Ivan Kabadzhov is a PhD-level data science researcher and software engineer with 7 years of experience applying C++ development, performance optimization, and distributed systems techniques to scientific data workflows. Currently a doctoral student at EURECOM with research stints at CERN and Japan’s National Institute of Informatics, he has scaled ROOT's distributed dataframe to thousands of HPC nodes and implemented NUMA-aware, multi-threaded execution and dataset metadata features. He pairs strong systems engineering and test automation skills—demonstrated by contributions to the flagship ROOT project—with hands-on network traffic measurement and analysis from long-running MAWI datasets. Based in Antibes, France, he also brings teaching experience in algorithms and operating systems, and a track record of turning low-level profiling insights into robust, test-covered features.
7 years of coding experience
Doctor of Philosophy - PhD, Doctor of Philosophy - PhD at Sorbonne Université
Master of Science - MS, Master of Science - MS at The University of Freiburg
Bachelor of Science - BS, Bachelor of Science - BS at Jacobs University Bremen
The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
Role in this project:
Back-end Developer & Test Automation Engineer
Contributions:287 reviews, 105 commits, 86 PRs in 1 year 2 months
Contributions summary:Ivan primarily focused on improving the functionality of the RDisplay class within the ROOT project. Their commits involved modifying the `RDisplay::Print` method to list a custom number of elements from collections and adding new tests to check the behavior of wide tables. The user also implemented changes to the `RDisplay` class by improving the pretty Print and AsString, including the addition of a custom column "rdfentry_" and displaying dashes between entries. Furthermore, the user contributed to the testing suite, adapting and expanding test cases to ensure the correctness of the new features.
The official repository for ROOT: analyzing, storing and visualizing big data, scientifically
Contributions:438 pushes, 84 branches in 1 year 2 months
analyzingdata-analysispythondata-sciencestoring
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