About

I am a Research Associate in the OPTIMUS Center of the Oden Institute at The University of Texas at Austin. I work on numerical methods for the inference, prediction, and optimal design and control of complex physical systems which are often mathematically modeled as parametrized partial differential equations (PDEs). My work blends numerical analysis, machine learning, and mechanistic modeling to create state-of-the-art methods to support decision making regarding complex systems under high-dimensional uncertainty.

I am currently looking for tenure-tracked positions.

Please do not hesitate to reach out, if you think I may be a suitable candidate for an open position.

Short Bio: I completed my PhD in Computational Science, Engineering, and Mathematics at The University of Texas at Austin Oden Institute for Computational Engineering & Sciences under the supervision of Omar Ghattas and the co-supervision of Patrick Heimbach. Before that I completed degrees in Engineering Mechanics and Mathematics at the University of Wisconsin--Madison.

Current Research Funding

NSF RISE Award 2425922  2024–2027   A Bayesian Inference Framework for Learning Earthquake Cycle Deformation Processes Across Scales via Novel Neural Operators (PI Omar Ghattas, Co-PIs Thorsten Becker and Thomas O’Leary-Roseberry) $832,277

NSF OAC Award 2313033  2023–2026   The Best of Both Worlds: Deep Neural Operators as Preconditioners for Physics-Based Forward and Inverse Problems (PI Omar Ghattas, Co-PI Thomas O’Leary-Roseberry) $600,000

NSF DMS Award 2324643  2023–2026   Co-Design of Neural Operators and Stochastic Optimization Algorithms for Learning Surrogates for PDE- Constrained Optimization Under Uncertainty (PI Raghu Bollapragada, Co-PIs Omar Ghattas and Thomas O’Leary-Roseberry) $499,792