Applied Math. Department, Shahid Bahonar University, Iran
Dr. Ehsan Kheirandish is a Ph.D. graduate in Applied Mathematics from Shahid Bahonar University of Kerman, Iran. His academic journey reflects a consistent focus on the fields of numerical analysis and numerical linear algebra, with a particular specialization in matrix theory and tensor computations. With a solid background in theoretical and computational mathematics, Dr. Kheirandish has contributed to the understanding and development of generalized inverses, including W-weighted core-EP matrices and bilateral inverses via Einstein products. His work has been published in reputable peer-reviewed journals and presented at national mathematical conferences. He also possesses strong teaching and mentoring capabilities, having taught courses such as differential equations and numerical methods, and assisted in subjects including matrix theory and linear algebra. As an emerging researcher, Dr. Kheirandish is building a strong foundation for a promising academic and research-oriented career. His consistent publication record, collaboration with senior researchers, and participation in academic seminars showcase a commitment to advancing mathematical science. While still early in his career, his academic rigor and research clarity place him in a favorable position for future accomplishments in applied and computational mathematics.
Professional Profile
Education
Dr. Ehsan Kheirandish pursued a structured academic path in the field of mathematics. He began his undergraduate studies in 2011 at Hakim Sabzevari University, Iran, where he earned a Bachelor of Science (B.S.) degree in Mathematics in 2014. During his undergraduate studies, he developed a foundational understanding of core mathematical principles, which laid the groundwork for his graduate education. He furthered his studies with a Master of Science (M.S.) degree in Mathematics at Tabriz University from 2015 to 2017. Here, he began to engage with more advanced topics in numerical analysis and linear algebra, likely initiating his first exposure to research methods and applications in matrix theory. From 2018 to 2024, Dr. Kheirandish completed his Doctor of Philosophy (Ph.D.) in Applied Mathematics at Shahid Bahonar University of Kerman, Iran. His doctoral research focused on specialized matrix computations and the theoretical aspects of generalized inverses. Throughout his academic training, Dr. Kheirandish was mentored by expert mathematicians and collaborated with established researchers, which helped shape his research interests. His education has been consistent, rigorous, and deeply aligned with his current research output, positioning him well for academic and professional contributions to the field of applied mathematics.
Professional Experience
Dr. Ehsan Kheirandish has gained professional experience primarily through academic teaching and research activities within Iranian universities. During his postgraduate studies, he took on responsibilities as a teaching assistant in several mathematics courses, including Basics of Matrices and Linear Algebra, Numerical Analysis, and Numerical Linear Algebra. His involvement in course instruction extended to leading undergraduate classes in Differential Equations and Numerical Calculations, where he helped students understand complex mathematical theories through practical examples and problem-solving sessions. This experience demonstrates his ability to communicate mathematical ideas effectively and support student learning. In addition to teaching, Dr. Kheirandish has been actively engaged in research projects, often in collaboration with senior scholars such as A. Salemi and Q. Wang. Although his professional roles have thus far remained within the academic sphere, his consistent participation in national seminars and mathematics conferences indicates a proactive effort to integrate research with professional development. Dr. Kheirandish’s academic positions have not yet extended to formal university faculty roles or international appointments; however, his profile reflects growing expertise and responsibility within academic institutions in Iran. His professional experience underscores a balance between teaching, mentorship, and original research contributions in applied mathematics.
Research Interest
Dr. Ehsan Kheirandish’s research interests lie at the intersection of numerical analysis and numerical linear algebra, with a particular focus on generalized inverses of matrices and tensors. His work centers on the theoretical development and practical computation of matrix inverses, including novel concepts like W-weighted core-EP matrices and generalized bilateral inverses. A significant part of his recent research also investigates the applications of these mathematical structures in solving singular tensor equations, which have implications in computational science, engineering, and data analysis. He is especially interested in extending classical linear algebra concepts to high-dimensional and structured data systems through operations such as the Einstein product. This interest aligns with current trends in applied mathematics that explore tensor analysis and multilinear algebra. His research is both mathematically rigorous and computationally relevant, indicating a commitment to bridging theory with practical applications. Dr. Kheirandish’s ongoing collaborations with established researchers suggest that he is contributing to the advancement of specialized topics in linear algebra. While his current research is highly focused, there is potential for expansion into interdisciplinary domains such as machine learning, scientific computing, and applied physics, where tensor-based methods are increasingly relevant.
Research Skills
Dr. Ehsan Kheirandish possesses a strong set of research skills rooted in theoretical mathematics and numerical computation. His expertise in numerical linear algebra is evident in his published work on generalized inverses, tensor algebra, and matrix decomposition techniques. He demonstrates proficiency in analytical problem-solving, mathematical modeling, and symbolic computation, which are essential for his research topics. His work with the Einstein product and singular tensor equations indicates advanced capabilities in high-dimensional algebraic computations. Furthermore, his publication record suggests competence in using mathematical software tools, possibly including MATLAB, Mathematica, or Python-based numerical libraries, although specific tools are not explicitly listed in his CV. Dr. Kheirandish also shows skill in academic writing and collaboration, having co-authored several articles in peer-reviewed journals. His presentations at national mathematics seminars and conferences demonstrate his ability to communicate complex mathematical ideas to academic audiences. Through his teaching assistant roles, he has further honed his skills in mentoring, instructional design, and conveying abstract concepts effectively. As an emerging researcher, Dr. Kheirandish combines a solid theoretical foundation with practical research techniques, positioning himself well for continued contributions to computational mathematics and applied analysis.
Awards and Honors
While the CV does not mention specific awards or honors formally received by Dr. Ehsan Kheirandish, his research output and academic activities reflect a level of merit and recognition within his field. He has published in respected journals such as the Journal of Computational and Applied Mathematics and Computational and Applied Mathematics, which indicates peer validation of his work. Additionally, his selection as a speaker at the 53rd Annual Iranian Mathematics Conference and the 11th Seminar on Linear Algebra and its Applications suggests recognition from the national academic community. These presentations provide important platforms for early-career researchers to showcase their work and receive feedback from experts, and his participation implies a growing reputation in specialized mathematics circles. While formal honors such as research fellowships, international grants, or best paper awards are not currently listed, Dr. Kheirandish’s academic path and publication record reveal a trajectory of scholarly achievement. With continued focus on expanding the visibility and impact of his research, he is well-positioned to receive future awards and distinctions in the field of applied and computational mathematics.
Conclusion
Dr. Ehsan Kheirandish is a highly capable and focused early-career researcher in applied mathematics, demonstrating commendable depth in numerical linear algebra and matrix theory. His doctoral research, combined with a consistent publication record and academic engagement, reflects a clear and structured approach to advancing knowledge in his chosen domain. Through teaching, assisting in core mathematical subjects, and publishing collaborative research, he has established himself as a promising academic in the Iranian mathematical community. Although his international exposure and interdisciplinary reach are currently limited, his strong foundational skills and specialized focus provide a solid platform for future growth. To further enhance his research profile, engaging in international collaborations, securing competitive funding, and exploring real-world applications of his mathematical work would be beneficial. Overall, Dr. Kheirandish exemplifies the qualities of a dedicated and methodical researcher with strong potential for academic leadership. His contributions thus far position him as a worthy candidate for recognitions such as the Best Researcher Award, especially in categories that value depth, consistency, and clarity of research focus.
Publications Top Notes
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Title: Further characterizations of W-weighted core-EP matrices
Authors: A. Salemi and Q. Wang
Year: 2025
Journal: Journal of Computational and Applied Mathematics
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Title: Properties of core-EP matrices and binary relationships
Authors: A. Salemi and N. Thome
Year: 2024
Journal: Computational and Applied Mathematics
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Title: Generalized bilateral inverses of tensors via Einstein product with applications to singular tensor equations
Authors: A. Salemi
Year: 2023
Journal: Computational and Applied Mathematics
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Title: Generalized bilateral inverses
Authors: A. Salemi
Year: 2023
Journal: Journal of Computational and Applied Mathematics