Environmental
Intelligence
for Global Change
We are a research group based at the Department of Electronics, Information, and Bioengineering, Politecnico di Milano. Our research mission is advancing environmental decision-analytics for supporting human decisions in complex engineering systems including multiple actors and exposed to evolving multisectoral demands and global change. Our research fuses environmental, climate, and hydrologic disciplines with machine learning, optimal control, and evolutionary computation. This multidisciplinary mix yields innovative, flexible, and robust solutions facilitating participatory decision making processes by addressing the multifaceted complexity of environmental systems, including their nested interdependencies across stakeholders, processes, and policies at different spatial scales; as well as potential changes in human-nature interactions and feedbacks under changing climate extremes and societal demands.
The eiLab contributed to a systematic review assessing how machine learning has been used in drought research over the past two decades. Published in Water Resources Research, the review analyses 544 scientific papers on machine
We are pleased to share a new publication developed in collaboration with colleagues from the University of Cambridge, the Environment Agency, and several UK partners. This perspective explores the potential of artificial intelligence (AI) to
The eiLab contributed to a study developing an explainable machine learning model to estimate intense Mediterranean cyclone activity from large-scale climate variables. In the study, published in Journal of Geophysical Research: Machine Learning and Computation,
