I am a Warschawski Assistant Professor at the University of California, San Diego. My research interests encompass the fields of field theory and polynomial, linear, and multilinear algebra, as well as matching theory and additive number theory. I earned my Ph.D. from the University of Illinois at Chicago under the supervision of Shmuel Friedland (I was his last (8th) student.) From 2020 to 2022, I served as a postdoctoral associate at Iowa State University. You may find my more or less updated CV here.
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I serve on the editorial board of The Bulletin of the International Linear Algebra Society, IMAGE.
Linear Algebra and Matrices: This introductory textbook grew out of several courses in linear algebra given over more than a decade and includes such helpful material as: constructive discussions about the motivation of fundamental concepts many worked-out problems in each chapter, and topics rarely covered in typical linear algebra textbooks. The authors use abstract notions and arguments to give complete proof of the Jordan canonical form and, more generally, the rational canonical form of square matrices over fields. They also provide the notion of tensor products of vector spaces and linear transformations. Matrices are treated in depth, with coverage of the stability of matrix iterations, the eigenvalue properties of linear transformations in inner product spaces, singular value decomposition, and min-max characterizations of Hermitian matrices and nonnegative irreducible matrices. The authors show the many topics and tools encompassed by modern linear algebra to emphasize its relationship to other areas of mathematics.
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You may use this amazon link to purchase it.
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Coming soon
Analysis and Probability on Graphs: This textbook originates from years of teaching courses in probability, graph theory, combinatorics, and matrix theory by the first author at the University of Illinois, Chicago. The book has seven chapters. The first five chapters may be used as a textbook for advanced undergraduate courses, related to probability theory, random walks and probability on graphs in mathematics and mathematical computer science departments. The materials covered in these chapters may be used to investigate real-world problems. The last two chapters are aimed at graduate students as a reference book or for individual study or research. We use abstract notions and arguments to introduce probability theory, random graphs, Markov chains on digraphs, Square matrices with nonnegative entries, symbolic dynamics and walks on graphs and Discrete Lyapunov exponents and Hausdorff dimension.
We highlight the following unique features of the book:
• Motivational Discussions: The book features discussions elucidating the
motivations behind fundamental concepts.
• Worked-out Problems: Most chapters include many solved problems that
help students apply what they have learned in a practical way.
• Comprehensive Coverage: The textbook goes beyond conventional topics,
exploring areas rarely covered in Probability on Graphs-related literature.
Specifically, we have compiled subjects recognized by the community but
never previously assembled in a single book.