Machine learning in ecosystem informatics and sustainability

Abstract

Ecosystem Informatics brings together mathematical and computational tools to address scientific and policy challenges in the ecosystem sciences. These challenges include novel sensors for collecting data, algorithms for automated data cleaning, learning methods for building statistical models from data and for fitting mechanistic models to data, and algorithms for designing optimal policies for biosphere management. This presentation discusses these challenges and then describes recent work on the first two of these - new methods for automated arthropod population counting and linear Gaussian DBNs for automated cleaning of sensor network data.