Hojjatollah Shokri Kaveh is an applied mathematician from Tehran, Iran, with a PhD in Applied Mathematics from Shahid Beheshti University. His expertise lies in data analysis, data visualization, and programming with MATLAB, Python, C, and C++. He has experience in both teaching and accounting and is passionate about applying mathematical tools to solve real-world problems.
Hojjatollah Shokri Kaveh, Shahid beheshti university, Iran
Profile
GOOGLESCHOLAR
🎓 Education
Hojjatollah Shokri Kaveh holds a PhD in Applied Mathematics from Shahid Beheshti University, where he studied. He earned his Master’s degree in Applied Mathematics from Amirkabir University of Technology. His academic journey began with a Bachelor’s degree in Applied Mathematics from Ilam University.
💼 Experience
He has accumulated diverse professional experience across both education and finance. He worked as a mathematics teacher at Ostadbank in Tehran, and later served in a similar role at Aloostad. He transitioned into a financial role, working as an accountant at Azarnan Nazari .
🛠️ Contributions
Hojjatollah Shokri Kaveh has contributed to the academic and educational fields through both teaching and research. As a mathematics teacher at Ostadbank and Aloostad, he played a key role in supporting student learning and academic achievement across a range of mathematical subjects. His background in applied mathematics, combined with practical experience in data analysis and visualization, has allowed him to approach problem-solving with both theoretical depth and real-world application. His programming skills in MATLAB, Python, and C-family languages have supported various academic projects, and his research contributes to advancing data-driven approaches in applied mathematics.
📡 Research Projects
Hojjatollah Shokri Kaveh has been involved in research projects centered around applied mathematics with a particular focus on data analysis and data visualization. His work aims to develop mathematical models and computational techniques for interpreting complex datasets. During his PhD studies at Shahid Beheshti University, he likely undertook projects involving the application of programming tools such as MATLAB and Python to analyze real-world data and visualize results effectively. His research bridges the gap between mathematical theory and practical implementation, addressing contemporary challenges in data-driven decision-making and scientific computing.
🔬 Research Focus
His primary research interests lie in data analysis and data visualization. He is particularly engaged in exploring mathematical approaches to interpreting and presenting complex datasets in meaningful ways.
📘 Publication
Mapped regularization methods for the Cauchy problem of the Helmholtz and Laplace equations
👨🔬 Authors: H Shokri Kaveh, H Adibi
📘 Journal: Iranian Journal of Science and Technology, Transactions A: Science
📅 Year: 2021
Finding solution of linear systems via new forms of BiCG, BiCGstab and CGS algorithms
👨🔬 Authors: H Shokri Kaveh, M Hajarian, AT Chronopoulos
📘 Journal: Computational and Applied Mathematics
📅 Year: 2024
Developing variable s-step CGNE and CGNR algorithms for non-symmetric linear systems
👨🔬 Authors: HS Kaveh, M Hajarian, AT Chronopoulos
📘 Journal: Journal of the Franklin Institute
📅 Year: 2024
Efficient image reconstruction via regularized variable s-step conjugate gradient method for Sylvester matrix equations
👨🔬 Authors: HS Kaveh, M Hajarian, AT Chronopoulos
📘 Journal: Journal of the Franklin Institute
📅 Year: 2025
Variable s-step technique for Planar algorithms in solving indefinite linear systems
👨🔬 Authors: H Shokri Kaveh, M Hajarian, AT Chronopoulos
📘 Journal: Computational and Applied Mathematics
📅 Year: 2025