Blaz Zupan
Professor at Revelo.ai
Ljubljana, Slovenia
Summary
🤩
Rockstar🎓
Top SchoolBlaz Zupan is a professor and machine learning researcher with 23 years of experience who bridges academia and industry from Ljubljana to Houston, leading a 20-member lab that builds the popular Orange Data Mining platform. He specializes in explainable AI, interactive data visualization, and democratizing data science through intuitive UIs and open-source tools, and his hands-on contributions to Orange (including feature scoring and core backend work) show deep familiarity with ML internals. As co-founder of Revelo and advisor to Genialis, he helps translate cutting-edge computational biology and explainable ML into practical solutions for competitive industries. He teaches widely-used, practice-oriented courses and innovates pedagogy by embedding research-grade tools into classroom and workshop settings. An active researcher with expertise spanning feature construction, bioinformatics, and explainability, he combines rigorous academic training with product-minded delivery.
23 years of coding experience
5 years of employment as a software developer
BSc Computer Science, BSc Computer Science at University of HoustonPhD Computer Science, PhD Computer Science at University of Ljubljana
slovene, English, Croatian
Stackoverflow
1,423reputation
326kreached
3answers
0questions
numpy
top-5%
max
top-5%
python
top-5%
Github Skills (19)
python10
data-science10
data-mining10
machine-learning10
numpy10
classification9
scikit9
max9
scikit-learn9
computer-engineering9
unit-testing7
data-visualizations7
data-visualisation7
data-visualization7
text-mining6
Programming languages (8)
Github contributions (5)
biolab/orange2
Mar 2003 - Jan 2015
DEPRECATED: Orange 2 (Python 2) data mining suite. NEW: https://github.com/biolab/orange3
Role in this project:
Backend Developer
Backend DeveloperContributions:656 commits, 4 pushes in 11 years 11 months
Contributions summary:Blaz primarily focused on the maintenance, modification, and extension of the Python 2-based Orange data mining suite. Their contributions involved implementing and refining core functionalities, as evidenced by the addition of new methods for discretization, handling weights and correcting bugs, in existing files. Their work also involved the creation of new modules, and adjustments to existing ones, demonstrating a solid understanding of the suite's internal structure and intended operation. The user appears to be involved in fixing the issues and modifying core of the package.
data-analysispythonminingorangedata-science
biolab/orange3
Feb 2012 - Dec 2022
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Role in this project:Data Scientist
Data ScientistContributions:199 commits, 165 PRs, 115 pushes in 10 years 11 months
Contributions summary:Blaz primarily contributed to the `Orange3` repository by implementing feature scoring metrics and integrating them into the existing framework. Their work involved the creation of classes for Information Gain, Gain Ratio, and Gini scoring methods, alongside associated unit tests. They also addressed domain-specific issues by incorporating domain checking and NaN value adjustments within the feature scoring algorithms. Furthermore, the user added and reorganized documentation and added feature scoring for classification problems.
orangepythondata-miningorange3scipy
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