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Youssra1999/README.md

🚀 Youssra Abouelmawahib | Data Scientist

Hi, I'm Youssra Abouelmawahib, a Data Scientist with a deep passion for leveraging AI and Data Science to tackle real-world challenges.
I specialize in Geospatial Analytics (GIS) and Artificial Intelligence (AI), with a mission to drive innovation in climate change and sustainability.

I believe in data-driven impact, continuous learning, and pushing the boundaries of AI for environmental and societal benefit.
Passion, curiosity, and resilience fuel my journey.

🌍 Areas of Expertise

  • 🌐 GIS & Geospatial Data Science → Harnessing tools like Google Earth Engine, QGIS for environmental monitoring and spatial analytics.
  • 🤖 Artificial Intelligence & Machine Learning → Building intelligent systems to solve complex problems.
  • ♻️ AI for Climate & Sustainability → Developing models to monitor and mitigate climate impacts.
  • 🔒 Ethical AI → Advocating for responsible AI practices that benefit both people and the planet.

🔬 Current Research & Projects

  • 🌊 Inland Water Monitoring → Tracking water body dynamics using Google Earth Engine & Python.
  • 📊 Climate Data Analysis → Exploring large-scale climate datasets to extract actionable insights.
  • 🤖 AI & Code Generation → Investigating LLMs for automatic code generation and cybersecurity applications.

🛠️ Tech Stack & Tools

Python Scikit-learn PyTorch Google Earth Engine QGIS Power BI Google Cloud AWS

💡 Core Skills

  • Programming: Python, R, SQL
  • Machine Learning: Scikit-learn, PyTorch
  • Data Visualization: Matplotlib, Seaborn, Power BI
  • Geospatial Analytics (GIS): Google Earth Engine, QGIS
  • Cloud Platforms: AWS, Google Cloud

📈 GitHub Streak

GitHub Streak

🔥 Let's Connect

📧 Email: [email protected]
🌐 LinkedIn: linkedin.com/in/youssra
🔗 GitHub: github.com/YoussraAb

🚀 Always eager to collaborate and explore new research opportunities!

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  1. Gaussian-Process-Estimation-for-Unobserved-Temperature-Data Gaussian-Process-Estimation-for-Unobserved-Temperature-Data Public

    This project explores the application of Gaussian processes to estimate unobserved temperature data in Boston. We utilize Gaussian processes to model temperature variations, leveraging historical a…

    Jupyter Notebook

  2. Deciphering-Long-Term-CO2-Trends-A-Time-Series-Analysis-of-Mauna-Loa-Data Deciphering-Long-Term-CO2-Trends-A-Time-Series-Analysis-of-Mauna-Loa-Data Public

    Using sophisticated time series analysis techniques on Mauna Loa Observatory data, we unveil insightful patterns and trends crucial for understanding climate change dynamics. This project showcases…

    Jupyter Notebook 1

  3. Estimating-Ocean-Flows-with-Gaussian-Processes Estimating-Ocean-Flows-with-Gaussian-Processes Public

    The Philippine Archipelago is a fascinating multiscale ocean region. Its geometry is complex, with multiple straits, islands, steep shelf-breaks, and coastal features, leading to partially intercon…

    Jupyter Notebook

  4. Monitoring-Inland-Surface-Water-Area-using-Google-Earth-Engine-Python Monitoring-Inland-Surface-Water-Area-using-Google-Earth-Engine-Python Public

    In this project, we’ll explore the process of developing a powerful tool to monitor inland surface water areas using the Google Earth Engine (GEE) platform and Python. By leveraging geospatial data…

  5. Collaborative-Filtering-via-Gaussian-Mixtures Collaborative-Filtering-via-Gaussian-Mixtures Public template

    This project aims to build a mixture model for collaborative filtering using Gaussian mixtures. The dataset used consists of movie ratings provided by users, extracted from a subset of the Netflix …

    Python 1

  6. Genomics-and-High-Dimensional-Data Genomics-and-High-Dimensional-Data Public

    In this project, we will analyze a single-cell RNA-seq dataset, with the goal of unveiling hierarchical structure and discovering important genes. The datasets provided are all different subsets of…

    Jupyter Notebook 1