Andre Holzner is a Staff Research Engineer with 11+ years of experience applying advanced ML, high-throughput computing, and firmware expertise to large-scale scientific and production systems. Trained as a Higgs hunter at CERN and ETH Zürich (PhD in Physics), he has run and optimized multi‑terabit data acquisition networks for CMS, implemented VHDL for FPGA trigger systems, and built deep learning classifiers for particle ID that ranked in the top 25% of the Kaggle Higgs challenge. At Meta and UCSD he bridged research and engineering—shipping C++, Java, and Python solutions, improving Infiniband throughput, and maintaining kernel and low-level data‑acquisition code. He combines statistical rigor (parametric modeling and hypothesis testing) with hands-on performance tuning (SSE/assembly, custom CRCs) and a knack for making complex, distributed systems operate 24/7. Based in the Zürich area, he’s a pragmatic problem solver comfortable moving between firmware, simulation (Geant4), ML, and production-scale infrastructure.
11 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (PhD) Physics, Doctor of Philosophy (PhD) Physics at ETH Zürich
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