Saumil Patel

Saumil Patel is a Researcher at Argonne National Laboratory (ANL) and a graduate of the City College of New York (CCNY), where he earned his Ph.D. in Mechanical Engineering. He is affiliated with ANL's Mathematics and Computer Science (MCS) Division and Argonne Leadership Computing Facility (ALCF).

• Education: Ph.D. in Mechanical Engineering (CCNY), B.S./M.S. in Mechanical Engineering (prior to Ph.D.)

His research focuses on Computational Fluid Dynamics (CFD) with an emphasis on high-order numerical methods, meshing techniques, and high-performance computing (HPC). He has developed applications like NekLBM and optimized workflows for CFD simulations using Arbitrary Lagrangian-Eulerian (ALE) methods.

His recent work includes enabling in-situ visualization for the Exascale Computing Project, optimizing CFD codes for next-generation computing architectures, and integrating machine learning (e.g., TensorFlow) with CFD to enhance physical models of near-wall behavior. His research has been applied to internal combustion engine (ICE) simulations by domain scientists in academia and DOE labs.