Summary
David Sondak is a Research and Development Software Engineering Manager with 10+ years at the intersection of computational science, AI/ML, and engineering physics, now leading R&D at Dassault Systèmes Simulia. He blends deep domain expertise in CFD, turbulence modeling, and numerical methods with production-grade software skills in C++, Python, PyTorch, and Fortran, and a track record of published research in scientific machine learning and fluid mechanics. His background includes academia—teaching and supervising graduate research at Harvard and developing novel algorithms for coherent structures and thermal convection—bringing rigorous scientific thinking to industrial software development. David’s work often focuses on physics-informed ML, surrogate and reduced-order models, and uncertainty quantification, allowing him to translate complex flow physics into practical, high-performance simulation tools. An underappreciated strength is his experience shipping and validating commercial CFD codebases, giving him rare fluency across theory, code, and product.
10 years of coding experience
3 years of employment as a software developer
PhD, Aerospace Engineering, PhD, Aerospace Engineering at Rensselaer Polytechnic Institute
B.S., Mechanical Engineering, Mechanical Engineering, B.S., Mechanical Engineering, Mechanical Engineering at Lehigh University
English, French