Stefan Schroedl is a Senior Applied Scientist with 17 years of experience applying machine learning and algorithm design to high-impact products across search, recommendation, computational drug discovery, and large language models. He blends deep research credentials—a PhD, co-authorship of an AI textbook, 30+ peer-reviewed papers and patents with 5k+ citations—with hands-on production engineering at Amazon, Atomwise, Yahoo, and Mercedes-Benz. Stefan has led teams that shipped large-scale ranking and NLU features for consumer products and helped establish ML best practices and platforms for startups and enterprises. His recent work focuses on interpretable AI, inference optimization for large language and video models, and core contributions to Amazon Nova. An independent thinker and prolific OSS author in R, C++ and Matlab, he frequently advises academia and industry, bringing a rare combination of theoretical rigor and pragmatic delivery.
16 years of coding experience
22 years of employment as a software developer
Ph.D. Computer Science, Ph.D. Computer Science at The University of Freiburg
Master Computer Science, Master Computer Science at RPTU Kaiserslautern-Landau
R tool for automated creation of ggplots. Examines one, two, or three variables and creates, based on their characteristics, a scatter, violin, box, bar, density, hex or spine plot, or a heat map. Also automates handling of observation weights, log-scaling of axes, reordering of factor levels, and overlays of smoothing curves and median lines.
Contributions:4 releases, 54 commits, 1 PR in 4 years 9 months
smoothingobservationautomatesheatcharacteristics
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Stefan Schroedl - Senior Applied Scientist, AGI Foundations