Abstract: Thanks to the advances in sensor, wireless communication, large scale storage devices and supercomputer technologies, we are steadily moving from data sparse to data rich regimes and it is estimated that the amount of data doubles in every two to three years. This growth has brought big data problems to the forefront. In this talk we will review the developments in data analytics from the early days of Astronomy and will discuss the three pillars of Data Science, namely Data Mining, Data Assimilation and Prediction. The relation between Data Science and AI will be presented.
About the speaker: After completing his PhD from the Indian Institute of Science in 1973, S. Lakshmivarahan held faculty and post-doctoral positions at the IIT-Madras, Brown and Yale Universities through 1978. In the Fall of 1978, he joined the School of Computer Science, University of Oklahoma (OU) where he held the position of George Lynn Cross Research Professor since 1995.
His research interests are in Applied Mathematics and Computation and includes Data Mining and Analytics, Data Assimilation, Computational Finance, Parallel Computation and Learning Algorithms. He is an author/coauthor of six books in these areas. He was elected as a Fellow of the IEEE in 1993 and a Fellow of ACM in 1995.
He has held short-term visiting positions in Japan, China, Taiwan, Thailand, India, Germany, England, Mexico, Brazil, Canada, and USA.
Since July 2019, he holds the position of George Lynn Cross Research Professor Emeritus at the School of Computer Science, OU.