Hesam Safari

Institute of Applied Mechanics (iAM) - Optimized Laser Additive Manufacturing process using data-driven surrogates based on Deep Neural Operators using PyTorch. - Conducting research in Scientific Machine Learning (SciML) with a focus on the development of physics-informed and data-driven surrogates based on deep neural operators. - Project Coordinator for KI4All, an initiative dedicated to creating interdisciplinary, AI-focused educational content (https://ki4all.net). - Teaching Machine Learning fundament

Laboratory of Fluid Dynamics and Technical Flows (LSS) - Extended lattice Boltzmann solvers in C++ for reactive flows in complex geometries. -Increased the solver accuracy by applying curved boundary conditions.

Institute for Computational Modeling in Civil Engineering (iRMB) - Developed LBM framework for thermally-compressible low Mach flows with application in combustion simulations. - Developed and extended multiphase lattice Boltzmann parallel solvers in C++ for the research code VirtualFluids. - Alexander von Humboldt Postdoctoral Fellow (Jan. 2017 – May 2019)

- Extended and further developed an in-house C++ code for thermodynamic modeling and simulations of gas turbines. - Performed combustion process analysis using thermodynamics zonal models. - Prepared detailed technical reports to document project progress, methodologies, and performance outcomes for internal and client stakeholders.

- Developed a numerical FORTRAN solver for knock prediction in dual-fuel (gas-diesel) engines. - Verified the developed code and analyzed engine performance for the first national heavy-duty diesel engine design project (D-87). -Authored a technical paper for ASME 2008 Internal Combustion Engine Division Spring Technical Conference held in Chicago, USA.