Prof. Sedaghat Shahmorad 🎓, a distinguished scholar in Applied Mathematics at the University of Tabriz 🇮🇷, specializes in numerical analysis, particularly integro-differential equations. With over two decades of academic experience 🧠, he has significantly contributed to the field through extensive teaching, research, and leadership. He has supervised numerous M.Sc. and Ph.D. theses 🎓📚 and authored multiple scholarly books and impactful journal articles 📖📝. His work on the Tau method and approximation techniques has earned recognition in computational mathematics 🧮. As Head of the Applied Mathematics Department and former Dean, he has demonstrated strong administrative and academic leadership 👨🏫📊. Prof. Shahmorad’s dedication to advancing numerical methods and mentoring future mathematicians makes him a highly deserving candidate for the Best Researcher Award 🏆🔬.
Professional Profile
Education 🎓📘
Prof. Sedaghat Shahmorad earned his B.Sc. in Applied Mathematics from the University of Tabriz 🇮🇷, followed by an M.Sc. and Ph.D. in Numerical Analysis from the same institution. His academic journey has been marked by excellence in mathematical modeling and computational theory 📊. With a solid foundation in numerical methods and integro-differential equations, he developed deep expertise in solving complex mathematical problems 💡. Throughout his academic training, Prof. Shahmorad received high honors, standing out for his analytical acumen and innovation 🧠. His commitment to lifelong learning and scholarly development has shaped a distinguished academic and research career, reinforcing his role as a leading expert in numerical mathematics 📐🔍.
Professional Experience 👨🏫🏢
Prof. Shahmorad brings over two decades of academic and leadership experience in Applied Mathematics at the University of Tabriz 🎓. He has served as the Head of the Department of Applied Mathematics and formerly as the Dean of the Faculty of Mathematical Sciences 🏛️. In addition to his teaching duties, he has led multiple research projects, supervised numerous postgraduate students, and contributed to curriculum development 📚. His strong leadership and mentorship have made a lasting impact on the academic community 👥. He has also participated in editorial boards, conferences, and international collaborations 🌐. His professional trajectory reflects his deep commitment to both teaching and research excellence, making him a vital contributor to the advancement of numerical mathematics 🔬📈.
Research Interest 🔍📐
Prof. Shahmorad’s research focuses on numerical analysis, especially the development of efficient methods for solving integro-differential and delay differential equations 🔢. He is renowned for his work on Tau methods, spectral techniques, and high-order approximation algorithms, which have broad applications in engineering, physics, and applied sciences ⚙️🌌. His studies aim to bridge theoretical rigor with computational feasibility, providing tools for real-world problem-solving 💻📊. He also explores fractional calculus, integral transforms, and mathematical modeling of dynamic systems. His interdisciplinary research contributes significantly to advancing both applied and pure mathematical domains 📘🧪. Prof. Shahmorad’s innovative methodologies continue to influence emerging trends in computational mathematics and inspire the next generation of researchers around the globe 🌍.
Award and Honor 🏆🎖️
Prof. Sedaghat Shahmorad has received multiple awards and honors recognizing his academic excellence, innovative research, and outstanding mentorship 🏅📚. Notably, he has been acknowledged as a Top Researcher at the University of Tabriz and by national science organizations in Iran 🇮🇷. His contributions to numerical mathematics, especially in solving integro-differential equations, have earned accolades from peer-reviewed journals and international conference bodies 🧾🌟. He has also received honors for excellence in teaching and student supervision, highlighting his role as a mentor par excellence 👨🏫🌱. These awards are a testament to his impactful research output, dedication to knowledge dissemination, and continued service to the academic community 🎓🧠.
Research Skill 🧠💻
Prof. Shahmorad possesses advanced skills in mathematical modeling, numerical simulations, and algorithm development. He is proficient in implementing spectral and collocation methods, particularly the Tau method, to tackle complex integro-differential systems with precision 🔢📈. His expertise extends to fractional differential equations, delay systems, and applied analysis using computational tools like MATLAB and Mathematica 🖥️⚙️. With a strong command over linear algebra, integral transforms, and functional analysis, he develops robust algorithms that are widely cited and applied in science and engineering 🔍📚. His problem-solving approach blends theoretical insight with computational strategy, fostering innovation and practical applications in numerical mathematics 📘🚀.
Publications Top Note 📝
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Title: Solving a class of auto-convolution Volterra integral equations via differential transform method
Authors: Sedaghat Shahmorad, et al.
Year: 2025
Source: Journal of Mathematical Modeling
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Title: Approximate solution of multi-term fractional differential equations via a block-by-block method
Authors: Sedaghat Shahmorad, et al.
Year: 2025
Citations: 1
Source: Journal of Computational and Applied Mathematics
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Title: Convergence analysis of Jacobi spectral tau-collocation method in solving a system of weakly singular Volterra integral equations
Authors: Sedaghat Shahmorad, et al.
Year: 2024
Citations: 1
Source: Mathematics and Computers in Simulation
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Title: Theoretical and numerical analysis of a first-kind linear Volterra functional integral equation with weakly singular kernel and vanishing delay
Authors: Sedaghat Shahmorad, et al.
Year: 2024
Citations: 1
Source: Numerical Algorithms
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Title: Double weakly singular kernels in stochastic Volterra integral equations with application to the rough Heston model
Authors: Sedaghat Shahmorad, et al.
Year: 2024
Source: Applied Mathematics and Computation
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Title: Existence, uniqueness and blow-up of solutions for generalized auto-convolution Volterra integral equations
Authors: Sedaghat Shahmorad, et al.
Year: 2024
Source: Applied Mathematics and Computation
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Title: The application of fuzzy transform method to the initial value problems of linear differential–algebraic equations
Authors: Sedaghat Shahmorad, et al.
Year: 2024
Source: Mathematical Sciences
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Title: Solving fractional differential equations using cubic Hermit spline functions
Authors: Sedaghat Shahmorad, et al.
Year: 2024
Source: Filomat (Open Access)
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Title: Solving 2D-integro-differential problems with nonlocal boundary conditions via a matrix formulated approach
Authors: Sedaghat Shahmorad, et al.
Year: 2023
Citations: 1
Source: Mathematics and Computers in Simulation
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Title: Review of recursive and operational approaches of the Tau method with a new extension
Authors: Sedaghat Shahmorad, et al.
Year: 2023
Source: Computational and Applied Mathematics
Conclusion ✨📜
Prof. Sedaghat Shahmorad stands as a prominent figure in numerical analysis, combining deep theoretical knowledge with computational expertise 🌐📊. His dedication to teaching, mentoring, and advancing numerical methodologies has significantly shaped the field and inspired scholars across disciplines 🧠🎓. With a rich portfolio of research, leadership roles, and academic honors, he exemplifies excellence in mathematics and its real-world applications 🧾🏅. His work not only contributes to scientific understanding but also provides tools for innovation across technology and engineering sectors 🧬⚙️. As a visionary academic and skilled researcher, Prof. Shahmorad continues to influence future directions in computational and applied mathematics with distinction 🌟📘.