Natalie uses geospatial analytics to inform agriculture, aquaculture, water and coastal resources management. She develops data-intensive, management-focused and interdisciplinary approaches to the study of complex biological system dynamics, including the connectivity between land management practices and downstream water quality. Other interests include identifying risks to food security in coastal basins, linking data mining and mechanistic modeling approaches and investigating spatial and temporal dynamics of socio-environmental systems across settings and scales.
- Post hoc support vector machine learning for impedimetric biosensors based on weak protein-ligand interactions (2018)
- Revealing biotic and abiotic controls of harmful algal blooms in a shallow subtropical lake through statistical machine learning (2018)