Geospatial Data Scientist | GIS Developer | Machine Learning | Deep Learning | Computer Vision
I'm a Geospatial Data Scientist and GIS Developer working at the intersection of Remote Sensing and Artificial Intelligence.
My research focuses on applying Machine Learning and Deep Learning — especially Semantic Segmentation and Computer Vision — to satellite imagery (mainly Sentinel-2) for automatic detection of environmental phenomena such as landslides.
I design end-to-end GeoAI pipelines using tools like Docker, FastAPI, and PyTorch to automate the full workflow — from data acquisition and preprocessing to model training, inference, and visualization.
| Stage | Focus | Repository | Description |
|---|---|---|---|
| Stage 1 | ML Foundations | General-ML-Projects | Building intuition with classic datasets and models. |
| Stage 2 | GeoAI Transition | GeoAI-Landslide-Risk-Pipeline | Integrating geospatial analysis with ML-based hazard modeling. |
| Stage 3 | Cloud Deployment | GeoAI-Cloud-Pipeline | Deploying deep-learning models for real-world hazard detection. |
- Geospatial Data Science & GIS Development
- Satellite Image Processing (Sentinel-2, Sentinel Hub API)
- Machine Learning & Deep Learning (CNN, U-Net, DeepLabv3)
- Semantic Segmentation for Hazard Detection
- Dockerized AI Pipelines & FastAPI APIs
machine-learning Regression Supervised Learning scikit-learn data-visualization feature-engineering car-prices
Regression model focusing on accuracy improvement through feature engineering, scaling, and R² analysis on car-price data.
Time Series Deep Learning LSTM Rainfall Prediction
Time-series prediction of rainfall using LSTM neural networks.
Computer Vision CNN Image Classification PyTorch
CNN-based classification of rice grain types using PyTorch and image augmentation.
TensorFlow CNN Image Classification Agricultural AI
Same task as above but implemented using TensorFlow.
GIS Mapping GeoPandas Matplotlib
Introduction to visualizing geospatial data with Python.
GIS Coordinate Reference System Projection
Understanding and converting between geographic and projected CRS.
Geospatial Visualization Folium Leaflet
Creating interactive web maps using Folium and Python.
GIS Spatial Analysis Grid Density
Visualization and computation of Mean Grid Density from spatial point data.
GIS Buffer Analysis Distance Metrics GeoDataFrames
Analyzing spatial relationships using buffers and distance-based methods.
Main Language: Python
Libraries: PyTorch, TensorFlow, Scikit-learn, NumPy, Rasterio, GeoPandas, OpenCV
Tools: FastAPI, Docker, Git, PostgreSQL/PostGIS, QGIS
Remote Sensing: Sentinel Hub, Google Earth Engine, GDAL, Rasterio - 🧪 ResearchGate
- 📊 Kaggle
🌟 Currently focused on building AI-powered solutions for environmental hazard detection using satellite data.
🇩🇪 Available for remote roles or relocation to Germany in geospatial AI or Earth observation domains.
