Ivan Stanimirović, PhD, is currently with the Department of Computer Science, Faculty of Sciences and Mathematics at the University of Niš, Serbia, where he is an Assistant Professor. He formerly was with the Faculty of Management at Megatrend University, Belgrade, as a Lecturer. His work spans from multi-objective optimization methods to applications of generalized matrix inverses in areas such as image processing and restoration and computer graphics. His current research interests include computing generalized matrix inverses and its applications, applied multi-objective optimization and decision making, as well as deep learning neural networks. Dr. Stanimirović was the Chairman of a workshop held at 13th Serbian Mathematical Congress, Vrnjačka banja, Serbia, in 2014.
"""This book explores the computation of various kinds of generalized inverses of constant matrices, matrix polynomials, and rational functions, from the point of view of symbolic computation. The matter of stability is not considered. After setting basic definitions and properties in Chapter 1, in Chapter 2 the author reviews various methods for constructing generalized inverses of constant matrices. In the third chapter, techniques based on classical matrix factorizations are applied to “polynomial and rational matrices”, i.e., matrix polynomials and rational matrix functions. The discussion focuses mainly on theoretical properties and algorithms, rather than on the role of generalized inverses in solving particular problems, e.g., least squares problems. Some applications are briefly described in the last chapter. Many examples involving matrices of small size are given, in order to illustrate the peculiarities of the algorithms. The implementation of some of the methods described is reported in the form of Mathematica programs. Due to the size of the font used, it is not always easy to read the program listings. It would have been preferable to attach to the volume a CD containing the code. The English language used in the book is sometimes convoluted or incorrect, but on average it is rather comprehensible."" - Giuseppe Rodriguez - Mathematical Reviews Clippings - March 2019"