AI is advancing fast, driven by large, data-hungry models that are powerful but often opaque, costly to train and hard to scrutinise. Real-world use requires AI that copes with scarce, imbalanced or streaming data, generalises to unforeseen situations, and runs efficiently on constrained devices. It must also be fair and privacy-preserving, and earn the trust of the people who use it.
INESC combines symbolic and neural approaches with generative and foundation models, including multilingual language technologies, to build reusable AI resources and data-efficient learning methods. We develop responsible, human-centred AI that people can inspect, understand and work with. We also build efficient AI that runs at the edge, and multimodal perception systems that integrate vision, audio, text and sensor data, applied to decision support across industry and society.
Hybrid symbolic and neural AI, generative and foundation models, ontologies, AutoML, speech and natural language processing, machine translation, and multilingual language models and datasets
Learning from data streams and imbalanced data, anomaly and extreme-event prediction, predictive maintenance, causal inference and nowcasting, data integration, geospatial analytics, and machine learning combined with optimisation
Explainability, fairness and privacy-preserving AI, verification, visual analytics, human-AI collaboration, social and affective AI agents, and disinformation detection
Edge AI and federated learning, model compression, energy-efficient AI and hardware accelerators, computer vision, multimodal sensor fusion, and AI for cyber-physical systems and security
Coordinates the Artificial Intelligence area at INESC TEC and serves as the coordinator of LIAAD (Laboratory of Artificial Intelligence and Decision Support).
Research Coordinator at INESC TEC and Vice-Director of LIAAD, specializing in data streams and machine learning.
Research Coordinator within LIAAD supporting decision support and optimization frameworks.
Power Systems
Grid Intelligence Lab
Power Systems
Grid Intelligence Lab
Power Systems
Grid Intelligence Lab
Power Systems
Grid Intelligence Lab
AI and data science are central to Europe’s competitiveness, its digital transition, and its commitment to AI that is trustworthy and ethical by design. INESC research in this domain covers the full AI lifecycle: data, algorithms, explainability, fairness and efficient deployment at the edge. It contributes to European priorities on AI uptake in industry, energy-efficient and privacy-preserving AI, and multilingual language technologies for Europe’s languages. This helps turn Europe’s research strength into reliable AI applications for manufacturing, health, energy, mobility, security and society.
