Lorenz Diener
Senior Machine Learning Scientist at Microsoft
Tallinn, Harju County, Estonia
Summary
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Rockstar🎓
Top SchoolLorenz Diener is a Senior Machine Learning Scientist at Microsoft in Tallinn with 16 years of engineering and research experience bridging academia and industry. He holds a magna cum laude PhD in computer science from Universität Bremen where he worked on converting EMG signals to audible speech, and now focuses on improving communication with ML and exploring generative models for creative image synthesis. Lorenz pairs deep research expertise with hands-on software craftsmanship—his open-source work includes foundational back-end development of a popular Mastodon Python API wrapper, where he implemented authentication flows and rate-limit handling. A hobbyist 3D artist, he brings an unusual blend of signal-processing rigor and visual creativity to product-focused ML problems.
16 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Informatik, Bachelor's degree, Informatik at Universität Karlsruhe (TH)Doctor of Science, Informatik, Magna cum laude, Doctor of Science, Informatik, Magna cum laude at Universität BremenMaster's degree, Informatik, Master's degree, Informatik at Karlsruher Institut für Technologie (KIT)
English, German
Github Skills (7)
api-rest10
python10
apidoc10
http-request10
api-client10
api9
mastodon9
Programming languages (9)
Github contributions (5)
halcy/Mastodon.py
Nov 2016 - Dec 2022
Python wrapper for the Mastodon ( https://github.com/mastodon/mastodon/ ) API.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:27 releases, 573 commits, 134 PRs in 6 years 1 month
Contributions summary:Lorenz's contributions primarily involve the initial setup and development of the Mastodon API wrapper in Python. They established the foundational structure of the wrapper, including class definition, methods for app registration and authentication, and functions for interacting with the API endpoints. Furthermore, the user made incremental improvements by cleaning up and refactoring the codebase and incorporating features like rate limit handling to enhance the wrapper's usability.
api-clientapisocial-networkpythonpython-wrapper
microsoft/PLC-Challenge
Jan 2022 - Oct 2022
This repo contains required files for the INTERSPEECH 2022 Audio Deep Packet Loss Concealment (PLC) Challenge.
Contributions:14 commits, 2 PRs, 19 pushes in 8 months
audiolosspacketplcpacket-loss
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