Summary
Daniel Karls is a Senior Cascade Modeling Engineer with a Ph.D. in Aerospace Engineering & Mechanics and over a decade of experience building scientific software and computational infrastructure for atomistic simulation. He has led development of production-grade pipelines and tooling—most notably as a core developer for the NSF-backed OpenKIM project—bridging HPC, cloud services, and developer workflows with Docker-based environments and ML model backends. Comfortable across C, C++, Python, and ML frameworks like PyTorch and TensorFlow, he designs interfaces that make research code robust and portable between supercomputers and cloud platforms. Now transitioning from academia to industry at Boeing Research & Technology, he brings rare institutional knowledge of validated atomistic model deployment and distributed execution. A detail that often surprises collaborators: he pairs deep theoretical insight from his Ph.D. work with practical, reproducible engineering that scales from single-user experiments to multi-cloud production systems.
12 years of coding experience
12 years of employment as a software developer
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at University of Minnesota
Master of Science - MS, Master of Science - MS at Georgia Institute of Technology
Non-degree coursework, Non-degree coursework at University of Washington Tacoma