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S. Lakshmivarahan
University of Oklahoma
Norman, Oklahoma

After completing his PhD from the Indian Institute of Science, in 1973, S. Lakshmivarahan held faculty and postdoctoral positions at the Indian Institute of Technology Madras, Brown University, and Yale University.

In the fall of 1978, Lakshmivarahan joined the School of Computer Science at the University of Oklahoma (OU). He has been recognized as a George Lynn Cross Research Professor since 1995, and has won numerous awards for both teaching and research. As of July 2019, he holds the position of George Lynn Cross Research Professor Emeritus at OU’s School of Computer Science.

His research interests are in applied mathematics and computation and include data mining and analytics, data assimilation, parallel computation, and learning algorithms. He has authored/coauthored six books in these areas and has mentored over 30 PhD dissertations and 40 master’s theses.

He was recognized as an IEEE Fellow in 1993 and an ACM Fellow in 1995, and has held short-term visiting positions in Japan, China, Taiwan, India, Germany, England, Mexico, Brazil, and Canada.

Lakshmivarahan has been a member of the CR community since 1986.


Matrix analysis and applied linear algebra (2nd ed.)
Meyer C. (ed), SIAM, New York, NY, 2023. 991 pp.  Type: Book (1611977436)

This expanded and revamped second edition follows an excellent first edition, and is the culmination of classroom experiences since the first edition’s publication more than two decades ago. While the two editions share the same title, this ...


Dynamics and bifurcation in networks: theory and applications of coupled differential equations
Golubitsky M., Stewart I., SIAM, New York, NY, 2023. 870 pp.  Type: Book (1611977320)

This magnificent book covers the impact of (a) inherent symmetry in a class of ordinary differential equations (ODEs); (b) inherent structural symmetry in the underlying graph/network; and (c) their interaction on the overall stability and bifurca...


Foundations of computational imaging: a model-based approach
Bouman C., SIAM, Philadelphia, PA, 2022. 349 pp.  Type: Book (1611977126)

This attractively titled book deals with the process of creating images using raw noisy data from unknown sources such as a black hole, for example. This book arose out of the notes used for a graduate-level course on this topic for over two decad...


 Applied linear analysis for chemical engineers: a multi-scale approach with Mathematica
Balakotaiah V., Ratnakar R., DE GRUYTER, Berlin, Germany, 2022. 590 pp.  Type: Book (3110739690)

This 750-plus-page book on applied linear analysis is the culmination of the authors’ more than three decades of experience teaching graduate students in chemical engineering, as well as a continuation of their own mentors’ legacy. It ...


Computational methods for deep learning: theoretic, practice and applications
Yan W., Springer International Publishing, Cham, Switzerland, 2021. 211 pp.  Type: Book (978-3-030610-80-7), Reviews: (1 of 3)

Computational methods for deep learning is written for the typical second-year graduate student at a US university, working in this area for his/her PhD-level dissertation research on the application of various manifestations of...


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