Summary
Saul Acevedo is a PhD-trained Data Science Developer with nine years of experience applying mathematical evolutionary models and computational methods to biological problems. He builds R Shiny applications and reproducible bioinformatics workflows to help researchers visualize, curate, and analyze preclinical drug and tumor-volume data, and he consults with scientists to embed statistical comparisons into interactive tools. His academic work on stochastic simulations and prion evolution (published in Proceedings B) informs a practical, model-driven approach to software for life sciences. Based in Houston, he blends hands-on coding in R, Python, Java, and CWL with domain fluency across biotech projects, enabling rapid adaptation to new biological challenges.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Biology Mathematical Evolutionary Biology, Doctor of Philosophy - PhD Biology Mathematical Evolutionary Biology at University of Houston