About me
I am currently a Research Fellow in the Computational Hydraulics Group at the Oden Institute for Computational Engineering & Sciences of the University of Texas at Austin, where I am working with Clint Dawson. Previously, I was a ORISE postdoctoral fellow at the Coastal & Hydraulics Laboratory of the U.S. Army Engineer Research and Development Center, where I worked with Matthew Farthing. Prior to that, I earned a Ph.D. in mathematics from Texas A&M University, supervised by Prabir Daripa.
My research interests lie at the intersection of classical, physics-based computational methods and modern data-driven, machine learning-based techniques with applications to computational science and engineering. I am particularly interested in exploring ways to develop efficient and robust numerical approximations of real-world, large scale environmental flow problems by combining physical principles with modern machine learning algorithms, either by infusing physics-based regularization in the learning trajectory or by modeling the underlying differential operator.
Download my resumé .
- Model Order Reduction
- Computational Fluid Dynamics
- Scientific Machine Learning
- Uncertainty Quantification
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PhD in Mathematics, 2017
Texas A&M University
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BSc & MSc in Mathematics & Computing, 2010
Indian Institute of Technology Kharagpur
Experience
Projects include:
- Development of compound flood simulation capabilities within Adaptive Hydraulics (AdH)
- Reduced order modeling for coastal engineering applications
- Development of physics-based operator learning framework for environmental flows
Projects include:
- Development of reduced order model (ROM) for shallow water flows
- Data-driven ROMs for computational fluid dynamics problems
- Machine learning (ML)-based ROM for advection-dominated flows
- Python-based, open source package for ROM development
News
October 2022: I have started my new position as Research Fellow at the Oden Institute for Computational Engineering & Sciences of The University of Texas at Austin. I will be working with Clint Dawson and some of his collaborators from the esteemed Computational Hydraulics Group. Looking forward to an exciting and productive time ahead.
September 2022: Co-organizing a minisymposium on Machine Learning and Data-Driven Methods for Forward and Inverse Problems along with Matthew Farthing and Dhruv Patel at the SIAM Mathematics of Data Science 2022 meeting in San Diego, CA.
July 2022: Giving a talk on Physics-Aware Machine Learning Model for Predicting Coastal Hydrodynamics at the SIAM Annual Meeting 2022 in Pittsburgh, PA.
June 2022: Giving a talk at the Computational Methods in Water Resources 2022 (CMWR) meeting on Deep Learning Methods for Reduced Order Modeling of Convection-Dominated Environmental Hydrodynamics.
May 2022: Attending the HydroML Symposium on Big Data Machine Learning in Hydrology and Water Resources at Penn State University.
February 2022: Giving an invited talk on Data-Driven Reduced Order Modeling for Applications in Computational Hydrology in the Applied Math Seminar of the Department of Mathematics at Texas A&M University Corpus-Christi.
Recent Publications
Contact
- sourav.dutta@austin.utexas.edu
- 601 634 3614
- US Army ERDC, CHL, 3909 Halls Ferry Rd, Vicksburg, MS 39180