Stephan Gabler
Founder at Neupitz
Berlin, Germany
Summary
👤
Senior🎓
Top SchoolStephan Gabler is a Berlin-based founder and full-stack developer with 16 years of experience bridging computational neuroscience, data science, and product engineering. He has led startups and tech teams as CTO and founder while shipping production web and CLI tools as a freelance developer, combining algorithmic rigor with pragmatic engineering. Early research roles at Max Planck and BCCN honed his expertise in large-scale topic modeling and cognitive data analysis, contributions that include model work and tests for the popular gensim library. Comfortable across backend, frontend and ML stacks, he’s delivered features from encrypted journaling and markdown export to scalable TF-IDF and log-entropy models. Now seeking a new, meaningful mission, he offers a rare mix of research-grade modeling experience and hands-on product delivery.
16 years of coding experience
14 years of employment as a software developer
Master of Science (M.Sc.), Computational Neuroscience, Master of Science (M.Sc.), Computational Neuroscience at BCCN BerlinBachelor of Science (B.Sc.), Cognitive Science, Bachelor of Science (B.Sc.), Cognitive Science at Universität Osnabrück
Hebrew, German, English
Github Skills (16)
machine-learning10
gensim10
topic-modeling10
nlp10
topic-models10
python10
encryption10
natural-language-processing10
data-science10
command-line10
word-embeddings9
markdown-it9
markdown9
json9
cli8
Programming languages (11)
Github contributions (5)
jrnl-org/jrnl
Apr 2012 - Nov 2014
Collect your thoughts and notes without leaving the command line.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:36 commits, 1 comment in 2 years 7 months
Contributions summary:Stephan primarily focused on enhancing the `jrnl` command-line journal application. Their contributions include implementing features like password-based encryption using the PyCrypto library, enabling markdown support for journal entries, and adding options for exporting journals to JSON and Markdown formats. Furthermore, the user improved the user experience by incorporating features like autocompletion for the journal file path during setup and implementing a "short" option for displaying only entry titles.
notespythonjournal-applicationcollectnote-taking
piskvorky/gensim
Feb 2011 - Jun 2011
Topic Modelling for Humans
Role in this project:Data Scientist
Data ScientistContributions:17 commits in 4 months
Contributions summary:Stephan primarily contributed to model development and experimentation within the gensim library. Their work included saving and loading TF-IDF models and implementing a LogEntropyModel. They also developed a function to compare paragraphs of text (para2para) and integrated it into the library's utility functions, including unit tests for the function. Finally, the user added a test suite that reproduces the results of Lee et al. (2005).
pythonword-similarityword-embeddingsdata-miningfor-humans
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