Research areas
Below is a top-level description of the main research topics for each curriculum.
Computer Engineering
Methods and technologies of software
Concerns methods of design, examination and evaluation of complex software systems, with further details on formal methods and advanced SW architectures.
Multimedia and computer vision
Concerns the design and implementation of multimedia data processing systems, automatic image and video interpretation, 3D data elaboration, automatic image and video annotation, media search from databases and internet, smart computing and intelligent environments for advanced human-machine interaction, surveillance, robotics.
Artificial intelligence and bioinformatics
Mainly focused on algorithms and architectures for machine learning, with special emphasis on relational and structured data, kernel methods, neural networks, bioinformatics applications, neuroinformatics, chemioinformatics, image recognition and methods for electronic publishing
Distributed systems and data engineering
Concerns the study of distributed, parallel and complex processing systems wherein distributed architecture, performance and data complexity issues are integral part of the problem, such as for instance in applications for big data, smart cities, smart clouds, internet-of-things, smart manufacturing, etc..
Control, Optimization and Complex Systems
Concerns analysis, modelling and synthesis of high-performance (possibly networked and hence subject to cyber attacks) automatic control, supervision and monitoring systems for processes that are only partially known, possibly distributed in space and subject to constraints, such as those encountered in industrial applications, robotics, bio-engineering, aerospace, electrical systems, etc.
Concerns the study of Operations Research models and applications, the development and the analysis of efficient optimization algorithms for the solution of complex problems and the interaction between data science and optimization. The applications of optimizations can be found in the field of automation, in industrial production, from logistics to transportation, to the supply-chain, in the management of electrical energy networks and in training machine learning systems.
This research is suitable for applicants with a strong background in Physics, Chemistry, Mathematics or Engineering who are willing to carry out research work of cross-disciplinary type. The research topic can concern methodological aspects, from dynamical systems to stochastic processes, including complex networks and their applications, from computer engineering to social networks and life science.
Electronics, Electromagnetics and Electrical Systems
Concerns the analysis and design of electronic devices and systems at high frequency (from radio frequency to millimeter waves).
Concerns the analysis and design of electronic systems based on advanced digital components, with applications from biomedical to radar fields.
Concerns the use and development of numerical techniques for the analysis and design of radiant systems and passive devices at high frequency, from some GHz up to optical frequencies.
Concerns the critical and comparative analysis of control techniques for electrical drives with the development of innovative algorithms, the automation of power systems, with particular reference to the “power quality” in distribution networks, to the “smart-metering” and fault diagnosis in electrical systems.
Telecommunications and Telematics
Algorithms and technologies for signal processing
Concerns processing methods and techniques of mono/multidimensional signals for the extraction of information and the efficiency of their representation in transmission and storage.
Concerns methods and techniques for efficient generation, transmission and disclosure of information through future terrestrial and satellite transmission channels.
Concerns methods and techniques for efficient transfer of information from source to destination through complex and advanced communication networks and related communication network applications
Telematics and information society
This cross-disciplinary area involves the applications of ICT technologies considered as key-enabling in different scientific and application domains. It requires a multi-disciplinary background in order to cope with the large variety of services and applications of telematics. The domains of interest include: telecommunications, communication, political and socio-economic sciences including all areas of the “Societal Challenges” of the European programme H2020.
For information on the research themes for each curriculum see here.