Intelligent Systems Engineering (LM-32)

Artificial intelligence, cybersecurity and robotics

From the investigations conducted, and aimed at evaluating the professional figures required by the world of work,
it emerges unequivocally that there is a strong shortage of graduates in technical-scientific disciplines with adequate skills to govern the digital transformation of industrial processes and, more generally, of all work, social and personal processes of interaction between natural persons and IT or computerizable systems.

The Master's Degree Course in IngIntelligent Systems Engineering aims to respond to this demand for professional figures, focusing onattention on systems in which the hardware components and
software integrate to offer advanced functionality
that respond effectively to current ones
need for innovation. The design and management of these systems therefore require the integration of technical and transversal skills, relevant in the fields of production and services.

To this end, training activities mainly concern three fundamental aspects of intelligent systems:

  • L'artificial intelligence, which has an enabling role for the understanding of the data generated by digital transformation processes, for their dynamic inclusion in these processes and, subsequently, for their virtuous use in the governance of computerized systems.
  • La cyber-security as a fundamental requirement of every cyber-physical system necessary to guarantee its correct functioning, prevent potentially dangerous behavior and make the systems compatible with regulations.
  • La robotics, as an intelligent system paradigmatic of the integration between the physical world and the computational world, in which computational techniques, control methods and communication technologies are strongly interconnected and interacting with the physical world.

The study of intelligent systems approached from three different perspectives stimulates lateral thinking
learners in promote innovation and creativity in solving complex problems. In order to address these topics, the basic training activities (common training core) concern statistics and mathematical optimization, the principles and methodologies underlying artificial intelligence, robotic systems and advanced automatic systems, as well as the architectures of distributed systems and the use of IoT devices for interaction with the physical world. The course is therefore characterized by transversality and for the inclusion in the training course of topics related to the development of solutions based on information technologies, automatic and robotics and on the use of intelligent systems in multiple application areas, including interaction with people.

The master's graduate will be able to design, integrate, implement and manage distributed and complex ICT solutions from a technical point of view, which guarantee adequate levels of security, and which integrate Internet of Things (IoT), robotic systems and software components that acquire and process data with artificial intelligence techniques to carry out functions, provide services and extract information useful for decision-making processes in industrial, administrative, healthcare, personal support, sustainable development, planning, optimization and intelligent management of energy resources, and circular economy.

At the end of his training course, the student:

  • will be able to analyse, design and create systems in which software components interact with sensors, actuators and other physical components to carry out functions and provide services in application contexts that employ digital and robotic technologies as enabling factors;
  • will be able to design systems capable of acquiring, analyzing and managing a multiplicity of quantitative and qualitative data sources for the performance of functions and the provision of services in application contexts that use digital technologies as enabling factors;
  • will be able to guarantee adequate levels of security for these systems with particular reference to the management of IT vulnerabilities;
  • will be able to plan and manage information flows in the entire process of collecting, valorising and presenting data in order to support organisational, production and decision-making processes;
  • will be able to interact with experts from different application sectors to define project specifications and/or identify indicators that allow qualitatively and quantitatively evaluating the performance of distributed and complex ICT systems and infrastructures;
  • will be able to use the language fluently, in written and oral formingua inginjured with reference to disciplinary lexicons.

Graduates can find work at:

  • Industries and companies that operate in the design, management and configuration of hardware and software systems, and engaged in digital transformation processes and/or characterized by complex production and organizational processes that require continuous technological updating and the use of advanced analysis technologies to their management;
  • Service and consultancy companies operating in areas related to digital transformation;
  • Service and consultancy companies operating in areas related to data analysis;
  • Service and consultancy companies operating in fields related to cybersecurity,
  • Companies and companies that design, configure or use robotic systems for industrial automation,
  • Public administration for the provision of services based on IoT technologies;
  • Companies and organizations that use digital technologies as enabling factors for the provision of services in the healthcare, personal care, sustainable development, intelligent management of resources and energy systems, circular economy.

The training path is divided into a common first year with teachings that cover the characterizing aspects of the study course described above, as well as training activities that allow the development of sensitivity to issues related to the human factor, and in a second year in which the student can delve into the topics of modern cyber-physical systems, advanced robotic systems, and the most recent artificial intelligence algorithms and models.

The training course includes a significant activity relating to the final test, which favors the in-depth study of the topics being studied in significant periods to be spent in university laboratories or, as happened for the completed and final cohorts, in significant periods of internship to be carried out at and in collaboration with companies.

President of the Course