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.
Herman, J.D., J.D. Quinn, S. Steinschneider, M. Giuliani, and S. Fletcher (2020), Climate adaptation as a control problem: Review and perspectives on dynamic water resources planning under uncertainty, Water Resources Research, 56
Bertoni, F., M. Giuliani, and A. Castelletti (2020), Integrated Design of Dam Size and Operations via Reinforcement Learning, Journal of Water Resources Planning and Management, 146(4)
Piégay, H., F. Arnaud, B. Belletti, M. Bertrand, S. Bizzi, P. Carbonneau, S. Dufour, F. Liebault, V. Ruiz‐Villanueva, and L. Slater (2019), Remotely Sensed Rivers in the Anthropocene: State of the Art and Prospects, Earth Surface Processes and Landforms, 45
Bertoni, F., A. Castelletti, M. Giuliani, and P.M. Reed (2019), Discovering dependencies, trade-offs, and robustness in joint dam design and operation: An ex-post assessment of the Kariba dam, Earth’s Future, 7