The PhD course in Information and Communication Technologies (ICT) is structured around three curricula: The course offers specialization in three areas: Computer Engineering and Science, Electronics, and Telecommunications, and Industrial Applications of ICT.

The research topics offered within these curricula encompass a number of contemporary research and technological issues on computer engineering, electronics, and telecommunications. The curriculum in Computer Engineering and Science is centered on research topics pertaining to the domains of computer engineering and computer science. The curriculum in Electronics and Telecommunications is centered on research topics pertaining to the fields of electronics, measurements, telecommunications, electromagnetic fields, and automation. The Industrial Applications of ICT curriculum encompasses all the scientific disciplines mentioned above, with an emphasis on the development of innovations and new knowledge that address industrial needs. 

The areas of investigation encompass a range of topics related to ICT, with both theoretical, experimental, and applied connotations in various scientific fields.

Electronics and Telecommunications

• Smart Sensors and Innovative Instrumentation: Design, development, and characterization of sensors and instrumentation for automotive, agricultural, biomedical, and industrial applications.
• Brain-Inspired Computing: Development of high-performance, low-power AI systems using new brain-inspired computing paradigms and non-volatile memory devices.
• Big Logic-in-Memory Circuits: Exploration of emerging non-volatile memory devices for next-generation ultra-low power edge computing architectures through device/circuit co-design strategies.
• Compact Modeling of Emerging Non-Volatile Memories: Development, testing, and validation of compact models based on the complex physics of non-volatile memory devices for use in state-of-the-art circuit simulation software.
• Nanoscale Small Particle/Single Molecule Bio-Sensor Arrays: Development of nanoscale sensors integrated into CMOS technology for health, food, and environmental applications.
• Iontronic and Electronic Sensor/Actuator Arrays: Development of mixed iontronic and electronic microtechnologies to stimulate and record neural activity for advancing brain studies and neuroscience.
• Alternative Semiconductor Materials: Exploration and benchmarking of new materials for nanoelectronics, focusing on transport effects and applications in IoT, energy, communication, and quantum technology sectors.
• Vehicular Networks and Multiradio Access Technologies: Design of new radio access schemes and machine learning tools to enhance vehicular communications and support Intelligent Transport Systems (ITS).
• Innovative Devices and Circuits for Next-Generation Hardware: Development of innovative materials, devices, and circuits for low-power hardware to enhance AI and autonomous systems.
• Signal Processing Algorithms: Development and implementation of innovative signal processing algorithms for wireless communication systems, radar systems, and positioning systems.
• Specialty Optical Fibers: Development of innovative optical fibers for applications in physics, telecommunications, sensing, and laser technology.

Computer Engineering and Science

• AI and Deep Learning for Computer Vision: Research in image processing, analysis, and visual information retrieval from images and videos.
• Big Data Management, Integration, and Analytics: Development of methodologies and tools for designing and managing heterogeneous and distributed information systems.
• Machine Learning Theory and Applications: Development of new learning algorithms and training methods for applications in machine and deep learning.
• Autonomous Systems, Agents, and Middleware: Methodologies and tools for distributed systems, including swarm robotics, software agents, and pervasive computing.
• Cybersecurity: Research on network and software security, cloud security, blockchain, intrusion detection systems, and IoT protection.
• Fog and Cloud Computing: Management of cloud and fog computing platforms, focusing on computing load, processing tasks, network characteristics, and power efficiency.
• Modeling, Identification, and Control for Autonomous Systems: Development of novel modeling techniques and control algorithms for industrial automation and autonomous systems.

Industrial Applications of ICT

• This curriculum encompasses all the scientific disciplines mentioned above, with a focus on developing innovations and knowledge to meet manufacturing needs. PhD students engage in a three-year industrial project in collaboration with a supporting company.