Arber Zela
Postdoctoral Researcher at ELLIS Institute Tübingen
Freiburg im Breisgau, Baden-Württemberg, Germany
Summary
🤩
Rockstar🎓
Top SchoolArber Zela is a postdoctoral researcher and AutoML specialist with a decade of experience focused on Automated Deep Learning, particularly Neural Architecture Search and hyperparameter optimization. He completed a PhD at the University of Freiburg and has held research positions at ELLIS, Oxford, Samsung, and now EPFL, blending academic rigor with industry-facing internships. A hands-on contributor to NASLib, he expanded the library with DARTS and NAS-Bench-1Shot1 search spaces and implemented mixed operation and cell structures, making NAS research more accessible. Based in Freiburg, Germany, he combines deep theoretical knowledge with practical engineering—often surfacing reproducible, runnable examples—and has a background bridging electrical engineering and computer science that informs his systems-oriented approach.
9 years of coding experience
2 years of employment as a software developer
Master's degree Computer Science, Master's degree Computer Science at The University of FreiburgBachelor of Science - BS Electrical and Electronics Engineering, Bachelor of Science - BS Electrical and Electronics Engineering at Universiteti Politeknik i Tiranës
Github Skills (10)
pytorch10
machine-learning10
deep-learning10
python10
nas10
neural-architecture-search10
automl9
github9
lstm9
linear-algebra7
Programming languages (4)
Github contributions (5)
automl/NASLib
May 2019 - Jun 2022
NASLib is a Neural Architecture Search (NAS) library for facilitating NAS research for the community by providing interfaces to several state-of-the-art NAS search spaces and optimizers.
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 1 review, 272 commits in 3 years 1 month
Contributions summary:Arber's commits primarily focus on the development and integration of Neural Architecture Search (NAS) capabilities within the NASLib library. This includes adding new search spaces, specifically DARTS and NAS-Bench-1Shot1, which expands the library's functionality. The user implemented mixed operation and cell structures. Also, contributions include fixing bugs in existing code and providing runnable examples.
artnasneural-architecture-searchstate-of-the-artmachine-learning
automl/nes
Jun 2020 - Nov 2021
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift
Contributions:7 commits, 1 PR, 5 pushes in 1 year 5 months
shiftdatasetensembleestimationuncertainty
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