr. Davron Juraev is a leading mathematical scientist recognized for his profound contributions to mathematical physics, numerical analysis, and applied mathematics, with a citation record of 1421 citations, an h-index of 22, and an i10-index of 39. His extensive publication portfolio covers topics such as the Cauchy problem, Helmholtz equations, fractional calculus, and ill-posed problems, making significant theoretical and computational advancements. Prof. Juraev has served as Editor-in-Chief of the Karshi Multidisciplinary International Scientific Journal (KMISJ) and on editorial boards of numerous international journals, including IETI Transactions on Data Analysis and Forecasting (iTDAF), Computational Algorithms and Numerical Dimensions (CAND), and Advanced Engineering Science (AES). He has also acted as a Guest Editor for special issues in Axioms (Switzerland) and Global and Stochastic Analysis (India). His research leadership extends to major projects funded by the Academy of Sciences of Uzbekistan and the Ministry of Innovative Development, focusing on dynamic systems and anti-radar missile trajectory optimization. Widely respected as a reviewer, collaborator, and innovator, Prof. Juraev’s works continue to influence contemporary research in computational modeling, differential equations, and mathematical problem-solving worldwide.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Efendiev, R. F., Juraev, D. A., & Elsayed, E. E. (2025). PT-symmetric Dirac inverse spectral problem with discontinuity conditions on the whole axis. Symmetry, 17(10), 1603.

Martin, N., Yue, G. X. G., & Juraev, D. A. (2025). Plithogenic machine learning solutions to material selection in renewable energy systems. IETI Transactions on Data Analysis and Forecasting (iTDAF), 3(3), Article 57085.

Juraev, D. A. (2025). A mathematical model for the maintenance scheduling problem with disturbance effect and single maintenance team. Advanced Mathematical Models and Applications, 10(2), 304.

Basholli, F., Hayal, M. R., Elsayed, E. E., & Juraev, D. A. (2025). Deep learning for skin disease classification: A comparative study of CNN and CNN-LSTM architectures. Journal of Computing and Data Technology, 1(1), 40–49.

Niyozov, I. E., Juraev, D. A., Efendiev, R. F., & Abdalla, M. (2025). Cauchy problem for the biharmonic equation. Journal of Umm Al-Qura University for Applied Sciences, 5(2), 244.

Liu, T., Ding, B., Nemati Saray, B., Juraev, D. A., & Elsayed, E. E. (2025). On the pseudospectral method for solving the fractional Klein–Gordon equation using Legendre cardinal functions. Fractal and Fractional, 9(3), 177.

Annaghili, S., Efendiev, R., Juraev, D. A., & Abdalla, M. (2025). Spectral analysis for the almost periodic quadratic pencil with impulse. Boundary Value Problems, 2025(1), 27.

Abdulwahid, M. M., Kurnaz, S., Kurnaz Türken, A., Hayal, M. R., Elsayed, E. E., & Juraev, D. A. (2025). Performance analysis of input power variations in high data rate DWDM-FSO systems under various rain conditions. Journal of Optics, 54(1), 47.

Juraev, D. A., Agarwal, P., Shokri, A., & Elsayed, E. E. (2024). Cauchy problem for matrix factorizations of Helmholtz equation on a plane. In Recent Trends in Fractional Calculus and Its Applications (pp. 245–258). Elsevier.

Juraev, D. A., Agarwal, P., Shokri, A., & Elsayed, E. E. (2024). Integral formula for matrix factorizations of Helmholtz equation. In Recent Trends in Fractional Calculus and Its Applications (pp. 233–243). Elsevier.

Juraev, D. A., Noeiaghdam, S., Agarwal, P., & Agarwal, R. P. (2024). On the Cauchy problem for systems of linear equations of elliptic type of the first order in the space R^m. Turkish World Mathematical Society Journal of Applied and Engineering Mathematics, 4(1), 77–90.*

Juraev, D. A., Agarwal, P., Shokri, A., & Elsayed, E. E. (2024). The Cauchy problem for matrix factorizations of Helmholtz equation in space. In Recent Trends in Fractional Calculus and Its Applications (pp. 259–273). Elsevier.

Niyozov, I. E., Juraev, D. A., Efendiev, R. F., & Jalalov, M. J. (2024). The Cauchy problem for the system of elasticity. Journal of Contemporary Applied Mathematics, 14(2), 92.

Muxammedov, B. M., Sanko, A. A., Juraev, D. A., & Elsayed, E. E. (2024). Optimizing rocket trajectories: Advanced mathematical modeling in MATLAB/Simulink. International Journal of Information Technology, 16(12), 2162.

Putra, F. G., Putra, R. W. Y., Ricardo, S., Widyawati, S., & Juraev, D. A. (2024). Effectiveness of meaningful instructional design in improving students' mathematical skills. Journal of Philology and Educational Sciences, 32(5), 325.

Liu, T., Xue, R., Ding, B., Juraev, D. A., Nemati Saray, B., & Soleymani, F. (2024). A novel and effective scheme for solving the fractional telegraph problem via the spectral element method. Fractal and Fractional, 8(12), 711.

Elsayed, E. E., Hayal, M. R., & Juraev, D. A. (2024). Ensemble machine learning approaches for robust classification of maize plant leaf diseases. Journal of Modern Technology, 1(2), 87–93.

Egamberdiev, K., Khidirova, N., Juraev, D. A., & Elsayed, E. E. (2024). Numerical solution of groundwater modeling for mountain regions of Uzbekistan. Discover Water, 4(1), 159.

Behzad Nemati Saray | Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Behzad Nemati Saray | Mathematics | Best Researcher Award

Institute for Advanced Studies in Basic Sciences (IASBS) | Iran

Assoc. Prof. Dr. Behzad Nemati Saray is a distinguished mathematician whose research spans numerical analysis, applied mathematics, and computational methods. With an impressive record of 840 citations, h-index of 17, and i10-index of 22, his work demonstrates significant academic influence, particularly in developing efficient algorithms and multiwavelet-based methods for solving differential and integro-differential equations. He has published over 30 refereed journal papers and numerous conference articles that address complex mathematical problems, including fractional equations, Burgers equations, and Sturm–Liouville systems. As a reviewer for MathSciNet (AMS) and an active contributor to international mathematical conferences, he has earned recognition for his leadership roles, such as Director-in-Charge of the Seasonal School in Mathematics at IASBS and Executive Board member in academic seminars. His scholarly excellence was acknowledged when he was named Best Researcher of the Year (2023) at the Institute for Advanced Studies in Basic Sciences (IASBS). Dr. Saray’s contributions to the fields of computational mathematics and applied analysis continue to advance numerical modeling, multiscale methods, and spectral techniques, making his research a cornerstone for future developments in applied and computational mathematics. His sustained impact reflects a deep commitment to innovation and precision in mathematical sciences.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Liu, T., Ding, B., Nemati Saray, B., Juraev, D. A., & Elsayed, E. E. (2025). On the pseudospectral method for solving the fractional Klein–Gordon equation using Legendre cardinal functions. Fractal and Fractional, 9(3), 177. Multidisciplinary Digital Publishing Institute.

Shi, L., Nemati Saray, B., & Soleymani, F. (2024). Sparse wavelet Galerkin method: Application for fractional Pantograph problem. Journal of Computational and Applied Mathematics, 116081.

Liu, T., Xue, R., Ding, B., Juraev, D. A., Nemati Saray, B., & Soleymani, F. (2024). A novel and effective scheme for solving the fractional telegraph problem via the spectral element method. Fractal and Fractional, 8(12), 711. Multidisciplinary Digital Publishing Institute.

Ranjbari, S., Baghmisheh, M., Jahangiri Rad, M., & Nemati Saray, B. (2024). On the wavelet Galerkin method for solving the fractional Fredholm integro-differential equations. Computational Methods for Differential Equations.

Tarbiyati, H., & Nemati Saray, B. (2023). Weight initialization algorithm for physics-informed neural networks using finite differences. Engineering with Computers.

Afarideh, A., Dastmalchi Saei, F., & Nemati Saray, B. (2023). Eigenvalue problem with fractional differential operator: Chebyshev cardinal spectral method. Journal of Mathematical Modeling.

Shahriari, M., Nemati Saray, B., Mohammadalipour, B., & Saeidian, S. (2023). Pseudospectral method for solving the fractional one-dimensional Dirac operator using Chebyshev cardinal functions. Physica Scripta.

Pourfattah, E., Jahangiri Rad, M., & Nemati Saray, B. (2023). An efficient algorithm based on the pseudospectral method for solving Abel's integral equation using Hermite cubic spline scaling bases. Applied Numerical Mathematics.

Nemati Saray, B. (2022). On a multiwavelet spectral element method for integral equation of a generalized Cauchy problem. BIT Numerical Mathematics.

Nemati Saray, B. (2021). Pseudospectral method for solving fractional Sturm-Liouville problem using Chebyshev cardinal functions. Physica Scripta.

Nemati Saray, B. (2021). Abel’s integral operator: Sparse representation based on multiwavelets. BIT Numerical Mathematics.

Nemati Saray, B. (2021). On the sparse multiscale representation of 2-D Burgers equations by an efficient algorithm based on multiwavelets. Numerical Methods for Partial Differential Equations.

Nemati Saray, B. (2020). On the sparse multi-scale solution of the delay differential equations by an efficient algorithm. Applied Mathematics and Computation.

Nemati Saray, B. (2020). Reconstruction of the Sturm-Liouville differential operators with discontinuity conditions and a constant delay. Indian Journal of Pure and Applied Mathematics.

Nemati Saray, B. (2020). Heat and mass transfer investigation of MHD Eyring–Powell flow in a stretching channel with chemical reactions. Physica A: Statistical Mechanics and its Applications.

Nemati Saray, B. (2020). Sparse multiscale representation of Galerkin method for solving linear-mixed Volterra-Fredholm integral equations. Mathematical Methods in the Applied Sciences.

Muhammad Tahir | Mathematics | Young Scientist Award

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Dr. Muhammad Tahir | Mathematics | Young Scientist Award

Gomal University | Pakistan

Dr. Muhammad Tahir is an emerging researcher and academic in the field of applied mathematics, with expertise spanning numerical analysis, fuzzy logic, artificial intelligence, and decision-making systems. He has served as a Lecturer in Mathematics at Beacon Light College, Pakistan, and as a Teaching Assistant at the Islamia University of Bahawalpur, where he contributed to curriculum development and quality enhancement initiatives. Dr. Tahir holds a Master of Science in Mathematics from the Islamia University of Bahawalpur, where his thesis focused on the “Numerical Study of Deformation of Bubbles Using Phase-Field Models with Decoupling Technique.” His research portfolio includes several high-impact publications in reputed journals such as Applied Soft Computing, European Journal of Pure and Applied Mathematics, and Engineering Applications of Artificial Intelligence. His studies cover topics like fuzzy set theory, cryptographic security, cyber risk mitigation, environmental sustainability, and multi-criteria decision-making. Dr. Tahir’s recent works emphasize hybrid intelligence frameworks, machine learning-integrated decision systems, and quantum-resistant cryptography. He has presented his research at international conferences in Turkey, demonstrating his commitment to interdisciplinary collaboration and computational innovation. His scholarly contributions continue to advance soft computing, mathematical modeling, and intelligent decision-making for industrial and environmental applications.

Profiles : Scopus | Orcid

Featured Publications

Kamran, M., Zhang, Q., Pamucar, D., Tahir, M., & Simic, V. (2025). Enhancing confidence level in decision-making frameworks using Fermatean fuzzy rough sets: Application in Industry 4.0. Applied Soft Computing.

Tahir, M., Kfueit, K., Rasheed, M., Hanan, A., & Shahid, M. I. (2025, October 4). Pythagorean soft sets and hypersoft sets: A comprehensive framework for advanced uncertainty modeling in decision making. Spectrum of Decision Making and Applications.

Juan Chen | Mathematics | Best Researcher Award

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Assoc. Prof. Dr. Juan Chen | Mathematics | Best Researcher Award

Wuhan University of Science and Technology | China

Assoc. Prof. Dr. Juan Chen is a distinguished scholar in computational mathematics and complex network dynamics, currently serving at the College of Science, Wuhan University of Science and Technology. With a Ph.D. from Wuhan University, Dr. Chen has made significant contributions to nonlinear systems, synchronization, and complex network theory. Her prolific academic record includes 33 research documents, 432 citations, and an h-index of 13, reflecting her impact in the field. Dr. Chen’s works have appeared in leading journals such as IEEE Transactions on Network Science and Engineering, Chaos, Solitons and Fractals, and Expert Systems with Applications. She has authored influential books, including Synchronization of Complex Dynamical Networks, and contributed chapters to Springer handbooks. As a principal investigator and key collaborator on multiple National Natural Science Foundation of China projects, her research bridges mathematical theory and applied network science. Dr. Chen’s focus on synchronization, control, and robustness of complex networks highlights her pivotal role in advancing interdisciplinary computational research. Her dedication to exploring network behavior, information processing, and system dynamics positions her as an influential figure in contemporary applied mathematics and systems engineering.

Profiles : Scopus | Orcid

Featured Publications

Yin, L., Chen, J., Gao, F., & Wu, X. (2025). Coevolution of opinion and consumption behavior under a two-layer network framework. Physica A: Statistical Mechanics and its Applications, 680, 131020.

Yu, X., Tu, L., Chai, L., Wang, X., & Chen, J. (2024). Construction of implicit social network and recommendation between users and items via the ISR-RRM algorithm. Expert Systems with Applications, 235, 121229.

Chai, L., Tu, L., Yu, X., Wang, X., & Chen, J. (2023). Link prediction and its optimization based on low-rank representation of network structures. Expert Systems with Applications, 219, 119680.

Chai, L., Tu, L., Wang, X., & Chen, J. (2022). Network-energy-based predictability and link-corrected prediction in complex networks. Expert Systems with Applications, 207, 118005.

Shen, H., Tu, L., Guo, Y., & Chen, J. (2022). The influence of cross-platform and spread sources on emotional information spreading in the 2E-SIR two-layer network. Chaos, Solitons and Fractals, 165, 112801.

Chen, J., Li, X., Wu, X., & Shen, G. (2022). Prescribed-time synchronization of complex dynamical networks with and without time-varying delays. IEEE Transactions on Network Science and Engineering, 9, 4017–4027.

Zhang, P., Chen, J., Tu, L., & Yin, L. (2022). Layout evaluation of new energy vehicle charging stations: A perspective using the complex network robustness theory. World Electric Vehicle Journal, 13, 127.

Zhou, J., Chen, J., & Lu, J. (2017). On applicability of auxiliary system approach to detect generalized synchronization in complex networks. IEEE Transactions on Automatic Control, 62(7), 3468–3473.

Chen, J., Lu, J., & Zhou, J. (2013). Topology identification of complex networks from noisy time series using ROC curve analysis. Nonlinear Dynamics, 74, 1–8.

Zhang, Q., Chen, J., & Wan, L. (2013). Impulsive generalized function synchronization of complex dynamical networks. Physics Letters A, 377, 2754–2760.

Chen, J., Lu, J., Lu, X., Wu, X., & Chen, G. (2013). Spectral coarse graining of complex clustered networks. Communications in Nonlinear Science and Numerical Simulation, 18, 3036–3045.

Hassan Ramchoun | Mathematics | Best Researcher Award

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Dr. Hassan Ramchoun | Mathematics | Best Researcher Award

Moulay Ismail University | Morocco

Author Profile

Scopus

Early Academic Pursuits

Dr. Hassan Ramchoun’s academic journey reflects a strong foundation in mathematics and computer science. Beginning with his bachelor’s studies in applied mathematics, he progressively advanced through a master’s degree in operations research and statistics, where he explored Bayesian approaches in artificial neural networks for medical imaging. His doctoral research in applied mathematics and computer science further solidified his expertise, focusing on parameter and hyper-parameter estimation in Bayesian neural networks with applications in classification and regression. These early experiences shaped his specialization in applied mathematics, artificial intelligence, and machine learning.

Professional Endeavors

Dr. Ramchoun has built a diverse academic career with teaching, research, and leadership responsibilities. Since joining ENCG Meknès, Moulay Ismail University, as a lecturer, he has also taught at multiple institutions including ENSAM Meknès and the Euro-Mediterranean University of Fès. His teaching portfolio covers a wide spectrum, from probability and statistics to optimization, data analysis, and artificial intelligence. His active engagement in curriculum design, supervision of students, and participation in doctoral juries reflects his deep commitment to higher education and student mentorship.

Contributions and Research Focus

Dr. Ramchoun’s research focuses on applied mathematics, artificial intelligence, and data science, with particular emphasis on Bayesian neural networks, deep learning, optimization, and statistical learning methods. He has contributed to developing new methods for training and optimizing neural networks, incorporating regularization and Bayesian inference. His work extends to multi-objective optimization for neural architectures, convolutional neural networks, and applications in big data analytics. His scholarly contributions are reflected in numerous publications in international journals and conferences, alongside editorial contributions to Springer volumes on artificial intelligence and industrial applications.

Accolades and Recognition

Dr. Ramchoun’s academic excellence has been acknowledged through distinctions such as the CNRST excellence research scholarship and his recognition for doctoral work with high honors. His research output is regularly published in reputed international journals including Neurocomputing, Knowledge-Based Systems, Soft Computing, and Evolving Systems. His active involvement as a reviewer for leading journals and as a member of scientific committees of conferences demonstrates recognition of his expertise by the global scientific community.

Impact and Influence

Through his work, Dr. Ramchoun has significantly influenced both the academic and applied dimensions of artificial intelligence. His innovations in neural network optimization and Bayesian learning methods have advanced understanding in machine learning research, while his teaching and supervision of master’s and doctoral students have contributed to developing future generations of researchers. By bridging theoretical modeling with practical applications, his contributions have relevance not only in academia but also in applied domains such as data science, robotics, and image processing.

Legacy and Future Contributions

The legacy of Dr. Ramchoun lies in his efforts to advance the integration of applied mathematics with artificial intelligence, particularly in deep learning and Bayesian modeling. His involvement in research projects, scientific committees, and international conferences ensures that his contributions extend beyond publications to shaping the field itself. Looking forward, his continued work in optimization techniques, advanced statistical learning, and interdisciplinary applications promises to strengthen the role of artificial intelligence in addressing scientific and industrial challenges.

Publications

  • Article: Convergence of batch gradient descent with learnable smooth masks for pruning feedforward neural networks
    Authors: Quasdane, M., Ramchoun, H., Masrour, T.
    Journal: Neurocomputing
    Year: 2025

  • Article: Enhancing CNN structure and learning through NSGA-II-based multi-objective optimization
    Authors: Elghazi, Khalid, Ramchoun, Hassan, Masrour, Tawfik
    Journal: Evolving Systems
    Year: 2024

  • Article: Implicitly adaptive optimal proposal in variational inference for Bayesian learning
    Authors: Bakhouya, Mostafa, Ramchoun, Hassan, Hadda, Mohammed, et al.
    Journal: International Journal of Data Science and Analytics
    Year: 2024

  • Article: Gaussian Mixture Models for Training Bayesian Convolutional Neural Networks
    Authors: Bakhouya, M., Ramchoun, H., Hadda, M., Masrour, T.
    Journal: Evolutionary Intelligence (Springer)
    Year: 2024

  • Article: Sparse smooth group L0L1/2 regularization method for convolutional neural networks
    Authors: Quasdane, M., Ramchoun, H., Masrour, T.
    Journal: Knowledge-Based Systems
    Year: 2023

Conclusion

Dr. Hassan Ramchoun exemplifies the qualities of a dedicated academic, innovative researcher, and committed educator. His career reflects a balance of teaching excellence, impactful research, and institutional service. With strong foundations in mathematics and expertise in artificial intelligence, his contributions are shaping the evolving landscape of machine learning and data science. His recognition, publications, and leadership in academic communities confirm his standing as an influential figure whose work will continue to resonate in both research and applied domains.

Mehrtash Eskandaripour | Engineering | Best Researcher Award

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Dr. Mehrtash Eskandaripour | Engineering | Best Researcher Award

University of Isfahan | Iran

Author Profile

Scopus

🌊 Early Academic Pursuits

Dr. Mehrtash Eskandaripour embarked on his academic journey with a strong foundation in Civil Engineering, earning his Bachelor's degree from Islamic Azad University of Khomeynishahr. His passion for water resource management led him to pursue a Master's degree at Isfahan University of Technology, where he focused on designing Low Impact Development (LID) systems for urban runoff pollution control. Currently, as a Ph.D. candidate at the University of Isfahan, he is delving into the intricate dynamics of the Water-Energy NEXUS, applying advanced quantitative-qualitative modeling approaches to optimize water distribution networks.

🏗️ Professional Endeavors

Beyond academia, Dr. Eskandaripour has played a pivotal role in the engineering sector. As a civil engineering supervisor, he has overseen the structural integrity of over 50 buildings, ensuring sustainable and efficient construction practices. His leadership extends to the Iranian Organization for Building Engineering Codes, where he has managed an engineering department, fostering innovation and adherence to industry standards.

🔬 Contributions and Research Focus

With a research portfolio spanning water quality, climate change, drought management, and urban hydrology, Dr. Eskandaripour has significantly contributed to water sustainability. His studies on optimizing water distribution networks and mitigating urban runoff pollution through advanced simulation and optimization algorithms have provided actionable insights for urban planners and environmental policymakers. His work on the hidden threats of heavy metal leaching in urban environments highlights his commitment to ecological and public health risk assessment.

🏆 Accolades and Recognition

Dr. Eskandaripour’s dedication has been recognized through numerous prestigious awards. He has won multiple national and international congresses on civil engineering, urban planning, and environmental sustainability. His research excellence is reflected in publications in esteemed journals such as Heliyon, Urban Climate, and Environmental Research, further establishing his reputation as a thought leader in water resource management.

🌍 Impact and Influence

As an educator and mentor, Dr. Eskandaripour has contributed to shaping the next generation of engineers. His teaching experience at the University of Isfahan and Isfahan University of Technology has equipped students with expertise in water distribution network modeling and hydrology. His involvement in professional workshops and certification programs showcases his commitment to continuous learning and knowledge dissemination.

🔮 Legacy and Future Contributions

With a vision to revolutionize water sustainability, Dr. Eskandaripour continues to push the boundaries of research in water-energy interactions, smart urban water systems, and risk mitigation strategies. His future contributions promise to advance sustainable water management solutions, addressing global challenges such as climate change, resource scarcity, and environmental resilience.

 

Publications

📝 Maximizing Efficiency and Performance of Water Distribution Systems through the Implementation of Optimization Algorithms: A Comprehensive Analysis of Valve and Chlorine Booster Placement and Management
✍️ Authors: Najarzadegan, M., Eskandaripour, M.
📖 Journal: Heliyon
📆 Year: 2025

📝 Optimal Low-Impact Development Facility Design in Urban Environments: A Multidimensional Optimization Approach Employing Slime Mould and Nondominated Sorting Genetic Algorithms
Authors: Eskandaripour, M., Soltaninia, S.
Journal: Urban Climate
Year: 2024

📝 The Hidden Threat of Heavy Metal Leaching in Urban Runoff: Investigating the Long-Term Consequences of Land Use Changes on Human Health Risk Exposure
Authors: Soltaninia, S., Eskandaripour, M., Ahmadi, Z., Ahmadi, S., Eslamian, S.
Journal: Environmental Research
Year: 2024

📝  Optimization of Low-Impact Development Facilities in Urban Areas Using Slime Mould Algorithm
Authors: Eskandaripour, M., Golmohammadi, M. H., & Soltaninia, S.
Journal: Sustainable Cities and Society
Year: 2023

📝 Analyzing Drought Duration Frequency and Severity Using Copula Function in the Yazd City
Authors: Eskandaripour, M., Soltaninia, S.
Journal: Journal of Water and Climate Change
Year: 2022

 

Mohammad Mahdavian | Materials Science | Best Researcher Award

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Prof. Mohammad Mahdavian | Materials Science | Best Researcher Award

Institute for Color Science and Technology | Iran

Author Profile

Scopus

Orcid

🎓 Early Academic Pursuits

Prof. Mohammad Mahdavian embarked on his academic journey with a passion for polymer engineering. He earned his Bachelor's, Master's, and Ph.D. from Amirkabir University of Technology, consistently excelling in his studies. His Ph.D. research focused on evaluating azole derivatives as corrosion inhibitors, positioning him as a pioneer in chromate-free protective coatings. His academic excellence was evident in his top-ranking performance, with an impressive GPA of 3.94 in both his postgraduate degrees.

💼 Professional Endeavors

With a career spanning academia and industry, Prof. Mahdavian has played a crucial role in advancing polymer coatings and corrosion protection. He currently serves as a Professor at the Institute for Color Science and Technology (ICST), leading the Surface Coatings and Corrosion Department. His previous roles include Assistant and Associate Professorships at ICST and Sahand University of Technology, along with leadership roles in postgraduate education and international scientific collaborations. Parallel to his academic career, he has contributed to industrial innovation as a Coating Scientist at Atlas Protecting Coating (APC) and R&D Deputy at Khosh Paint Company (KPC).

🔬 Contributions and Research Focus

Prof. Mahdavian’s research is at the forefront of material science, specializing in nano-particles, polymer and silane coatings, conversion coatings, and corrosion-resistant technologies. His expertise extends to electrochemistry, metal-organic frameworks (MOFs), and layered double hydroxides (LDHs). His prolific contributions include over 200 scientific papers in esteemed international journals, solidifying his reputation as a thought leader in protective coatings. His innovative approach has led to multiple patents, including hybrid organic-inorganic corrosion inhibitors and nanocomposite coatings.

🏆 Accolades and Recognition

Prof. Mahdavian's outstanding contributions to material science have earned him widespread recognition. He has been ranked among the top 2% of scientists globally by Elsevier BV and Stanford University and acknowledged as a top reviewer by Web of Science. His research excellence has been further honored by prestigious awards, including the Distinguished Paper Award from the American Cleaning Institute and the Preeminent Scientist Award from the National Science Foundation of Iran. Additionally, he has been recognized as an Outstanding Researcher by the Ministry of Science and Technology.

🌍 Impact and Influence

Beyond research, Prof. Mahdavian has made a profound impact through mentorship and leadership. He has guided numerous MSc and Ph.D. students, fostering innovation in corrosion protection. As the Head of International Scientific Cooperation at ICST, he has facilitated global research collaborations, further amplifying his influence in the field. His teaching expertise spans various advanced subjects, including corrosion engineering, polymer coatings, and chemical reactor design, shaping the next generation of engineers and researchers.

🚀 Legacy and Future Contributions

Prof. Mahdavian’s contributions to polymer engineering and protective coatings continue to shape the future of corrosion-resistant materials. His ongoing research projects, including anti-icing coatings for wind turbines and graphene-based composite coatings, highlight his commitment to industrial innovation and sustainability. With a legacy of scientific excellence, mentorship, and groundbreaking research, he remains a visionary leader poised to drive further advancements in material science and engineering.

 

Publications

📖 Unlocking the Potential of FTIR for Corrosion Inhibition Prediction Exploiting Principal Component Analysis: Machine Learning for QSPR Modeling
Journal: Journal of the Taiwan Institute of Chemical Engineers
Year: 2025
Authors: A. Sadeghi, M. Shariatmadar, S. Amoozadeh, A. Mahmoudi Nahavandi, M. Mahdavian

📖N-Doped-GO@Zn Nano-Layers Filled Epoxy Composite with Superior Mechanical and Anti-Corrosion Properties
Journal: Colloids and Surfaces A: Physicochemical and Engineering Aspects
Year: 2024
Authors: Motahhare Keramatinia, Bahram Ramezanzadeh, Mohammad Mahdavian

📖Adiantum Capillus-Veneris Extract as a Sustainable Inhibitor to Mitigate Corrosion in Acid Solutions: Experimental, Machine-Learning Simulation, and Multiobjective Optimization
Journal: Langmuir
Year: 2024
Authors: Mahya Olfatmiri, Mohammad-Bagher Gholivand, Mohammad Mahdavian, Alireza Mahmoudi Nahavandi

📖 Falcaria vulgaris Leaves Extract as an Eco-Friendly Corrosion Inhibitor for Mild Steel in Hydrochloric Acid Media
Journal: Scientific Reports
Year: 2023
Authors: Mohammadreza Alimohammadi, Mohammad Ghaderi, S. A. Ahmad Ramazani, Mohammad Mahdavian

📖 Assessment of Synthesis Conditions on the Corrosion Inhibitive Features of ZIF-67 MOF
Journal: Surface and Coatings Technology
Year: 2023
Authors: D. Aliyari, M. Mahdavian, B. Ramezanzadeh

 

Caiming Zhang | Decision Sciences | Best Researcher Award

Published on by Book of Award

Prof. Caiming Zhang | Decision Sciences | Best Researcher Award

China University of Labor Relations | China

Author profile

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🌱 Early Academic Pursuits

Prof. Caiming Zhang's educational journey showcases his steadfast dedication to Industrial Economics and Management. He began with a Bachelor of Engineering from Nanchang University in 1998, followed by a Master of Management from Beijing University of Technology in 2001. His academic ambition culminated in a Ph.D. in Industrial Economics from Beijing Jiaotong University in 2008. These formative years laid the foundation for his future contributions to academia and industry.

🏛️ Professional Endeavors

Prof. Zhang's career trajectory reflects a seamless integration of academic leadership and industry innovation. As the Dean of the School of Labor Relations and Human Resources at China University of Labor Relations, he continues to guide the next generation of thinkers. His prior roles as Vice Dean and Director within the same institution underscore his impactful leadership. Beyond academia, Prof. Zhang is the Founder and President of Beijing Dimensional Insight Inc., a hub for cutting-edge research in big data and business intelligence, showcasing his entrepreneurial spirit and technical expertise.

🔬 Contributions and Research Focus

Prof. Zhang’s research encompasses pivotal areas such as big data, artificial intelligence, and Industry 4.0. His work has been recognized globally through publications in esteemed journals like Journal of Industrial Information Integration and Information Systems Frontiers. His patents, including innovative methods for big data analysis, highlight his contributions to technological advancement. Furthermore, his hosting of national research projects and development of big data systems for institutions like Beijing Metro Commission and Hebei Hospitals reflect his commitment to practical applications of research.

🏅 Accolades and Recognition

Prof. Zhang’s contributions have earned numerous accolades. Among them are awards for groundbreaking research in artificial intelligence and educational excellence. His paper on AI prospects won the Third Award at the 16th Scientific Research Achievements in China University of Labor Relations. He has also been recognized for innovative curriculum design, securing prestigious teaching awards. As a Senior Member of IEEE and the Chinese Society of Technology Economics, his influence extends across academic and professional spheres.

🌍 Impact and Influence

As a visiting scholar at Old Dominion University and a sought-after speaker at international conferences, Prof. Zhang has brought Chinese academic insights to the global stage. His research on topics like the economic impact of AI and blockchain technology not only advances knowledge but also addresses contemporary industry challenges. Through his mentorship of graduate students and leadership in research, he has shaped the academic and professional paths of countless individuals.

🌟 Legacy and Future Contributions

Prof. Zhang's enduring legacy lies in his ability to bridge the gap between theory and practice. His work in advancing big data applications, combined with his passion for education and innovation, promises a future where technology continues to drive societal progress. As he leads projects on intelligent education and big data decision-making, Prof. Zhang remains a beacon of inspiration, paving the way for breakthroughs in both academia and industry.

 

Publications

📝 The Impact of Generative AI on Management Innovation

  • Author: Zhang, C., Zhang, H.
  • Journal: Journal of Industrial Information Integration
  • Year: 2025

📝 A Dynamic Attributes-driven Graph Attention Network Modeling on Behavioral Finance for Stock Prediction

  • Author: Zhang, Q., Zhang, Y., Yao, X., Zhang, C., Liu, P.
  • Journal: ACM Transactions on Knowledge Discovery from Data
  • Year: 2023

📝 Acquisition and Cognition Information of Human Body Swing

  • Author: Fan, J.-F., Sigov, A., Ratkin, L., Chen, S.-W., Zhang, C.-M.
  • Journal: Journal of Industrial Information Integration
  • Year: 2022

📝 A Literature Review of Social Commerce Research from a Systems Thinking Perspective

  • Author: Wang, X., Wang, H., Zhang, C.
  • Journal: Systems
  • Year: 2022

📝 Study on the Interaction Between Big Data and Artificial Intelligence

  • Author: Li, J., Ye, Z., Zhang, C.
  • Journal: Systems Research and Behavioral Science
  • Year: 2022