PhD in Automatic Control, Bioengineering and Operations Research

Department

Department of Computer, Control and Management, Sapienza University of Rome

Main research activities/topics/projects

The educational objective of the PhD program in Automatic Control, Bioengineering and Operations Research is to prepare young scholars who can manage complex realities through the use of modeling tools, the adoption of analytical methods for models and processes, as well as the development of design and implementation techniques for systems arising in various application fields.

The program has 3 different curricula, described below.

AUTOMATIC CONTROL

The Automatic control curriculum is devoted to the theory and development of methods and technologies for the information processing (data and signals) aimed at automation (i.e., planning, management management and control, carried out automatically) of plants, processes and systems dynamics in general. In view of the specific areas of research present at DIAG, the main aeras covered are: systems theory and control, robotics, and control over networks.

BIOENGINEERING

The Bioengineering curriculum is devoted to an inherently interdisciplinary scientific area that deals with complex problems of a biomedical nature through the integration of tools from basic sciences, engineering, biology and medicine. Given the expertise of faculty members at DIAG, the main aeras covered are: modeling of physiological and biological systems, biomedical data and signal processing, computational neuroscience, analysis of functional brain networks, brain-computer interfaces, and the bioengineering for rehabilitation.

OPERATIONS RESEARCH

The Operations Research curriculum is devoted to the development of quantitative models and methods for decision-making problems with the purpose of analyzing, optimizing, planning, and governing the behavior of complex processes. Methodological skills and research areas include optimization theory and algorithms, simulation, and more generally decision support tools and their implementation including on complex, high-performance computing architectures. Given the expertise of faculty members at DIAG, the main aeras covered are: algorithms for integer and continuous nonlinear programming, combinatorial optimization, theory of graphs and networks, game theory and variational inequalities, Machine learning models and methods, and optimization in the presence of uncertainty.

Working language

English, Italian

Duration in months (min-max)

PhD sandwich: 6-12