Current AI research predominantly focuses on big data, which introduces challenges related to model explainability, limited access to extensive datasets, model complexity, the need for normalization techniques, and requirements for data annotation and collection. These challenges contrast with human decision-making, which relies on small data, explainability, and the ability to handle uncertainty.
During the seminar, an AI Lifelong Learning approach will be introduced that operates effectively with small data, offers explainable outcomes, and eliminates the need for new data gathering or annotation. To witness the practicality of this approach, join us at the seminar, where its application to a problem of interest will be demonstrated.
About the speaker
José Sousa managed the Advanced Informatics Core Technology Unit at the Faculty of Medicine, Health and Life Sciences at Queen’s University Belfast. He earned his PhD from the University of Minho.
Before and during his doctoral studies, he served as Information Systems Director at Institute for Systems and Computer Engineering, Technology and Science (INESC TEC), a research institution affiliated with the University of Porto.
José Sousa later worked as an AI researcher at Health Data Research UK and collaborated with the Centre for Public Health, Queen’s University Belfast, where he developed self-learning AI methods to support pandemic response.
At Sanofi, José Sousa leads the Personal Health Data Science team, developing AI technologies designed to improve disease management in line with the company’s “Citizen Before Patient” vision.
