Vishal Srivastava
Hello there! I am Vishal, an aerospace engineer working at the intersection of data-driven methodologies, computational science, and fluid mechanics. While the tools I develop are relevant for several engineering disciplines, my research work primarily revolves around data-driven modeling of transition and turbulence in fluid flows. I graduated with a B.Tech. in Aerospace Engineering from the Indian Institute of Technology, Kanpur in 2016, and a Ph.D. in Aerospace Engineering from the University of Michigan, Ann Arbor in 2022 (Go Blue!). During my Ph.D., I worked at the Computational Aerosciences Laboratory under the supervision of my advisor, Prof. Karthik Duraisamy, on creating methodologies to infer generalizable model augmentations for numerical models - predominantly closure models for Reynolds-Averaged Navier-Stokes (RANS) simulations - from limited data.

I currently work as a Senior Scientist at Flexcompute where I collaborate with some of the best people in the industry in meshing, numerics, solver development and PhysicsAI, to constantly improve the capabilities of our already best-in-class GPU-native CFD solver Flow360. I have previously worked as a Senior Aerospace Engineer at Analytical Mechanics Associates where I collaborated with highly esteemed researchers at NASA Langley Research Center on data-driven transition and turbulence modeling.

Through all my experiences, I have gathered significant expertise in scientific machine learning, numerical methods, high-performance computing (MPI/OpenMP/CUDA), optimization, inverse problems, uncertainty quantification, and scientific visualization. Over my career, I have used these skills to implement end-to-end scientific computing and machine learning workflows/pipelines including an unstructured, fully differentiable, adjoint-driven RANS solver to perform field inversion and machine learning studies that scaled to thousands of CPU cores. Outside work, I enjoy recreational programming, solving physics/mathematics problems, reading fiction/non-fiction, chess, long walks, and spending time with my lovely wife.
Selected Publications
  1. Vishal Srivastava, Christopher L. Rumsey, Gary N. Coleman, and Li Wang. "On generalizably improving RANS predictions of flow separation and reattachment." AIAA SciTech 2024 Forum. 2024.
  2. Nathaniel Hildebrand, Vishal Srivastava, Tamer A. Zaki, and Meelan M. Choudhari. "DeepONet-Assisted Optimization of Surface Topography for Transition Delay in A Mach 4.5 Boundary Layer." 14th International ERCOFTAC Symposium on Engineering Turbulence Modelling and Measurements (ETMM14), no. 20230001917. 2023.
  3. Vishal Srivastava, Valentin Sulzer, Peyman Mohtat, Jason B. Siegel, and Karthik Duraisamy. "A non-intrusive approach for physics-constrained learning with application to fuel cell modeling." Computational Mechanics 72.2 (2023): 411-430.
  4. Vishal Srivastava, and Karthik Duraisamy. "Towards a generalizable data-driven approach to predict separation-induced transition." 12th International Symposium on Turbulence and Shear Flow Phenomena (TSFP12). 2022.
  5. Vishal Srivastava, and Karthik Duraisamy. "Generalizable physics-constrained modeling using learning and inference assisted by feature-space engineering." Physical Review Fluids 6.12 (2021): 124602.
  6. Vishal Srivastava, and Karthik Duraisamy. "Aerodynamic design of aircraft engine nozzles with consideration of model form uncertainties." 2018 AIAA Non-Deterministic Approaches Conference. 2018.
Experience