Johann Dreo is an expert research engineer based in Paris with 17 years of experience at the intersection of AI, computational biology, and optimization. Currently at Institut Pasteur, he applies advanced bioinformatics and systems biomedicine methods while maintaining a long-running role as an open-source developer and maintainer of ParadisEO, an evolutionary computation framework. His background spans robotics, planning, stochastic optimization, and parallel computing from senior research roles at Thales to academic postdoc work on hospital operations and swarm intelligence. A maker and illustrator by inclination, he contributes practical tooling to the community—examples include UI and theming improvements for popular CLI projects like liquidprompt and colout—reflecting a rare blend of rigorous research, production-quality engineering, and design sensibility.
16 years of coding experience
17 years of employment as a software developer
Master’s degree, Evolution, ethology and ecology, Master’s degree, Evolution, ethology and ecology at Université de Rennes I
A full-featured & carefully designed adaptive prompt for Bash & Zsh
Role in this project:
Full-stack Developer
Contributions:105 reviews, 374 commits, 46 PRs in 12 years 1 month
Contributions summary:Johann appears to have focused on improving the user interface and functionality of the shell prompt. Their contributions include refactoring the prompt's construction, adding comments, and incorporating features such as version control system (VCS) support (Git, Mercurial, Subversion), and display of various system information (battery status, load average). The user also added support for theming and the capability to customize the prompt's layout and features.
Color text streams with a polished command line interface
Role in this project:
Full-stack Developer
Contributions:2 releases, 169 commits, 20 PRs in 10 years 6 months
Contributions summary:Johann significantly contributed to the `colout` project, enhancing its functionality and usability. They refactored the original code to incorporate Python, improved argument handling, and fixed several bugs related to the program's core logic. The user also added more features, like support for source code coloring, and implemented new themes to tailor to different situations, and changed the way the source code is managed.
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