Ing Rüb
Founder at EnBW
Villingen-Schwenningen, Baden-Württemberg, Germany
Summary
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Top SchoolIng Rüb is an AI and TinyML specialist with eight years of experience bridging research and industry, currently founding ForestHub.ai while driving AI strategy at EnBW. He develops and deploys efficient on-device learning algorithms for resource-constrained hardware (MCUs, FPGAs, TPUs), has led publicly funded projects up to €1M, and holds deep expertise in sparse training, continual learning and model compression. As a PhD researcher and former Head of AI, he combines hands-on implementation in Python/C/C++/VHDL and frameworks like PyTorch and TensorFlow with product-minded leadership in data platforms and NLP. He teaches TinyML and Deep Learning, mentors students, and helps run TinyML Germany, reflecting a strong commitment to community and technology transfer. Notably, his research contributions (e.g., DRIP and TinyProp) focus on making on-device training practical by cutting computation, memory and labeling costs.
7 years of coding experience
5 years of employment as a software developer
Ausbildung, Systemelektroniker, Ausbildung, Systemelektroniker at Staatliche Feintechnikerschule Schwenningen mit TGDr. Ing, Machine learning, Dr. Ing, Machine learning at Technical University of MunichMaster of Science - MS, Mechatronik, Robotik und Automatisierungstechnik, Master of Science - MS, Mechatronik, Robotik und Automatisierungstechnik at Hochschule Furtwangen
Github Skills (8)
autoencoder9
pruning9
optimization7
deep-learning6
machine-learning6
artificial-intelligence6
tensorflow6
python6
Programming languages (3)
Github contributions (5)
Hahn-Schickard/Automatic-Structured-Pruning
Nov 2020 - Jun 2022
We have implemented a framework that supports developers to structured prune neural networks of Tensorflow Models
Contributions:38 commits, 5 PRs, 35 pushes in 1 year 7 months
autoencoderstructuredpruningdeep-learningneural-networks
r1marcus/Fundamentals-of-Deep-Learning-HFU
Dec 2020 - May 2021
Contributions:6 commits, 5 pushes, 1 branch in 4 months
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