Miraxmat Mirsaburov | Mathematics | Excellence in Research Award

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Mr. Miraxmat Mirsaburov | Mathematics | Excellence in Research Award

Termez State University | Uzbekistan

Mr. Miraxmat Mirsaburov is a mathematician whose research focuses on boundary-value and nonlocal problems for mixed-type and degenerate hyperbolic equations, with particular emphasis on singular coefficients, transmission conditions, and characteristic-based constraints. Across a corpus of 41 documents, his work—which has accrued 81 citations  yields an h-index of 5—systematically develops existence, uniqueness, and formulation results for classes of Gellerstedt-, Tricomi- and Bitsadze–Samarskii–type problems, addressing challenges such as missing Goursat or shift conditions, Frankl and Bitsadze–Samarskii analogues on degeneration segments, and problems posed in unbounded domains. His publications combine rigorous analytical techniques with careful handling of singularities and degeneracy lines, producing solvability theorems and novel transmission conditions that extend classical theory to more physically and geometrically complex settings. Collaborative work with colleagues has produced advances in generalizing the Tricomi problem, treating singular coefficients, and proposing integral and boundary frameworks adaptable to mixed elliptic–hyperbolic regimes. Mirsaburov’s contributions appear in respected journals (including Russian Mathematical Surveys, Differential Equations, and Lobachevskii Journal of Mathematics), and his sustained focus on mixed-type equations has provided useful tools and formulations for researchers addressing applied problems where equation type and coefficient singularities complicate classical approaches.

Profile : Scopus

Featured Publications

Mirsaburov, M., & Mamatmuminov, D. T. (2025). A problem with an analogue of the Bitsadze–Samarskii condition on the segment of degeneracy and an internal segment parallel to it in the domain for a certain class of degenerate hyperbolic equations. Russian Mathematics, 69, 19–23.

Mirsaburov, M., & Turaev, R. N. (2024). On a nonlocal problem for the Gellerstedt equation with singular coefficients. Differential Equations, 60, 1074–1086.

Mirsaburov, M. M., & Allakova, S. I. (2024). An analogue of the Zhegalov problem with data on internal characteristics for a mixed-type equation with a singular coefficient. Lobachevskii Journal of Mathematics, 45, 5637–5648.

Mirsaburov, M., Berdyshev, A. S., Ergasheva, S. B., & Makulbay, A. B. (2024). The problem with the missing Goursat condition at the boundary of the domain for a degenerate hyperbolic equation with a singular coefficient. Bulletin of the Karaganda University: Mathematics Series, 2(114), 147–164.

Mirsaburov, M., & Turaev, R. N. (2023). A problem in an unbounded domain with combined Tricomi and Frankl conditions on one boundary characteristic for one class of mixed-type equations. Russian Mathematics, 67, 34–46.

Mirsaburov, M., & Ergasheva, S. B. (2023). The problem in the unbounded domain with the Frankl condition on the segment of the degeneration line and with a missing Gellerstedt condition for a class of mixed-type equations. Russian Mathematics, 67, 18–26.

Mirsaburov, M., & Khurramov, N. K. (2021). A problem with local and nonlocal conditions on the boundary of the ellipticity domain for a mixed-type equation. Russian Mathematics, 65, 68–81.

V., M., & Islomov, N. B. (2021). Problem with a Bitsadze–Samarskii condition on parallel characteristics for a mixed-type equation of the second kind. Differential Equations, 57, 1358–1371.

Mirsaburov, M., Begaliev, O., & Khurramov, N. K. (2019). Generalization of the Tricomi problem. Differential Equations, 55, 1084–1093.

Mirsaburov, M., & Khurramov, N. (2020). A problem with the Bitsadze–Samarskii condition on the characteristics of one family and with general transmission conditions on the degeneration line for the Gellerstedt equation with a singular coefficient. Differential Equations, 56, 1050–1071.

Mirsaburov, M. (2018). The problem with missing shift condition for the Gellerstedt equation with a singular coefficient. Russian Mathematics, 62, 44–54.

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.

Vasil Angelov | Mathematics | Best Researcher Award

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Prof. Dr. Vasil Angelov | Mathematics | Best Researcher Award

University of Mining and Geology St. Ivan Rilski | Bulgaria

Prof. Dr. Vasil Angelov is a distinguished mathematician and researcher with an h-index of 11, 151 articles with 562 citations, reflecting his significant contributions to mathematics and applied sciences. He earned his PhD in Mathematics, followed by an Associate Professorship, Doctor of Sciences, and Full Professorship. He served as Chair of the Department of Mathematics at the University of Mining & Geology “St. I. Rilski,” Bulgaria, and as Deputy Rector before retiring. Prof. Angelov’s research focuses on delay differential equations, fixed point theory, classical electrodynamics, transmission lines, and nonlinear circuits, with over 150 research papers published. He authored notable monographs including Fixed Points in Uniform Spaces and Applications and A Method for Analysis of Transmission Lines Terminated by Nonlinear Loads. His work on periodic solutions of the 4-body electromagnetic problem and its application to the Li atom demonstrates his expertise in mathematical modeling of complex physical systems. Prof. Angelov has been widely recognized for his contributions, receiving awards such as Who’s Who in the World, Gold Medal of the American Biographical Institute, International Peace Prize, Scientist of the Year honors, and recognition from international research centers, highlighting his global impact in mathematics, physics, and applied sciences.

Profiles : Scopus | Google Scholar

Featured Publications

Angelov, V. G. (2025). Periodic solutions of the 4-body electromagnetic problem and application to Li atom. AppliedMath, 5(3), 112.

Angelov, V. (2025). Energy estimation of the moving particles in 2-body and 3-body problem of classical electrodynamics. Science Set Journal of Physics.

Angelov, V. G. (2024, December 25). Spin 3-body problem of classical electrodynamics in the 3D-Kepler form.

Angelov, V. G. (2024, August 21). Energy of the moving particles in 3-body problem of classical electrodynamics. Preprints.

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.

Sergio Manzetti | Mathematics | Best Researcher Award

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Dr. Sergio Manzetti | Mathematics | Best Researcher Award

Linnaeus University | France

Dr. Sergio Manzetti is a distinguished researcher whose interdisciplinary work bridges mathematics, quantum information theory, and nanotechnology. With an h-index of 26, 4,946 citations, and numerous scholarly documents, his research demonstrates both depth and global impact. His expertise spans mathematical analysis, Fourier analysis of partial differential equations (PDEs), quantum chemistry, computational systems, and nonlinear dynamics, contributing significantly to the understanding of quantum systems and wave phenomena. Dr. Manzetti’s academic foundation includes advanced degrees from Uppsala University, Linnaeus University, Queensland University of Technology, and Oslo University College, where he specialized in the mathematical and physical sciences. His professional experience is equally impressive—serving as an EU expert for Marie-Curie Fellowships, AI prompt reviewer at Mercor Intelligence, and researcher at Fjord-Research AS. He has co-authored influential publications in Analysis and Mathematical Physics, Advanced Theory and Simulations, and RSC Advances, addressing topics from eigenvalue problems of non-self-adjoint operators to supersymmetric wave equations and nanomaterial design. Skilled in Python, Mathematica, and MATLAB, Dr. Manzetti combines theoretical rigor with computational precision. His contributions to quantum information systems, rogue wave modeling, and nanotechnology continue to advance interdisciplinary research, positioning him as a leading figure in applied mathematics and theoretical chemistry.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Manzetti, S., & Khrennikov, A. (2025, September 28). Quantum and topological dynamics of GKSL equation in camel-like framework. Entropy.

Manzetti, S. (2025, September 22). Geometric formalism for quantum entanglement via B³ and S⁰ mappings. Preprint.

Manzetti, S., & Khrennikov, A. (2025, July 11). Quantum and topological dynamics of the GKSL equation in the camel-like framework. Preprint.

Kumar, R., Hiremath, K. R., & Manzetti, S. (2024, April). A primer on eigenvalue problems of non-self-adjoint operators. Analysis and Mathematical Physics.

Manzetti, S. (2021). Spectral properties of non-self adjoint operators: A review of the recent literature. Unpublished manuscript.

Kamerlin, N., Delcey, M. G., Manzetti, S., & van der Spoel, D. (2020, August 24). Toward a computational ecotoxicity assay. Journal of Chemical Information and Modeling.

Manzetti, S., & Trounev, A. (2020, January). Analytical solutions for a supersymmetric wave-equation for quasiparticles in a quantum system. Advanced Theory and Simulations.

Manzetti, S. (2020, January). Electromagnetic vorticity in a square-well crystal system described by a supersymmetric wave-equation. Advanced Theory and Simulations.

Ghisi, R., Vamerali, T., & Manzetti, S. (2019). Accumulation of perfluorinated alkyl substances (PFAS) in agricultural plants: A review. Environmental Research.

van der Spoel, D., Manzetti, S., Zhang, H., & Klamt, A. (2019, August 27). Prediction of partition coefficients of environmental toxins using computational chemistry methods. ACS Omega.

Manzetti, S., & Gabriel, J.-C. P. (2019, March 2). Methods for dispersing carbon nanotubes for nanotechnology applications: Liquid nanocrystals, suspensions, polyelectrolytes, colloids and organization control. International Nano Letters.

Manzetti, S., & Trounev, A. (2019, May). Supersymmetric Hamiltonian and vortex formation model in a quantum nonlinear system in an inhomogeneous electromagnetic field. Advanced Theory and Simulations.

Behzadi, H., Manzetti, S., Dargahi, M., Roonasi, P., & Khalilnia, Z. (2018). Application of calculated NMR parameters, aromaticity indices and wavefunction properties for evaluation of corrosion inhibition efficiency of pyrazine inhibitors. Journal of Molecular Structure.

Manzetti, S. (2018). Applied quantum physics for novel quantum computation approaches: An update. Computational Mathematics and Modeling.

Manzetti, S. (2018). Mathematical modeling of rogue waves, a review of conventional and emerging mathematical methods and solutions. Preprint.

Manzetti, S. (2018, November 8). Derivation and numerical analysis of an attenuation operator for non-relativistic waves. Scientific Reports.

Manzetti, S., & Lu, T. (2018, August 20). Addendum: Solvation energies of butylparaben, benzo[a]pyrene diol epoxide, perfluorooctanesulfonic acid, and DEHP in complex with DNA bases. Chemical Research in Toxicology.

Manzetti, S. (2018, June 20). Mathematical modeling of rogue waves: A survey of recent and emerging mathematical methods and solutions. Axioms.

Gwo Dong Lin | Mathematics | Excellence in Research Award

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Prof. Gwo Dong Lin | Mathematics | Excellence in Research Award

Academia Sinica, Institute of Statistical Science | Taiwan

Prof. Gwo Dong Lin is a distinguished statistician and mathematician whose extensive contributions have profoundly influenced the fields of probability theory, moment problems, and life distribution analysis. With an h-index of 18, 71 published documents, and 933 citations from 783 sources, his scholarly output demonstrates both depth and enduring impact. He earned his Ph.D. in Management Science from Tamkang University, following earlier degrees in mathematics from National Taiwan Normal University. Over his career, Prof. Lin served at Academia Sinica’s Institute of Statistical Science, including roles as Deputy Director and Acting Director, and later as Adjunct Research Fellow. He has also directed the Social and Data Science Research Center under the Hwa-Kang Xing-Ye Foundation. His editorial work spans several international journals, and he has been an invited speaker at global conferences organized by the International Statistical Institute and other leading organizations. Recognized as an ISI Elected Member since 1991 and recipient of Taiwan’s Outstanding Research Award (1994–1995), Prof. Lin’s pioneering studies on characterizations of distributions, inequalities for transforms, and moment determinacy continue to shape modern statistical theory and inspire future explorations in applied probability and statistical modeling.

Profile : Scopus

Featured Publications 

Lin, G. D., & Stoyanov, J. (2025). New sufficient conditions for moment-determinacy via probability density tails. Mathematics, 13, 2671.

Dou, X., Kuriki, S., Lin, G. D., & Richards, D. (2025). EM estimation of the B-spline copula with penalized pseudo-likelihood functions. Statistical Papers, 66, 30.

Lin, G. D., & Stoyanov, J. (2024). New characterizations of the Gamma distribution via independence of two statistics by using Anosov’s theorem. Theory of Probability and Its Applications, 69, 745–759 (Russian edition); SIAM version, 69, 592–604.

Hu, C.-Y., & Lin, G. D. (2022). Characterizations of the normal distribution via the independence of the sample mean and the feasible definite statistics with ordered arguments. Annals of the Institute of Statistical Mathematics, 74, 473–488.

Lin, G. D., & Hu, C.-Y. (2022). On the semi-Mittag-Leffler distributions. Probability and Mathematical Statistics, 42, 81–96.

Hu, C.-Y., Lin, G. D., & Stoyanov, J. (2021). Characterization of probability distributions via functional equations of power-mixture type. Mathematics, 9, 271. Also in: L. Shaikhet (Ed.), Prime Archives in Applied Mathematics (2nd ed.). Hyderabad, India: Vide Leaf.

Lin, G. D., & Dou, X. (2021). An identity for two integral transforms applied to the uniqueness of a distribution via its Laplace–Stieltjes transform. Statistics, 55, 365–385.

Dou, X., Kuriki, S., Lin, G. D., & Richards, D. (2021). Dependence structures of B-spline copulas. Sankhyā: The Indian Journal of Statistics, Series A, 83, 238–311.

Lin, G. D., & Hu, C.-Y. (2021). Formulas of absolute moments. Sankhyā: The Indian Journal of Statistics, Series A, 83, 476–495.

Hu, C.-Y., & Lin, G. D. (2020). Necessary and sufficient conditions for unique solution to functional equations of Poincaré type. Journal of Mathematical Analysis and Applications, 491, 124399.

Stoyanov, J. M., Lin, G. D., & Kopanov, P. (2020). New checkable conditions for moment determinacy of probability distributions. Theory of Probability and Its Applications, 65, 634–648 (Russian edition); SIAM version, 65, 497–509.

Lin, G. D., Dou, X., & Kuriki, S. (2019). The bivariate lack-of-memory distributions. Sankhyā: The Indian Journal of Statistics, Series A, 81, 273–297.

Lin, G. D. (2019). On powers of the Catalan number sequence. Discrete Mathematics, 342, 2139–2147.

Hu, C.-Y., & Lin, G. D. (2018). Characterizations of the logistic and related distributions. Journal of Mathematical Analysis and Applications, 463, 79–92.

Lin, G. D. (2017). Recent developments on the moment problem. Journal of Statistical Distributions and Applications, 4, 5.

Lai, C.-D., Lin, G. D., Govindaraju, K., & Pirikahu, S. (2017). A simulation study on the correlation structure of Marshall–Olkin bivariate Weibull distribution. Journal of Statistical Computation and Simulation, 87, 156–170.

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.

Seyedeh Azadeh Fallah Mortezanejad | Mathematics | Best Researcher Award

Published on by Book of Award

Dr. Seyedeh Azadeh Fallah Mortezanejad | Mathematics | Best Researcher Award

Jiangsu University | China

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Early Academic Pursuits

Dr. Seyedeh Azadeh Fallah Mortezanejad began her academic journey with a strong foundation in statistics, completing her undergraduate and postgraduate studies at Guilan University, Iran. Her master’s research on semi-parametric estimation of conditional copula reflected her interest in statistical theory and dependence structures. She advanced her academic training with doctoral research at Ferdowsi University of Mashhad, focusing on applications of entropy in statistical quality control, which laid the groundwork for her later interdisciplinary research.

Professional Endeavors

Following her doctoral studies, Dr. Mortezanejad pursued postdoctoral research at Jiangsu University in China, under the guidance of Professor Ruochen Wang. Supported by the National Natural Science Foundation of China, her work explored advanced applications of statistical inference in engineering systems. Her professional engagements span teaching, collaborative research, and presenting at international conferences, reflecting her role as both a researcher and an academic contributor.

Contributions and Research Focus

Her research lies at the intersection of statistics, data science, and engineering. She has significantly contributed to areas such as time series analysis, dependence data, deep learning, and statistical quality control. Her expertise in copula functions and entropy has enabled novel methods for addressing challenges in multivariate data analysis and control charts. More recently, her work integrates machine learning and physics-informed neural networks for solving complex problems in multivariate time series and image processing.

Accolades and Recognition

Dr. Mortezanejad’s scholarly contributions have been recognized through numerous publications in leading journals, including Entropy, Sankhya B, and Physica A. She has been invited to present her findings at international workshops in Germany, France, Vietnam, and Spain, underscoring her recognition in global research communities. Her role as a reviewer for reputed journals and conferences further reflects her professional standing in the field.

Impact and Influence

Through her interdisciplinary research, Dr. Mortezanejad has bridged the gap between theoretical statistics and practical applications in fields such as healthcare, engineering, and financial modeling. Her contributions to statistical quality control, machine learning applications, and Bayesian inference have influenced both academic discourse and applied research, making her work relevant across diverse scientific domains.

Legacy and Future Contributions

With her strong background in both theoretical and applied statistics, Dr. Mortezanejad is poised to continue advancing research in modern statistical methods, particularly in integrating entropy-based approaches with machine learning. Her future work is expected to focus on enhancing predictive analytics, developing robust statistical tools for big data, and contributing to sustainable innovations in engineering and healthcare.

Publications

Article: Physics-Informed Neural Networks with Unknown Partial Differential Equations: An Application in Multivariate Time Series
Authors: Seyedeh Azadeh Fallah Mortezanejad, Ruochen Wang, Ali Mohammad-Djafari
Journal: Entropy
Year: 2025

Article: Variational Bayesian Approximation (VBA): Implementation and Comparison of Different Optimization Algorithms
Authors: Seyedeh Azadeh Fallah Mortezanejad, Ali Mohammad-Djafari
Journal: Entropy
Year: 2024

Article: Variational Bayesian Approximation (VBA) with Exponential Families and Covariance Estimation
Authors: Seyedeh Azadeh Fallah Mortezanejad, Ali Mohammad-Djafari
Journal: Physical Sciences Forum
Year: 2023

Article: Variational Bayesian Approximation (VBA): A Comparison between Three Optimization Algorithms
Authors: Seyedeh Azadeh Fallah Mortezanejad, Ali Mohammad-Djafari
Journal/Conference: MaxEnt 2022 (Conference Proceedings)
Year: 2023

Article: Evaluation of Anti-lice Topical Lotion of Ozonated Olive Oil and Comparison of its Effect with Permethrin Shampoo
Authors: Omid Rajabi, Atoosa Haghighizadeh, Seyedeh Azadeh Fallah Mortezanejad, Saba Dadpour
Journal: Reviews on Recent Clinical Trials
Year: 2022

Conclusion

Dr. Seyedeh Azadeh Fallah Mortezanejad’s career reflects a rare blend of statistical rigor, innovative application, and international recognition. Her early commitment to statistical theory, coupled with her interdisciplinary contributions, has positioned her as a rising figure in applied statistics and data science. With her expanding research footprint, she is set to leave a lasting impact on statistical research and its applications in science, technology, and industry.