Michael Tsatsomeros

Michael Tsatsomeros is a Professor of Mathematics and Statistics at Washington State University (WSU), Pullman, WA, where he has served since 2007. He holds a PhD in Mathematics from the University of Connecticut (1990) and has extensive academic experience, including roles at the University of Regina, Canada, and visiting positions at institutions like the Indian Institute of Technology-Madras. His research focuses on linear algebra, matrix analysis, nonnegative matrices, numerical range, and applications in dynamical systems, control theory, and machine learning.

Education: PhD in Mathematics (1990, University of Connecticut), M.Sc. in Mathematics (1986, Concordia University), and a Diploma in Mathematics (1984, University of Patras, Greece).

Research interests include matrix positivity, numerical linear algebra, and applications of matrix theory in interdisciplinary fields like AI and data science. He has authored/co-authored books such as Matrix Positivity (2020) and Linear Algebra and Matrix Methods (2024). His work has been recognized with awards including the 2024 Tom & Julie Lutz Teaching Excellence Award and the 2021 Excellence in Graduate Advising.

Key research trends in his articles include P-matrices, Cayley transforms, and matrix positivity classes, with contributions to both theoretical and applied aspects of linear algebra. His grants include collaborations with the SPARC program and NSERC funding.

He advises and mentors numerous graduate students, including current PhD candidates and over 20 completed students. His lab and collaborative work emphasize matrix analysis and its interdisciplinary applications.