I'm Mohamed, a Geomatics Engineering student at the Faculty of Engineering, Shoubra, with a strong passion for computer vision, machine learning (ML), and deep learning (DL). My academic journey has focused on geomatics disciplines such as photogrammetry, GIS, and remote sensing.

Through self-directed learning, I've developed a solid foundation in CV, ML, and DL, which I actively integrate with traditional spatial methods to address complex geospatial challenges.

🎯 My Mission: Pioneer AI-first geomatics solutions, including real-time sensor fusion systems and self-training models for adaptive spatial analytics—transforming raw data into intelligent, context-aware insights.

🎓 Current Status: Final year Geomatics Engineering student at Shoubra
💼 Experience: AI Intern @ Samsung Innovation Campus | Freelance Geomatics Engineer

Aug 2025 - Nov 2025 | Remote

Awarded a place in the Samsung Innovation Campus AI Program, where I developed intelligent systems using:

• 🧠 Deep Learning & Computer Vision
• 💬 Natural Language Processing (NLP)
• 🏥 Healthcare AI: Created a heart-disease detection model from ECG signals for smarter medical decision-making
• 🎯 Focus: Building AI that makes a tangible difference

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

Jul 2024 - Aug 2024 | 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
• 🧹 Cleaned and processed point cloud data for optimal model creation
• ✅ Ensured accuracy and precision of 3D models per project specifications and industry standards
• 🤝 Collaborated with cross-functional teams for timely project delivery

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

Oct 2021 - Present | 4 years 3 months

Pursuing a degree where geospatial technologies intersect with AI, computer vision, and spatial data science. Specializing in:

• 📸 Photogrammetry & LiDAR
• 🛰️ Remote Sensing & Image Processing
• 🤖 AI-driven geospatial intelligence
• 🔬 Transforming raw spatial data into real-time knowledge
• 🌍 Applying AI to reveal concealed geospatial imagery trends

Long-term goal: Contributing to trailblazing solutions that combine geomatics and intelligent systems to address real-world challenges.

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

Nov 2025 | Associated with Samsung Innovation Campus

Advanced healthcare AI system for multi-label ECG classification using state-of-the-art xLSTM architecture.

Key Achievements:

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

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

Impact: Supports smarter medical decision-making through intelligent ECG diagnostics

Oct 2025 | Associated with 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 user-friendly interface.

Key Features:

• 🌊 Automated Flood Detection: Robust workflow with Refined Lee speckle filtering and Otsu's 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: Seamless export of flood masks (GeoTIFF) and vectorized polygons (Shapefile) to Google Drive

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

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

Jul-Aug 2024 | Freelance Project

Automated workflow for converting Mobile Mapping System data to 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

Impact: Streamlined geospatial data processing for engineering projects

• 🔭 Working on: AI-driven geospatial solutions for disaster monitoring .
• 🌱 Learning: Advanced xLSTM architectures, SAR image processing, and sensor fusion systems
• 👯 Looking to collaborate on: GeoAI, Remote Sensing, and Computer Vision projects
• 💬 Ask me about: Geomatics, Machine Learning, Google Earth Engine, Point Cloud Processing, LiDAR, Photogrammetry, SAR Analysis
• ⚡ Fun fact: I transform pixels into insights and coordinates into intelligence!

• 🎓 Final Year Geomatics Engineering Student - Faculty of Engineering, Shoubra (2021-Present)
• 🏅 Samsung Innovation Campus AI Program - Selected participant (Aug-Nov 2025)
• 💼 Freelance Geomatics Engineer - 3D Point Cloud & CAD expertise (Jul-Aug 2024)
• 🧠 Healthcare AI Development - xLSTM-based ECG multi-label classification system
• 🌊 Disaster Monitoring - SAR-based flood mapping for Nile Floodplain
• 🗺️ Mobile Mapping Systems - Professional experience in MMS data processing
• 📖 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 • NLP • xLSTM • Time Series Analysis

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

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

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