Summary
Óscar Pupo is a Head Data Scientist with a PhD in Computer Science and over a decade applying machine learning and data mining to healthcare, particularly improving outcomes for neurological diseases like multiple sclerosis. He leads data science efforts at Healios and Indivi, translating deep learning research into clinical-grade, GPU-accelerated solutions while maintaining a strong publication and peer-review record in top journals. His work bridges scalable Big Data methods and explainable AI to make predictive models interpretable and actionable for clinicians. Formerly a postdoc and senior scientist focused on computational biology and alternative splicing, he pairs domain-driven research with practical engineering in R, Python, Java, TensorFlow and MxNet. Notably, he concentrates on extracting non-invasive biomarkers and transferring them into public healthcare systems, emphasizing real-world impact beyond academic metrics.
10 years of coding experience
12 years of employment as a software developer
Engineer in Computer Science, Computer Technology/Computer Systems Technology, Engineer, Engineer in Computer Science, Computer Technology/Computer Systems Technology, Engineer at University of Holguín
Master, Computer/Information Technology Administration and Management, Master, Master, Computer/Information Technology Administration and Management, Master at Master in Applied Mathematic and Computer Science
High School diploma, Mathematics and Computer Science, High School diploma, Mathematics and Computer Science at Instituto Vocacional de Ciencias Exactas Jose Martí
Ph.D. in Computer Science, Computer Science and Artifitial Intelligence, Ph.D., Ph.D. in Computer Science, Computer Science and Artifitial Intelligence, Ph.D. at University of Córdoba, Spain
English, Spanish