Halimi A.

End-to-end design and development of an automated and intelligent extraction engine (POC) to analyze complex graphic files (industrial packaging files) and extract critical business data.

Main tasks:

- Benchmark & Architecture: Technical feasibility study and selection of the best approaches.

- Advanced image processing: Creation of an image cleaning and preprocessing pipeline.

- Complex data extraction: Automated extraction and decoding of textual item codes, barcodes (EAN/GENCOD), and Datamatrix codes.

- Reasoning & Business Rules: Integration of external data flows (parsing of source XML/CSV files) to apply validation and compliance rules per client.

- Data structuring: Normalization and serialization of extracted results into a structured and standardized XML format.

Developed a complete solution for automated identity document analysis:

Implemented an OCR Tesseract pipeline in Go, optimized by computer vision preprocessing.

Integrated vision-language models (VLM) via Nanonets to assist OCR in identifying areas of interest.

Developed and industrialized Faster R-CNN face detection models with fine-tuning for reliable facial region localization.

Developed predictive models as part of the Prognos® program to anticipate the degradation of critical Air France-KLM fleet systems.

Collaborated with business experts to transform technical signals into actionable indicators.

On-premise industrialization of a predictive maintenance solution applied to the air conditioning system of the Boeing 777.