"Placement of observations in Dynamic Data Assimilation using Forward Sensitivity Method"
Wednesday, Apr 15, 2026
- Colloquium - 499 DSL Seminar Room
- 03:30 to 04:30 PM Eastern Time (US and Canada)
Click Here to Join via Zoom
Meeting # 942 7359 5552
Zoom Meeting # 942 7359 5552
Abstract:
There is an ever-growing need for increasing model resolution which in turn increases the dimension of the model space. Thanks to the confluence of advances in sensor, wireless communication, large scale storage technologies, the amount of data collected doubles in a few years. With the Increase in model dimension, and the amount of data made available, the time needed to assimilate large volumes of data using the well-known 4-DVAR methods in high dimensional models correspondingly increases. However, in practical situations, time allotted for data assimilation is limited and is often fixed. For a given model of large dimension, the only way to reduce the assimilation time is to select a subset of observations in the assimilation window to get good estimates of the control variables consisting of initial and boundary conditions and parameters. A method based on the evolution of the forward sensitivity of the model solution with respect to the control variables can be used as a guide in the selection of a subset of effective observations for estimating the control. Simple examples will be used to illustrate this process.
Speaker Biography:
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.
While at OU, he has won numerous awards for both teaching and research.
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 and has mentored over 30 PhD dissertations and 44 MS theses.
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.
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