Benjamin Bengfort
Founder And CEO at Georgetown University
Saint Paul, Minnesota, United States
Summary
🤩
Rockstar🎓
Top SchoolBenjamin Bengfort is a founder and CEO with 13+ years designing distributed systems, machine learning, and NLP solutions that scale to large user bases. He balances academic rigor—PhD research in planetary-scale data systems and teaching applied data science at Georgetown—with hands-on engineering, contributing to open-source projects like Yellowbrick (a NumFOCUS-affiliated ML visualization library) and improving Python tooling such as memory_profiler. His career spans startups and academia, building recommender systems, streaming analytics, and smart IoT applications while emphasizing human-machine intelligence and knowledge sharing. Based in Saint Paul, he leads Rotational Labs and maintains a practical focus on developer experience and diagnostics for ML workflows. Notably, he authored two O’Reilly books and frequently presents at conferences like PyCon and PyData, reflecting a talent for translating complex systems into usable tools and teaching.
13 years of coding experience
NA, NA at United States Naval AcademyDoctor of Philosophy (PhD), Doctor of Philosophy (PhD) at University of MarylandUMBCM.S, M.S at North Dakota State University
Stackoverflow
5,332reputation
902kreached
20answers
24questions
python-multiprocessing
top-5%
django
top-5%
django-rest-framework
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python
top-5%
Github Skills (29)
data-visualizations10
python10
scikit10
k-means-clustering10
machine-learning10
data-visualisation10
python-multiprocessing10
tsne10
scikit-learn10
memory-profiling10
multiprocessing10
multi-process10
data-visualization10
django9
psutil9
Programming languages (16)
Github contributions (5)
DistrictDataLabs/yellowbrick
May 2016 - Aug 2022
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Role in this project:
Data Scientist
Data ScientistContributions:17 releases, 78 reviews, 346 commits in 6 years 4 months
Contributions summary:Benjamin's commits show that they were involved in adding examples of visual diagnostics using the Yellowbrick library. The specific examples include a t-SNE projection, a frequency distribution plot, and the application of K-means clustering to project data onto a lower-dimensional space. This suggests that the user was engaged in feature analysis and visualization to better understand the structure of the data and relationships among classes for potential machine learning applications.
pythonvisual-analysisvisualizermodel-selectionmachine-learning
pythonprofilers/memory_profiler
Jul 2016 - Mar 2017
Monitor Memory usage of Python code
Role in this project:Back-end Developer
Back-end DeveloperContributions:9 commits, 1 PR, 22 comments in 8 months
Contributions summary:Benjamin primarily focused on enhancing the `memory_profiler` tool's capabilities, specifically improving the tracking of memory usage in child processes. Their contributions involved modifying the core `memory_profiler.py` script to separately record memory for child processes and integrating these changes into the `mprof` utility. Furthermore, the user merged updates from the upstream repository and improved the documentation. These modifications suggest a focus on expanding the tool's functionalities and overall user experience.
python-codememorymemory-usagepythonmonitor
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