Summary
Ramon Díaz-uriarte is a professor and computational biologist with over two decades of experience applying statistical computing to bioinformatics, from patient classification on high-dimensional omics to HMM-based copy number analysis. He blends rigorous academic training (PhD in Zoology, MScs in Statistics and Biometry from University of Wisconsin–Madison) with practical software skills—teaching R, building parallelized web tools, and developing probabilistic graphical models for cancer evolution. His career spans research roles at CNIO and long-term faculty positions at Universidad Autónoma de Madrid, where he focuses on the sequence of driver events in cancer and simulation of evolutionary processes. Known for translating complex statistical methods into usable bioinformatics applications, he often works at the intersection of theory, scalable implementation, and teaching.
12 years of coding experience
10 years of employment as a software developer
Bachelors, Biology, Bachelors, Biology at Universidad Autónoma de Madrid
MSc, Statistics, MSc, Statistics at University of Wisconsin-Madison
English, Spanish, Portuguese