PhD Program in Systems Science
Coordinator: Rocco De Nicola
PhD Program Overview
The PhD Program in Systems Science relies on proficiencies in the development of predictive quantitative models for the analysis of economic, technological and social systems. It deals with increasingly relevant problems that regard, for example, smart grids, social networks, smart communities, smart cities, the management of immigration flows and international exchanges, risk analysis in global financial systems, intelligent and sustainable industrial production systems, health systems, logistics systems and cyber-physical systems, namely systems consisting of the interaction between digital systems and physical units, prominent in automotive, aerospace, chemical, infrastructure, energy, biomedicine and manufacturing industries.
The principal educational objective of the PhD Program is to help students master and effectively employ basic methodological tools (mathematical models, data extraction, statistical analysis, algorithms) and potentially develop new ones, within the specific domains of both its Tracks:
The Program is therefore characterized by the interdisciplinary nature of its innovative approach. Barriers that traditionally divide domains of knowledge are largely overcome through tackling problems that arise in diverse application frameworks - like economics, finance, industry, computer systems, etc. - with a variety of scientific methodologies for the analysis of systems derived from physics, statistics, econometrics, computer science, systems engineering and computational methods.
In particular, the Program’s educational offering foresees the use of tools such as machine learning and reconstruction of mathematical models from data, stochastic processes, statistics, network analysis, analysis of dynamic systems, numerical optimization methods, numerical integration for differential equations and high-dimensional econometrics, which is increasingly characterized by significant and highly-innovative computational components, that can allow for the study of extremely complex systems by dimension or execution speed, based on tools for the analysis of data, particularly so-called Big Data. Focusing on this core of general methodological skills provides both a broad applicative versatility and a shared vocabulary to deal with various issues.
The PhD program in Systems Science aims to enrich the track in Computer Science and Systems Engineering on the one hand, integrating field training with the ability to analyze the socio-economic dimension of the various problems, from different points of view, and the analysis of institutional, regulatory and patent contexts. On the other hand, the students of the track in Economics, Networks and Business Analytics will acquire a deeper knowledge of the tools of linear algebra, numerical methods for differential equations, optimization, programming and control of dynamic systems, network analysis, statistics and machine learning, and the management of large databases.
Input and Output Profiles
Perspective students should preferably have a master-level background in computer science, engineering, economics physics, mathematics, statistics or in a related field. The Program offers a preparation to analyze and resolve a broad spectrum of highly complex problems with an elevated institutional, social and industrial interest, with the primary aim of identifying government solutions and effective intervention policies in different domains. Employment opportunities are therefore found both within the academic realm, in various disciplines (engineering, computer science, economics and management), and in the public sector, in research laboratories, study centers and regulatory centers, as well as in the private sector (services, industry and professional consultancies).
- Prof. Rocco De Nicola (Full Professor of Computer Science, IMT School)
- Prof. Alberto Bemporad (Full Professor of Control Systems, IMT School)
- Prof. Ennio Bilancini (Full Professor of Political Economy, IMT School)
- Prof. Guido Caldarelli (Full Professor of Theoretical Physics, IMT School)
- Prof. Lorenzo Casini (Full Professor of Administrative Law, IMT School)
- Prof. Maria Luisa Catoni (Full Professor of Ancient Art History and Archaeology, IMT School)
- Dr. Gustavo Cevolani (Assistant Professor in Logic and Philosophy of Science, IMT School)
- Dr. Gabriele Costa (Assistant Professor in Computer Security, IMT School)
- Prof. Irene Crimaldi (Associate Professor of Statistics, IMT School)
- Dr. Giorgio Stefano Gnecco (Assistant Professor in Operations Research, IMT School)
- Prof. Nicola Lattanzi (Full Professor of Business Administration, IMT School)
- Prof. Marco Paggi (Full Professor of Structural Mechanics, IMT School)
- Prof. Emanuele Pellegrini (Associate Professor of Art History, IMT School)
- Prof. Pietro Pietrini (Full Professor of Clinical Bichemistry and Molecular Biology, IMT School)
- Prof. Massimo Riccaboni (Full Professor of Economics and Management, IMT School)
- Prof. Emiliano Ricciardi (Associate Professor in Psychobiology and Psychophysiology, IMT School)
- Dr. Francesco Serti (Assistant Professor in Economics, IMT School)
- Prof. Mirco Tribastone (Associate Professor of Computer Science, IMT School)