Environmental Intelligence

for Global Change

About us

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.

News

DAFNE NSL in the Zambezi River Basin
On July 9-10, 2020 we contributed to the online DAFNE Negotiation Simulation Lab (NSL) involving the stakeholders of the Zambezi River Basin. This was the third NSL organized by the
AWESOME kick-off
On May 22, 2020 the AWESOME (Managing Water, Ecosystems and Food Across Sectors and Scales in the South Mediterranean) project has officially started with a virtual kick-off.  The main
ROSS: A novel active learning algorithm for robust planning under deep uncertainty





Deep uncertainty in future climate, socio-economic and technological conditions poses a great challenge to medium-long term decision
eiLab @MIT & Tufts

In the context of a Rocca Seed Funds initiative, we started a collaboration with Prof. Dara Entekhabi and Dr. Sarah Fletcher from the MIT Dept. of Civil and Environmental Engineering. The first meeting
On the advantages of jointly designing dam size and operations: a new paper on Earth's Future





Globally, many countries are actively seeking to maximize the hydropower potential of major river basins, yielding proposals
eiLab @AGU Fall Meeting 2019​

Here the list of our contributions accepted for the AGU Fall Meeting to be held in San Francisco (CA), December 9-13:

Seasonal drought forecasts to optimally balancing multisector interests
Can Artificial Intelligence improve seasonal forecasts and inform reservoir operations? a new paper on WRR
Increasingly variable hydrologic regimes combined with more frequent and intense extreme events call for accurate

eiTweets

Our new paper develops insurance bundling among competing agents exposed to uncorrelated risks https://bit.ly/2SprtgA @simonadenaro @MxgTeo @eiPolimi

Happy to see people are reading our work and our paper "Data Mining to Uncover Heterogeneous Water Use Behaviors From Smart Meter Data" is a #TopDownloadedArticle on #WRR. It is available #openaccess here: https://doi.org/10.1029/2019WR024897 #KNguyen @MxgTeo #RStewart #HRMaier @hydroaholics

Bored from the quaranteen? Interested in #sensitivity #analysis of #MachineLearning groundwater #forecasts? Take a look at our new paper @eiPolimi @ihedelft @UNL_BSE @BristolUniWater https://www.sciencedirect.com/science/article/pii/S0022169420304170

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Publications