We develop secure, reliable, ethical artificial intelligence systems combining robust solutions with fairness, interpretability, and respect for privacy, in order to mitigate the risks associated with implementation of artificial intelligence and increase trust among users.

We experiment with machine vision techniques to allow computers to understand and interpret visual information from the surrounding environment and act or formulate reports based on the data acquired.

We study natural language processing to enable machines to understand, generate and interact with human language. Our research spans areas such as language understanding, generation, translation, and analysis of sentiments and dialogue systems, for application to virtual assistants, chatbots and language translation.

We explore multimodal learning techniques to allow artificial intelligence systems to effectively process and interpret different sources of information, such as texts, images, and audio, in order to obtain a more complete understanding and interaction of the available data.

We study the use of artificial intelligence techniques to improve the capabilities and performance of radar systems. In particular, we explore new algorithms for target anomaly detection, tracking, classification, and identification, enabling radar systems to operate more efficiently and adaptively in complex environments.