Summary
Balazs Strenner is a Senior Deep Learning Engineer in Budapest with 12 years of technical and academic experience, combining a PhD in Mathematics with four years of applied computer vision work in the automotive industry. He builds production-ready multi-task and end-to-end 3D perception systems, has led efforts in image-based localization and Monte Carlo localization, and contributed a patent application for novel algorithms. His background as a mathematical researcher and postdoc (including a Mary Ellen Rudin Award) informs a rigorous, performance-minded approach—evident in reimplementing algorithms in Julia for 20x speedups during his academic work. Comfortable in Scrum and SAFe roles, he also leverages foundation models to streamline annotation and tooling, bridging research-grade methods with deployable engineering.
12 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy (PhD) Mathematics, Doctor of Philosophy (PhD) Mathematics at University of Wisconsin-Madison
Master's degree Mathematics, Master's degree Mathematics at Eötvös Loránd University
English, Hungarian, French