Projects

The project aims to research and develop solutions based on computer vision and machine learning, two sub-areas of artificial intelligence, to automatically locate, classify, and track vessels, potential threats, and illicit activities based on the fusion of information from cameras installed on poles or drones and transponders on vessels to increase the safety, effectiveness, and level of automation of maritime traffic monitoring.

This research project aims to study the application of machine learning algorithms to radio resource allocation in next-generation wireless networks. It aims to reduce computational complexity and the latency of traditional algorithms, thus optimizing network performance.

This project aims to increase the security of IoT networks in response to the growing adoption of connected devices through research and development of solutions for classifying and detecting threats based on machine learning techniques.

This project aims to develop reconfigurable intelligent structures using AI algorithms, new materials, and manufacturing techniques.

The main objective of this project is to research and develop innovative solutions using computer vision, machine learning, drones, and IoT devices to improve the monitoring of crops and animals in rural areas. The goals include the efficient identification of pests and disease locations of animals, among others. With the solutions that will be proposed, we seek to increase agricultural efficiency and productivity, reduce production losses, and improve the decision-making process.

The main objective of this project is to research and propose solutions based on machine learning models that present low computational complexity and high precision to estimate the location of devices based on received signals.

This project aims to explore optimization and compression techniques that enable efficient execution of ML algorithms on embedded and edge devices, overcoming resource constraints and ensuring that these algorithms can be deployed effectively in environments with limited processing capacity, storage, and energy.

This research project aims to develop new solutions based on Artificial intelligence techniques to optimize reconfigurable intelligent surfaces and increase the performance of future wireless communication systems.

This research project aims to develop new solutions based on Artificial intelligence techniques to optimize the wireless energy transfer system to guarantee the uninterrupted and maintenance-free operation of a massive number of Internet of Things devices.

This research project aims to investigate the deployment of wireless energy transfer systems in rural scenarios to guarantee the uninterrupted operation of a massive number of Internet of Things devices and, consequently, optimize production, enhance animal welfare, and improve overall agricultural efficiency.

This research project focuses on designing and developing metasurfaces strategically manipulated in space and time to enhance wireless communications. Specifically, our project is dedicated to multiplexing wireless signals, paving the way for augmented capacity within forthcoming wireless communication networks.

The project aims to apply modern wireless communication techniques, mainly in adverse propagation conditions, operating primarily in the microwave and millimeter wave (mmWave) bands. It focuses on three main techniques enabling future sixth generation (6G) networks, namely: i) study and development of so-called intelligent surfaces and RIS; ii) proposition of improvements in spectral sensing techniques based on the distribution of the phase difference of the received signal and iii) study of fluid antenna systems.