Main research topics and current scientific activity

1. Geomatics, geostatistical and GIS modelling/simulations of environmental and pollution data (soil water, air). Risk mapping;
2. Environmental data mining and knowledge extraction. Development and adaptation of Machine Learning algorithms for space-time data;
3. Pattern recognition, modelling and visualisation of socio-economic, demographic and financial data;
4. Spatio-temporal point patterns analysis and modelling (clustering, outliers and hot spots detection) using topological, statistical and multifractal measures;
5. Modelling and assessments of natural hazards and risks: forest fires, avalanches, landslides. Renewable resources assessments;
6. Environmental and monitoring time series modelling using linear and nonlinear models and tools.

Active projects: 

• National Research Project “PNR 75: Big Data”
• Data Analysis Using Network, Multifractal and Dimensionality Reduction Tools
• Feature Selection based on a new estimator of Intrinsic Dimension
• Machine Learning Algorithm for Environmental Data Mining
• Deep Learning for remote sensing scene classification
• Wild/Rural Urban Interface assessment and prediction
• Analysis and Modelling of Space-Time Patterns in Complex Regions
• Fractal Data Mining : From Clustering Detection to Feature Selection