About

Vishal Garg is a highly skilled research scientist with a strong background in fluid mechanics, combustion, and computational fluid dynamics (CFD). He is currently working as a Wissenschaftlicher Mitarbeiter at inspire ag, where he is responsible for implementing predictive models with traditional engineering simulation algorithms, independent predictive models, or physical (CFD-Thermal) simulations. Vishal completed his Master's degree in Energy Science and Technology (Focus: Combustion, Flow and Propulsion) from ETH Zurich, where he gained extensive experience in experimental combustion research and CFD simulations. He is also interested in machine learning and has taken advanced courses in ML at ETH Zurich to enhance his predictive modeling capabilities inside the physical modeling of fluid dynamics. Prior to his current role, Vishal worked as a Research Assistant at ETH Zurich, where he developed C++ software for Smoothed Particle Hydrodynamics (SPH) particle-based numerical techniques for 3D CFD simulations for die casting. He also extended a data-driven RANS solver for multiphase physics using experimental data in OpenFOAM during his Master's thesis project at ETH Zurich, where he improved the accuracy by gradually adding the forward model with drag, turbulence, and dispersion sub-modules. Vishal's technical skills include ML, software engineering, Python, C++, parallel computing on clusters, and GIT version control. He has also worked with Gambit (user-defined meshes), ParaView, and OpenFOAM. Overall, Vishal is a highly motivated and skilled research scientist with a strong passion for fluid mechanics, combustion, and machine learning. He is always looking for new and exciting opportunities to apply his skills and knowledge to solve complex problems in the field of engineering.