Ph.D at Shahid Beheshti University, Iran
Hojjatollah Shokri Kaveh is an accomplished PhD candidate in Applied Mathematics at Shahid Beheshti University, Tehran, recognized for his advanced research in numerical linear algebra, inverse problems, and iterative algorithms. With a passion for mathematical problem-solving and algorithm development, he has published over ten scientific papers in prestigious international journals, often in collaboration with globally respected researchers. His academic excellence is underscored by ranking 2nd in Iran’s national doctoral entrance exam and maintaining a high GPA of 19.2/20 during his PhD studies. In addition to his research endeavors, he has contributed significantly to education through years of teaching experience across institutions and online platforms. His strong programming skills in MATLAB, Python, and C complement his theoretical work, enabling robust computational solutions. Mr. Shokri Kaveh’s dedication, technical proficiency, and scholarly output position him as a highly promising researcher with the potential to make lasting contributions to applied mathematics and computational science.
Professional Profile
Education🎓
Hojjatollah Shokri Kaveh is currently pursuing a PhD in Applied Mathematics at Shahid Beheshti University, Tehran, with an expected graduation in 2024. His outstanding academic performance is reflected in his remarkable GPA of 19.2 out of 20 and his achievement of securing 2nd place in Iran’s competitive national doctoral entrance exam in 2018. He holds a Master’s degree in Applied Mathematics from the Amirkabir University of Technology (Tehran Polytechnic), where he graduated in 2017 with a GPA of 16.5. His foundational academic journey began with a Bachelor’s degree in Applied Mathematics from Ilam University, which he completed in 2012. Throughout his academic career, he has focused on mathematical modeling, numerical solutions of partial differential equations, and the development of computational algorithms. His education has provided him with both deep theoretical knowledge and hands-on technical experience, preparing him well for high-level research and academic contributions in the field of applied mathematics.
Professional Experience📝
Hojjatollah Shokri Kaveh brings a diverse range of professional experiences, primarily centered on education and analytical work. He has worked as a mathematics teacher across several reputable platforms in Tehran, including Ostadbank and Aloostad, where he taught for two and three years respectively. Most recently, he served as a mathematics teacher at Sina School (2024–2025), reflecting his continued engagement with academic instruction. Earlier in his career, he also worked as an accountant at Azarnan Nazari for one year (2020–2021), showcasing his versatility and numerical accuracy in practical, real-world applications. His extensive teaching background underscores his strong communication skills, passion for mentoring, and ability to convey complex mathematical concepts clearly. These roles have not only strengthened his instructional capabilities but have also enriched his understanding of applied mathematics in various educational and organizational settings, making him well-rounded both as a researcher and an educator.
Research Interest🔎
Hojjatollah Shokri Kaveh’s research interests lie in the fields of numerical linear algebra, iterative methods for large-scale systems, regularization techniques, and inverse problems arising in partial differential equations. His work focuses on developing and optimizing computational algorithms—such as conjugate gradient, CGNE, and CGNR methods—for solving complex non-symmetric and ill-posed problems. He has a particular interest in Sylvester matrix equations and the mathematical modeling of physical phenomena such as heat conduction, wave propagation, and electrostatics. His publications demonstrate his expertise in variable s-step methods, mapped regularization techniques, and efficient solutions for Cauchy and Helmholtz equations. In addition to theory, he emphasizes algorithmic implementation, leveraging programming tools like MATLAB and Python to validate his methods. His collaborative research with international scholars further highlights the interdisciplinary and applicable nature of his work, bridging mathematical theory with engineering and control systems. His contributions aim to improve computational efficiency and accuracy in real-world scientific modeling.
Award and Honor🏆
One of the most notable honors achieved by Hojjatollah Shokri Kaveh is securing 2nd place in Iran’s highly competitive Doctoral Entrance Exam in Applied Mathematics in 2018, which granted him entry into the prestigious PhD program at Shahid Beheshti University. This national recognition is a testament to his academic rigor, problem-solving ability, and deep understanding of mathematical principles. His high GPA of 19.2/20 during his PhD further illustrates his consistent pursuit of academic excellence. In addition to formal accolades, his selection as a co-author with internationally esteemed scholars such as Dr. Anthony T. Chronopoulos serves as an informal but powerful acknowledgment of his research competence. His multiple publications in indexed international journals highlight his dedication to advancing mathematical science. These honors not only validate his past performance but also position him as a strong candidate for future recognitions, including awards for research, innovation, and contributions to scientific and academic communities.
Research Skill🔬
Hojjatollah Shokri Kaveh possesses a comprehensive set of research skills that bridge theoretical mathematics and practical computation. He is proficient in programming languages such as MATLAB, Python, and C, which he uses to develop and test numerical algorithms. His core competencies include data analysis, data visualization, numerical linear algebra, and iterative methods for solving large-scale linear systems, particularly under ill-posed conditions. He demonstrates expertise in partial differential equations, regularization methods, and inverse problems, with applications in image reconstruction, control systems, and physical simulations. His ability to combine mathematical theory with efficient algorithm design is evident in his high-quality publications in peer-reviewed journals. Mr. Shokri Kaveh is also skilled in scientific writing, LaTeX formatting, and peer communication—crucial for collaborative research. These capabilities allow him to contribute meaningfully to interdisciplinary projects, from initial modeling to final implementation, making him a valuable asset in both academic and applied research environments.
Conclusion💡
Mr. Hojjatollah Shokri Kaveh stands out as a highly capable and promising researcher in applied mathematics with a solid publication record, international collaboration, and exceptional academic performance. His contributions to numerical methods for solving complex mathematical systems are technically sophisticated and valuable to the scientific community.
With further emphasis on international visibility, real-world application, and quantitative impact metrics, he would be an even stronger contender. Nonetheless, based on his current profile, he is a suitable and deserving candidate for the Best Researcher Award.
Publications Top Noted✍
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Title: Mapped Regularization Methods for the Cauchy Problem of the Helmholtz and Laplace Equations
Authors: H. Shokri Kaveh, H. Adibi
Year: 2021
Citations: 7
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Title: Finding Solution of Linear Systems via New Forms of BiCG, BiCGstab and CGS Algorithms
Authors: H. Shokri Kaveh, M. Hajarian, A.T. Chronopoulos
Year: 2024
Citations: 3
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Title: Developing Variable s-step CGNE and CGNR Algorithms for Non-symmetric Linear Systems
Authors: H.S. Kaveh, M. Hajarian, A.T. Chronopoulos
Year: 2024
Citations: 2
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Title: Efficient Image Reconstruction via Regularized Variable s-step Conjugate Gradient Method for Sylvester Matrix Equations
Authors: H.S. Kaveh, M. Hajarian, A.T. Chronopoulos
Year: 2025
Citations: 1
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Title: Variable s-step Technique for Planar Algorithms in Solving Indefinite Linear Systems
Authors: H. Shokri Kaveh, M. Hajarian, A.T. Chronopoulos
Year: 2025
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Title: Exponential Cut-off Regularization Filter for the Cauchy Problem of the Helmholtz Equation
Authors: Hojjatollah Shokri Kaveh
Year: 2020
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Title: A New Regularization Method for Backward Heat Conduction Problem
Authors: Hojjatollah Shokri Kaveh
Year: 2020
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Title: Finite Difference Method for Solving Two-Dimensional Wave Equation
Authors: Hojjatollah Shokri Kaveh, Hojjatollah Adibi
Year: 2020
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Title: Numerical Solution for Dirichlet and Cauchy Problems of Laplace Equation
Authors: Hojjatollah Shokri Kaveh, Hojjatollah Adibi
Year: 2020
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Title: Mixed Regularization Methods for the Cauchy Problems of the Helmholtz Equation
Authors: Hojjatollah Shokri Kaveh
Year: 2019