Iolanda Velho holds a Ph.D. in Computational Engineering from Instituto Superior Técnico (IST), Universidade de Lisboa, and an M.S. in Biomedical Engineering from Faculdade de Ciências e Tecnologia (FCT), Universidade Nova de Lisboa. She is currently an Assistant Professor at Universidade Lusófona, where she focuses on advancing data-driven predictive models and exploring their applications in society, particularly in healthcare.
With a strong foundation in technology, programming, and statistical methods, Iolanda bridges the gap between organizations and the technological processes that generate and utilize data to drive impactful decision-making. Her academic and professional journey over the past decade reflects a dedication to research and education.
Her primary research interests lie at the intersection of mathematical modeling, image processing, data science, computational fluid dynamics, and numerical analysis, particularly applied to biological systems. In addition to her academic pursuits, Iolanda gained industry experience during her early career, working in health management and later serving as a Hospital Physicist at Instituto Português de Oncologia Francisco Gentil.
Iolanda has extensive teaching experience across various disciplines, including mathematics and physics courses, at multiple universities. In recent years, she has focused on teaching data science courses at institutions such as Nova SBE, FCT, IST, and Universidade Lusófona. These courses include Probability and Statistics, Data Mining, Data Curation, and Data Visualization.
Driven by her passion for data-driven decision-making, Iolanda aims to contribute to innovative solutions that address societal challenges, especially in the healthcare sector.
