Teaching
Analisi e Gestione dei Sistemi Ambientali
The course (in Italian) develops knowledge and skills for modeling and managing natural systems, and their use to support decision-making. Topics include: decision-making processes, descriptive models (both deterministic and stochastic), and design of management policies. Water resources are used to demonstrate the methodologies presented in the class.
Natural Resources Management
The course develops knowledge and skills for the advanced modelling, management, and control of natural resources systems. The emphasis will be on the operational and real time control aspects of natural resources modeling and management, with a focus on water resources systems and extensive reference to real world case studies. Topics include: natural resources systems modeling for management (from stochastic processes, through linear models, to non-linear model and machine learning), predictive modelling, uncertainty and sensitivity analysis, model diagnostics, stochastic and robust optimal control, approximate control methods (e.g. simulation-based approaches, approximate dynamic programming, reinforcement learning), real time control, and complexity reduction methods. The course is organized into two modules: the 1st module (Prof. Giuliani) develops topics from data to well validated models, the 2nd (Prof. Castelletti) covers algorithms and methods to design optimal decisions and negotiation support systems. The course is aimed at graduate students preparing to work in environmental and water resources engineering field.
Advanced Environmental Systems Analysis - mod. 2
The course offers a systematic overview of policy analysis and decision-making under global change. The emphasis will be on concepts and tools for modeling human decisions in environmental systems subject to demographic, land-use, energy, and climate change. The course develops knowledge and skills for modeling these changes across different spatial and temporal scales, quantifying their impacts at the local scale, assessing the variety of uncertainties associated to future projections, and developing tools to assist decision makers. Real world examples and numerical applications will be developed. The course is aimed at graduate students preparing to work in the environmental engineering field.
Perspectives in Science, Technology and Policy for Sustainable Change
The PhD course (STEP-CHANGE program) provides a general overview of challenges and opportunities of global sustainable change. The focus will be on the Water, Energy, Food, and Ecosystem (WEFE) nexus. Main goals include (1) to explore existing and projected science, technology and policy challenges to managing WEFE in a sustainable way; (2) to critically review existing quantitative and qualitative approaches to support decision-making for WEFE systems under change, including both physical and socio-economic aspects; and (3) to identify opportunities for trans- and inter-disciplinary approaches to address main limitations of existing approaches. The course is delivered through seminars by local and international experts, real world case studies will be systematically used to support theoretical lectures and engage students in learning by doing.
Social data analytics for Behavioural Modelling
The PhD course (STEP-CHANGE program) introduces qualitative data to support risk assessment and enrich complex systems modelling, mainly focused on synergies and trade-offs between competing-confronted water uses. The course cover different data collection sources, mixed methods, research pathways, and decision and policy transformation processes in detail. The fundamental goals include (1) to overview the main qualitative methods of data collection (interviews, surveys, focus groups, workshops); (2) to outline a step-by-step approach to qualitative research design, including sampling and recruitment strategies using primary and secondary data; (3) to explore data management tools for observational studies and content analysis; and (4) to discuss social data heterogeneity and derive useful insights to reinforce risk assessment and behaviour modelling. Lectures and seminars by experts are delivered to share experiences from case studies and exploratory research to engage students through hands-on experience.