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mguechaoui/README.md

Mohamed Guechaoui

Engineer & Researcher — Computer Vision · Deep Learning · Document AI

LinkedIn Email Portfolio CV

Engineering Degree + Master's, Artificial Intelligence & Data Science — École Supérieure en Informatique (ESI), Sidi Bel Abbès, Algeria (Jul 2026).

Open to PhD positions and permanent (CDI) roles, in computer vision, document AI, and applied deep learning.


📄 Publications

Paper Status Draft
AraMS-28k — The Largest Publicly Released Line-Level Dataset of Historical Arabic Manuscripts, with Margin and Insertion-Anchor Annotations arXiv submission in progress Request draft
RefLAM — A Reference-Grounded Line Annotation Pipeline for Historical Arabic Manuscripts arXiv submission in progress Request draft

(Both papers are currently in preparation with co-authors. Drafts are available directly — see links above or contact me — while the arXiv submission is finalized.)


🧪 Projects

AraMS-28k & RefLAM — Historical Arabic Manuscript Dataset & Annotation Pipeline

multimodal LLMs OCR alignment weak supervision document layout analysis

Built a reference-grounded annotation pipeline (RefLAM) that aligns multimodal-LLM OCR against independently sourced clean transcriptions, and used it to construct AraMS-28k — the largest publicly released line-level dataset of genuine historical Arabic manuscripts (14 books, 3,043 pages, 28,600 lines, three script traditions). Introduced the first publicly released line-level insertion-anchor annotation, recovering non-linear main/margin reading order. Proved a formal correctness guarantee (the Confidence-100 rule) achieving a 75× annotation throughput gain over manual review, with zero errors found on independent audit. 📦 Repository · 📄 See Publications above

Enhanced TEVAD — Multi-modal Video Anomaly Detection

PyTorch Transformers OpenCV video understanding

Led a 5-person team extending the TEVAD baseline for video anomaly detection through architectural refinements and improved multi-modal fusion, evaluated on UCF-Crime subsets. 📦 Repository · 📊 AUC 98.6% → 99.2%, 11× faster convergence · 📄 Technical report

LLM Data Analysis Automation

GPT FastAPI React NL-to-SQL

Built a natural-language interface for querying structured datasets conversationally, via a multi-stage pipeline (intent classification → SQL generation → validation → interpretation), with automated data profiling to flag anomalies and inconsistent distributions. 🔗 Live system · 📊 Validated on 100+ real-world datasets

Chest X-Ray Classification

PyTorch ResNet MobileNet transfer learning

Classified COVID-19, pneumonia, and normal chest X-rays using transfer learning with data augmentation and class balancing, deployed as an interactive demo. 🔗 Live demo · 📦 Repository · 📊 F1 0.93, ROC-AUC 90.22%


🛠️ Skills

Document & Image Analysis: Handwritten Text Recognition (HTR) · OCR-reference alignment · layout analysis · image restoration · Kraken · HATFormer Deep Learning & Computer Vision: PyTorch · TensorFlow · OpenCV · Vision Transformers · Multimodal LLMs · generative models NLP: Transformers · BERT variants · CLIP · GPT models · Hugging Face ecosystem Engineering: Python · SQL · Git · Docker · Linux · Weights & Biases Languages: Arabic (Native) · French (B2) · English (Professional)


📫 Reach out about research collaboration, PhD opportunities, or roles in document AI / computer vision.

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  1. ArchaText/AraMS-28k-Dataset ArchaText/AraMS-28k-Dataset Public

    The largest publicly released line-level dataset of historical Arabic manuscripts — 14 books, 3,043 pages, 28,600 lines, with margin/insertion-anchor annotations for non-linear reading order.

    Python 1

  2. ArchaText/Reflam-pipeline ArchaText/Reflam-pipeline Public

    Reference-grounded annotation pipeline for historical manuscripts — MLLM OCR + fuzzy alignment against clean transcriptions, with a provable confidence-100 correctness guarantee.

    HTML

  3. Enhanced-TEVAD/Enhanced-Tevad Enhanced-TEVAD/Enhanced-Tevad Public

    Enhanced TEVAD framework with improvements to the Multimodal Transformer Network (MTN) for better fusion of video features and textual embeddings, leading to more accurate temporal anomaly detectio…

    Python 1

  4. ChestXray_Finetuned_ResNet_MobileNet ChestXray_Finetuned_ResNet_MobileNet Public

    Fine-tuning ResNet18 and MobileNetV2 on the Chest X-ray dataset to detect pneumonia.

    Python