Karim Lekadir is an ICREA Professor in the Department of Mathematics and Computer Science at the University of Barcelona. He studied mathematics and computer science as an undergraduate in France and Germany. He obtained his PhD from Imperial College London and was a postdoctoral researcher at Stanford University. He investigates new data science techniques for trustworthy and ethical artificial intelligence in medicine. He has been PI in 12 EU-funded projects, coordinated 5 Horizon projects, and was awarded an ERC Consolidator grant to investigate new AI techniques tailored to resource-limited settings.
Research interests
My research lies at the intersection of artificial intelligence (AI), medicine and social sciences. I am interested in AI solutions that are that are effective, ethical, and trustworthy. I work a lot with European grants, which allowed me to specialise in generalisable AI solutions that can adapt across different environments. A key research interest of mine is AI for global health, such as through my ERC Consolidator Grant AIMIX ‘Inclusive AI for accessible medical imaging across resource-limited settings’. Here, my team and I are developing new AI approaches for under-served populations in rural African regions, addressing obstacles such as limited data, basic equipment and clinician shortages. My research also focuses on fairness in AI, always aiming for AI tools that provide equitable care across demographics, regardless of gender, age, ethnicity, or economic status. My research touches on several medical fields, including oncology, cardiology, mental health, and women’s health.
Selected publications
– Camacho M, Atehortúa A, Wilkinson, T, Gkontra P & Lekadir K 2025 “Low-cost predictive models of dementia risk using machine learning and exposome predictors” Health Technol.Volume 15, pages 355–365.
– Dang V N, Cascarano A, Mulder R H, Cecil C, Zuluaga M A, Hernández-González J & Lekadir K 2024, “Fairness and bias correction in machine learning for depression prediction across four study populations“, Scientific Reports, 14 – 1 – 7848.
– Chen Z, Lu Y, Long S, Campello V M, Bai J & Lekadir K 2024, “Fetal head and pubic symphysis segmentation in intrapartum ultrasound image using a dual-path boundary-guided residual network“, IEEE Journal of Biomedical & Health Informatics, vol 28 no 8 pp 4648-4659
Selected research activities
- Horizon Europe grant STAGE started. Role: WP Lead on AI-based prediction of ageing trajectories.
- ERC PoC grant accepted (AIFIX – Inclusive artificial intelligence using adaptive federated learning across high- and low-resource settings).
- General Chair of the MICCAI 2024 Conference (First time in Africa).
- Stakeholder engagement on AI-powered pregnancy screening in Kenyan villages completed (with local citizens, community managers, religious leaders, policymakers).
- FUTURE-AI guideline on trustworthy AI in healthcare accepted at The BMJ as first author (Impact Factor 93,7).
- Keynote speaker at the MIDL 2024 Conference (Title: The whole picture: Building trustworthy AI in medical imaging from the ground up).
- Keynote speaker at the AIMS Workshop on Data Science and Artificial Intelligence for Sustainable Development (Title: From Barcelona to Marrakesh to Nairobi: Collaborative AI for global health).
- Member of the EIBIR Scientific Advisory Board and the MICCAI Society Board.
- Two new graduated PhDs (Carlos Isla-Martin and Cristian Izquierdo).