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wildlife-conservation

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AI-powered environmental monitoring system for marine and terrestrial ecosystems using computer vision, real-time analysis, and FAIR data principles.

  • Updated Jan 2, 2026
  • Python

Developed a stable Negative Binomial (NB) Regression model for predictive analysis of over-dispersed bear incident counts. The model achieved an MAE of 2.39, revealing that dynamic weather and temporal factors are the dominant drivers of risk, informing future XGBoost/XAI work.

  • Updated Dec 13, 2025
  • Jupyter Notebook

My final year Bachelor’s university main project to predict future red squirrel populations in Scotland using Spatial-Temporal Modelling. Identifies and removes duplicate observations using both exact spatial matching and proximity-based detection that accounts for coordinate uncertainty.

  • Updated Oct 31, 2025
  • Jupyter Notebook

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