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.
- Gazzotti, P., J. Emmerling, G. Marangoni, A. Castelletti, K. van der Wijst, A. Hof, M. Tavoni (2021), Persistent inequality in economically optimal climate policies, Nature Communications
- Zaniolo, M., M. Giuliani, S. Sinclair, P. Burlando, A. Castelletti (2021), When timing matters—misdesigned dam filling impacts hydropower sustainability, Nature Communications
Cominola, A., M. Giuliani, A. Castelletti, P. Fraternali, S. L. Herrera Gonzalez, J. C. Guardiola Herrero, J. Novak, A. E. Rizzoli (2021), Long-term water conservation is fostered by smart meter-based feedback and digital user engagement, npj Clean Water, 4
Zaniolo, M., M. Giuliani, A. Castelletti (2021), Neuro-Evolutionary Direct Policy Search for Multiobjective Optimal Control, IEEE Transactions on Neural Networks and Learning Systems
Likmeta, A., A.M. Metelli, G. Ramponi, A. Tirinzoni, M. Giuliani, M. Restelli (2021), Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems, Machine Learning