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Lakshmivarahan, S.
University of Oklahoma
Norman, Oklahoma
 
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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.

 
 
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   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: (3 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...

Apr 23 2021  
   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...

Apr 23 2021  
   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: (2 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...

Apr 23 2021  
 
 
   
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