Reinhard Heckel
Professor (tenured Associate Professor)
Munich, Bavaria, Germany
Summary
👤
Senior🎓
Top SchoolReinhard Heckel is a tenured Associate Professor of Machine Learning at TUM and adjunct professor at Rice University with a decade of research and academic experience spanning ETH Zurich, Stanford, Berkeley, and IBM Research. He focuses on the theoretical foundations of machine learning and deep learning, translating rigorous signal-processing and information-theoretic training into impactful publications and teaching. Recognized as a Capital Top 40 under 40, he combines deep mathematical expertise from a Dr. sc. in Information Technology and Electrical Engineering with a track record of building research groups and mentoring PhD students. Based in Munich, he maintains an active transatlantic presence through his ongoing Rice affiliation, reflecting a rare blend of European and US academic leadership.
10 years of coding experience
9 years of employment as a software developer
Dr. sc., Information Technology and Electrical Engineering, Signal Processing, Machine Learning, Dr. sc., Information Technology and Electrical Engineering, Signal Processing, Machine Learning at Eidgenössische Technische Hochschule ZürichMS, Electrical Engineering, MS, Electrical Engineering at Universität Ulm
Github Skills (18)
reed-solomon9
language-model9
error-correction9
signal-processing8
inverse7
synthetic-dataset-generation5
synthetic-data4
python4
deep-learning3
fine-tuning3
natural-language-processing3
data-extraction3
machine-learning3
neural-network3
llm2
Programming languages (4)
Github contributions (5)
reinhardh/dna_rs_coding
Feb 2019 - Mar 2021
Error correction scheme for storing information on DNA using Reed Solomon codes
Contributions:28 commits, 12 pushes, 5 comments in 2 years 1 month
error-correctionreed-solomon
reinhardh/supplement_deep_denoising
Apr 2018 - Mar 2020
Contributions:4 commits, 2 pushes in 1 year 10 months
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