Delmiro Fernandez-Reyes is Professor of Biomedical Computing at the Intelligent Systems Group of the Department of Computer Science, Faculty of Engineering University College London, UK. He is also Adjunct Prof. in Paediatrics at the College of Medicine of the University of Ibadan (COMUI) Nigeria. He founded and directs the UCL - University of Ibadan African Computational Sciences Centre for Health and Development (ACSC4HD) https://african-cschd.org.  His interdisciplinary expertise in the clinical-, life-, and computer-sciences has translated into a tight interaction of computational approaches with the hypothesis-forming steps, clinical study design and novel data-generation. His research harness computational research to unravel complex disease associations and studies providing real-World prospective validation which in turn informs algorithm and system development. His contributions to knowledge and ongoing research can be summarised across the following research themes: 1- data-science to tackle severe childhood malaria; 2- data-science to tackle tuberculosis diagnosis; 3- machine-learning for biomedical research and clinical decision-support; 4- AI-driven microscopy for digital pathology and; 5- solutions to global challenges through engineering and digital technology research.He has pioneered the use of machine learning approaches on plasma proteomics to understand the complex spectrum of disease of childhood severe malaria. His team has discovered and validated protein and genetic biomarkers of severe malaria that currently underpin his research and development of scalable computational clinical decision-support systems for the sub-Saharan region for improving childhood global health in low-to-middle income sub-Saharan West Africa.Currently his focus on creating innovative and scalable solutions to global challenges of LMICs through engineering and digital technology research have been further consolidated by receiving over £3 millions of funding from the prestigious EPSRC-GCRF Awards to carry-out two large multi-group multi-site research projects: 1- Fast Accurate and Scalable Diagnosis of Malaria using Robotic Microscopy and Artificial Intelligence (FAST-Mal) (PI) for the research, development and deployment of an AI-driven robotic malaria diagnosis platform in sub-Saharan West Africa and; 2- AI-driven Image Quality Transfer improvement of sub-Tesla MRI resolution for clinical decision support of intractable childhood epilepsy (IQT-Epilepsy) in sub-Saharan West Africa (Co-PI).