Daniel Beutel
Co-Founder & CEO at Flower Labs
Germany
Summary
🤩
Rockstar🎓
Top SchoolDaniel Beutel is a founder and CEO with 11 years of engineering and leadership experience building privacy-preserving ML systems and production-grade software. He co-created Flower, a widely used federated learning framework, and has hands-on expertise as an ML engineer and backend developer contributing TensorFlow examples, gRPC integrations, and tooling to the project. His career spans startups and research—co-founding Adap and Flower Labs, serving as Head of AI/Interim CTO at XAIN where his work shifted the company toward distributed learning, and conducting research as a visiting scholar at the University of Cambridge while pursuing a PhD. Comfortable moving between strategy and code, he combines product vision, system architecture, and open-source craftsmanship, with a background in software engineering from Oxford and business informatics that supports both technical depth and commercial execution.
11 years of coding experience
9 years of employment as a software developer
Bachelor of Science (BSc) Business Informatics, Bachelor of Science (BSc) Business Informatics at Baden-Wuerttemberg Cooperative State University (DHBW)Master’s Degree Software Engineering, Master’s Degree Software Engineering at University of OxfordDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Cambridge
English, German
Github Skills (7)
machine-learning10
deep-learning10
tensorflow10
python10
federated-learning10
grpc10
develop9
Programming languages (9)
Github contributions (5)
adap/flower
Feb 2020 - Jan 2023
Flower: A Friendly Federated AI Framework
Role in this project:
ML Engineer & Backend Developer
ML Engineer & Backend DeveloperContributions:11 releases, 3925 reviews, 726 commits in 2 years 11 months
Contributions summary:Daniel contributed to the MNIST example by adding a strategy and improving logging. They also moved the TensorFlow MNIST example to a sub-package, introducing a starter script, and made various scripts executable. The code changes, along with the repository description and topics, indicate a focus on developing machine learning solutions with a federated learning framework, especially with tools such as TensorFlow and GRPC.
federated-analyticsfederated-learning-frameworkmachine-learningkeras-federated-learningflower
danieljanes/algorithmics
Jan 2019 - Apr 2020
Contributions:27 commits, 19 pushes, 1 branch in 1 year 3 months
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