Sourav Dutta

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I am currently a Research Associate in the Computational Hydraulics Group at the Oden Institute for Computational Engineering & Sciences of the University of Texas at Austin, working with Prof. Clint Dawson. Previously, I was an ORISE postdoctoral fellow at the Coastal & Hydraulics Laboratory of the U.S. Army Engineer Research and Development Center, where I worked with Dr. Matthew Farthing. I received my Ph.D. in Mathematics from Texas A&M University in 2017, supervised by Prof. 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.

Interests
  • Model Order Reduction
  • Computational Fluid Dynamics
  • Scientific Machine Learning
  • Uncertainty Quantification
Education
  • Ph.D. in Mathematics, 2017

    Texas A&M University

  • B.Sc. & M.Sc. in Mathematics & Computing, 2010

    Indian Institute of Technology Kharagpur

Work Experience

Oden Institute for Computational Engineering & Sciences, UT Austin

Research Associate

Mar 2025 - Present · Mississippi (Remote)

Research Fellow

Oct 2022 - Feb 2025 · Mississippi (Remote)

U.S. Army Engineer Research & Development Center (ERDC)

ORISE Postdoctoral Fellow

Sep 2017 - Aug 2022 · Mississippi

News

Oct 01, 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 Prof. Clint Dawson and other esteemed members of the Computational Hydraulics Group. Looking forward to an exciting and productive time ahead.
Sep 01, 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. Session 1 Session 2
Jul 01, 2022 Giving a talk on Physics-Aware Machine Learning Model for Predicting Coastal Hydrodynamics at the SIAM Annual Meeting 2022 in Pittsburgh, PA.
Jun 01, 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 01, 2022 Attending the HydroML Symposium on Big Data Machine Learning in Hydrology and Water Resources at Penn State University.

Selected Publications

  1. JGRML
    Preview of A Neural Operator Emulator for Coastal and Riverine Shallow Water Dynamics
    A Neural Operator Emulator for Coastal and Riverine Shallow Water Dynamics
    Peter Rivera-Casillas, Sourav Dutta, Shukai Cai, and 7 more authors
    Journal of Geophysical Research: Machine Learning and Computation, May 2026
  2. JCP
    Preview of A greedy non-intrusive reduced order model for shallow water equations
    A greedy non-intrusive reduced order model for shallow water equations
    Sourav Dutta, Matthew W. Farthing, Emma Perracchione, and 2 more authors
    Journal of Computational Physics, Aug 2021
  3. MCA
    Preview of Reduced Order Modeling Using Advection-Aware Autoencoders
    Reduced Order Modeling Using Advection-Aware Autoencoders
    Sourav Dutta, Peter Rivera-Casillas, Brent Styles, and 1 more author
    Mathematical and Computational Applications, Apr 2022
  4. SI
    Preview of pyNIROM—A suite of python modules for non-intrusive reduced order modeling of time-dependent problems
    pyNIROM—A suite of python modules for non-intrusive reduced order modeling of time-dependent problems
    Sourav Dutta, Peter Rivera-Casillas, Orie M. Cecil, and 1 more author
    Software Impacts, Aug 2021