I'm Mohamed, a Geomatics Engineering graduate from the Faculty of Engineering, Shoubra, Benha University, specializing in GeoAI — where satellite data meets machine learning.

My academic journey focused on geomatics disciplines such as photogrammetry, GIS, and remote sensing, which I actively integrate with hands-on AI experience in computer vision, deep learning, and spatial analytics to address complex geospatial challenges.

🎯 My Mission: Pioneer AI-first geomatics solutions — building intelligent, context-aware systems that transform raw spatial data into actionable insights, from real-time sensor fusion to location-aware AI applications.

🎓 Current Status: Geomatics Engineering graduate (2026) 💼 Experience: AI Intern @ Samsung Innovation Campus | Freelance Geomatics Engineer | NTI AI Trainee

Aug 2025 – Nov 2025 | Remote

Selected for a 4-month intensive AI residency, developing intelligent systems using:

• 🧠 Deep Learning & Computer Vision
• 🏥 Healthcare AI: Built an end-to-end heart-disease detection model from 12-lead ECG signals
• 🎯 Focus: Building AI that makes a tangible, real-world difference

Skills: Machine Learning, Deep Learning, Computer Vision, Healthcare AI, xLSTM

Jul 2025 – Aug 2025 | Al Qalyubiyah, Egypt (Remote)

• 📊 Converted 3D point cloud data from Mobile Mapping Systems (MMS) into precise CAD layouts
• 🎯 Performed feature extraction and created detailed technical drawings (buildings, line/point features)
• 🧹 Cleaned and processed point cloud data for optimal model creation
• ✅ Ensured accuracy and precision of 3D models per project specifications and industry standards

Skills: Mobile Mapping, Feature Extraction, Point Cloud Processing, CAD

Oct 2021 – Jun 2026 | Benha University

Graduated with a degree at the intersection of geospatial technologies, AI, computer vision, and spatial data science. Specialized in:

• 📸 Photogrammetry & UAV-based 3D modeling
• 🛰️ Remote Sensing & SAR image processing
• 🤖 AI-driven geospatial intelligence
• 🌍 Graduation project: automated Sentinel-1 SAR flood mapping for the Nile Floodplain (NRIAG)

Skills: Geospatial Data, GIS, Remote Sensing, Photogrammetry, GNSS, Image Processing, AI, Computer Vision, Spatial Data Science

Graduation Project — 2026 | Faculty of Engineering, Shoubra

Interactive web application for rapid flood mapping and analysis using Sentinel-1 Synthetic Aperture Radar (SAR) data. Leverages Google Earth Engine (GEE) for cloud-based processing and Streamlit for a user-friendly interface.

Key Features:

• 🌊 Automated Flood Detection: Refined Lee speckle filtering + Otsu automatic thresholding
• 🏔️ Topographic Correction: SRTM elevation data integration to mask high-slope areas (>5°), reducing false positives
• 🗺️ Interactive Analysis: Custom ROI definition via GeoJSON/Shapefile upload or coordinate input
• 📊 Real-time Statistics: On-the-fly calculation of total flooded area and ROI coverage
• 💾 Data Export: Export of flood masks (GeoTIFF) and vectorized polygons (Shapefile) to Google Drive

Tech Stack: Python, Google Earth Engine, Streamlit, Sentinel-1 SAR, SRTM

Impact: Enables rapid disaster response and flood-extent quantification for the Nile Floodplain

Nov 2025 | Samsung Innovation Campus Graduation Project

Healthcare AI system for multi-label ECG classification using a novel xLSTM architecture.

Key Achievements:

• 🧠 Implemented a parallel xLSTM architecture combining sLSTM and mLSTM branches for enhanced temporal pattern recognition
• 🔊 Built a complete signal preprocessing pipeline with bandpass and notch filtering
• 🌐 Built an interactive Streamlit web application for real-time ECG classification
• 👤 Integrated patient metadata (age, sex) for improved prediction accuracy
• 📚 Open-sourced with comprehensive documentation

Tech Stack: PyTorch, PyTorch Lightning, xLSTM, WFDB, Streamlit, NumPy, Pandas, SciPy, Scikit-learn

Jul – Aug 2025 | Freelance Project

Automated workflow for converting Mobile Mapping System data into precise CAD layouts with high-precision feature extraction.

Key Features:

• 🎯 Convert 3D point cloud data from MMS into precise CAD layouts
• 🔍 Automated feature extraction from point cloud data
• 🧹 Point cloud cleaning and optimization for model creation
• ✅ Industry-standard accuracy and precision compliance

Tech Stack: Point Cloud Processing, CAD, Feature Extraction, Mobile Mapping Systems

• 🔭 Working on: a self-directed study plan covering applied Machine Learning and Deep Learning fundamentals
• 🌱 Learning: NumPy/Pandas for ML, applied Machine Learning fundamentals
• 👯 Looking to collaborate on: GeoAI, Remote Sensing, and Computer Vision projects
• 💬 Ask me about: Geomatics, Machine Learning, Google Earth Engine, SAR Analysis, Photogrammetry
• ⚡ Fun fact: I transform pixels into insights and coordinates into intelligence!

• 🎓 Geomatics Engineering Graduate — Faculty of Engineering, Shoubra, Benha University (2021–2026)
• 🏅 Huawei HCIA-AI V4.0 Certified — Issued Feb 2026, valid through Feb 2029
• 🏅 Samsung Innovation Campus AI Program — Selected participant (Aug–Nov 2025)
• 💯 NTI AI Training Track — Perfect assessment score (100%), 80-hour track (Jan–Feb 2025)
• 💼 Freelance Geomatics Engineer — 3D Point Cloud & CAD expertise (Jul–Aug 2025)
• 🧠 Healthcare AI Development — xLSTM-based ECG multi-label classification system
• 🌊 Disaster Monitoring — SAR-based flood mapping for the Nile Floodplain
• 📖 Open Source Contributor — Published research-quality code on GitHub

Programming & ML/DL: PyTorch • PyTorch Lightning • TensorFlow • Keras • Scikit-learn • OpenCV • Deep Learning • Machine Learning • Computer Vision • xLSTM • Time Series Analysis

Geospatial Technologies: GeoAI • Remote Sensing • Google Earth Engine • QGIS • ArcGIS • Photogrammetry • SAR Processing • Sentinel-1 • SRTM • Mobile Mapping • Point Cloud Processing • CAD • Feature Extraction • GNSS

Data Science & Development: Python • Pandas • NumPy • SciPy • Streamlit • Jupyter • WFDB • Signal Processing • Data Visualization • Web Applications

Cloud & DevOps: Git • Docker • AWS • Google Drive Integration