Erel Segal-halevi
Lecturer at Ariel University
Israel
Summary
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Rockstar🎓
Top SchoolErel Segal-halevi is a lecturer and machine learning engineer with 13 years of experience building algorithms and back-end systems, currently teaching at Ariel University in Israel. His background spans academic research (PhD candidate at Bar-Ilan) and hands-on industry roles from senior algorithm engineering to simulation development in defense and startups. He contributed notable open-source work on limdu, implementing Bayesian and multi-label classifiers and feature extractors for machine learning in Node.js. Comfortable bridging theory and practice, he has a track record of turning research-grade models into production-ready infrastructure. Colleagues describe him as a pragmatic developer-academic who navigates both classroom, research, and engineering constraints effectively.
13 years of coding experience
13 years of employment as a software developer
Teacher, Teacher at Technion - Israel Institute of TechnologyDoctor of Philosophy - PhD, Doctor of Philosophy - PhD at Bar-Ilan University
Stackoverflow
35,355reputation
6.4mreached
52answers
305questions
json
top-1%
sorting
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Github Skills (15)
json10
multilabel-classification10
machine-learning10
nodejs10
javascript10
python10
classification10
java9
sorting9
concatenation6
html6
collections6
stl6
jquery6
pypi6
Programming languages (20)
Github contributions (5)
erelsgl/limdu
Jun 2013 - Apr 2022
Machine-learning for Node.js
Role in this project:
Back-end Developer & Data Scientist
Back-end Developer & Data ScientistContributions:300 commits, 14 PRs, 38 pushes in 8 years 11 months
Contributions summary:Erel primarily contributed to the development of machine learning models and the underlying back-end infrastructure for the project. Their work involved implementing and integrating classifiers, specifically focusing on Bayesian models. They were responsible for defining and utilizing feature extractors to improve classification accuracy. Additionally, the user designed and implemented a multi-label classification system to handle multiple labels per sample.
node-jsnodejsmachine-learningtensorflow
erelsgl-at-ariel/algorithms-5782
Jun 2021 - Mar 2022
Contributions:67 commits, 44 pushes, 1 branch in 8 months
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