This research line brings together foundational, basic, or general research in Artificial Intelligence. It includes sub-lines such as Computational Intelligence, covering research on AI algorithms (artificial neural networks, fuzzy logic, machine learning, deep learning, hybrid systems, quantum machine learning, etc.); Explainability and Ethics in Artificial Intelligence, addressing explainability, interpretability, and ethical considerations in AI models (explainable AI, ethics in AI, human-AI interaction, computational cognition, development of policies, regulations, recommendations, etc.); Distributed and Intelligent Computing Infrastructures, involving the development of intelligent distributed systems and smart environments for handling large-scale data generated by devices in IoT and IIoT contexts (cloud computing, intelligent distributed systems, federated learning, big data, etc.); and Generative Artificial Intelligence, focused on generating new content by learning from existing data, including text and images (large language models, machine translation using language models, content generation systems, synthetic data generation for machine learning, etc.).
It includes sub-lines such as:
This research line focuses on applied and often interdisciplinary research, close to the practical approaches of applied sciences. It includes sub-lines such as AI in the Spanish Language, which explores applications of AI in natural language processing for Spanish (large language models in Spanish, multilingual models, linguistic variation in models, AI in lexicography, AI in language teaching, etc.); AI in Digital Humanities (AI-driven humanities analytics, textual, musical and pictorial stylometry, AI in museology, historical text analysis, etc.); AI in Health Sciences (AI-assisted diagnosis, personalized treatments, genomic data analysis, population health management, telemedicine, virtual assistants, electronic health data integration, predictive analytics in healthcare, neuroscience, AI in biotechnology, ethics, etc.); AI and Legal Aspects (research on AI regulation, legal responsibility, use in court processes, legislation analysis, IP law, etc.); AI and Educational Technology (adaptive learning, classroom interaction analysis, augmented and virtual reality in education, data-driven educational management, AI in language teaching, universal learning design, etc.); AI and Social and Cultural Aspects, which addresses social challenges through psychology, sociology, anthropology (AI and demographic change, social media analysis, behavioral economics, AI in politics, governance, urban studies, inclusion and diversity, etc.).
It includes research areas such as: