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.
9 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 (12)
inverse8
synthetic-dataset-generation5
machine-learning4
synthetic-data4
natural-language-processing4
prompt4
python4
deep-learning3
fine-tuning2
pytorch1
double1
llm1
Programming languages (3)
Github contributions (5)
reinhardh/supplement_deep_denoising
Apr 2018 - Mar 2020
Contributions:4 commits, 2 pushes in 1 year 10 months
reinhardh/deep_inverse_workshop
Jul 2019 - Dec 2021
Website of the NeurIPS Deep Inverse 2019 Workshop
Contributions:56 commits, 48 pushes in 2 years 5 months
neuripsinverseworkshop
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