Adriano Pagano is a Senior Software Engineer with a decade of experience building reliable, maintainable systems across greenfield and legacy codebases, currently based in Lausanne and working at NIRLAB. He blends server-side engineering, data engineering, and cloud architecture—formerly serving as CTO at VIUN where he led the design and delivery of a multi-tenant SaaS for AI visual inspection and established engineering and security practices. His background includes high-throughput real-time ETL, IoT ingestion, healthcare and telecom diagnostics, and production-grade APIs, with hands-on work from bare metal to cloud. An active open-source contributor in the OCR space, he improved Tesseract integration and confidence reporting in pyocr, reflecting a practical focus on accuracy and data quality. Trained in systems biology (ETH Zurich), he brings analytical rigor and a product-minded approach that favors battle-tested technologies and long-term technical strategy.
10 years of coding experience
6 years of employment as a software developer
Master of Science (MSc), Systems Biology, Master of Science (MSc), Systems Biology at Eidgenössische Technische Hochschule Zürich
Bachelor of Science (BSc), Biology, General, Bachelor of Science (BSc), Biology, General at University of Lausanne (Switzerland)
Summer School in Bioethics, Summer School in Bioethics at University of Helsinki
A Python wrapper for Tesseract and Cuneiform -- Moved to Gnome's Gitlab
Role in this project:
Back-end Developer
Contributions:6 commits, 4 PRs, 11 comments in 15 days
Contributions summary:Adriano focused on enhancing the pyocr library, particularly in handling Optical Character Recognition (OCR) output. They improved the integration with Tesseract, adding features to propagate OCR confidence to the output and specifying the legacy model for Tesseract 4. The user also implemented support for calculating confidence measures within libtesseract, affecting the handling and reporting of OCR results, and refactored the code for flexibility. These changes directly improve the accuracy and completeness of OCR results provided by the library.
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