Summary
David Hendriks, PhD, is a research-focused software engineer with nine years' experience bridging computational astrophysics, AI/ML, and high-performance simulation engineering. He currently leads GPU-accelerated, meshless CFD development at Morpheus Fluid while building LLM-powered discovery tools for astronomy at UniverseTBD, combining CUDA/C++ numerical optimization with retrieval-augmented generation and semantic search. His academic work centers on binary stellar evolution and Bayesian data-assimilation, and he routinely integrates machine learning with traditional sampling to improve uncertainty estimation. Comfortable across Python, C, PyTorch and HPC stacks, he moves research code toward production-quality simulation and analysis pipelines. Notably, he extracts and connects knowledge from thousands of astrophysics talks into searchable datasets, enabling automated code synthesis and literature linking for researchers. Based in Guildford, he pairs rigorous PhD-level science with pragmatic software craftsmanship to deliver reproducible, high-performance research tools.
9 years of coding experience
2 years of employment as a software developer
VWO natuur en gezondheid, Natuur en Techniek/Natuur en Gezondheid, VWO natuur en gezondheid, Natuur en Techniek/Natuur en Gezondheid at St michaelcollege
Bachelor, Natuur en Sterrenkunde, Bachelor, Natuur en Sterrenkunde at Universiteit van Amsterdam / University of Amsterdam
Master of Science (M.Sc.), Physics and astronomy (Astronomy and astrophysics), GRAPPA/Astro, Master of Science (M.Sc.), Physics and astronomy (Astronomy and astrophysics), GRAPPA/Astro at Universiteit van Amsterdam
Dutch, English, German