I combine forestry science, geospatial data, and machine learning to transform forest measurements into predictive intelligence.
I'm a forestry engineer / data scientist hybrid focused on:
- 🌲 Forest inventory (pre-cut, continuous, survival)
- 🛰️ LiDAR & point cloud processing (LAS/LAZ)
- 📊 Forest growth & yield modeling
- 🤖 Machine learning for volumetrics and prediction
- 🧠 Virtual trees & synthetic data generation
I work daily with large-scale forestry datasets, operational calibration (harvesters, log scanners), and advanced statistical and ML models applied to real forest production systems.
- LAStools, FUSION, PDAL
- ArcGIS Pro, QGIS
- Rasterio, GeoPandas
- NumPy, Pandas, SciPy
- TensorFlow / Keras, Scikit-learn
- 🌲 Virtual Tree Generation using neural networks
- 📐 Schumacher & Hall + taper models automation
- 🛰️ LiDAR-based volume forecasting
- 📊 Diameter distribution modeling (Weibull, logistic)
- 🧠 ML pipelines for operational forestry decisions
⭐ Turning forest data into intelligence, one tree at a time.