Fernando Pérez's research focuses on creating tools for modern computational research and data science across domain disciplines, with an emphasis on high-level languages, interactive and literate computing, and reproducible research. Through tools like IPython and Project Jupyter, he builds foundational blocks that enable scientists to tackle all stages of computational research (from exploration through publication) with a coherent approach, thus improving scientific productivity, collaboration and reproducibility.
Research Expertise and Interest
data science, Educational Data Science, scientific computing
March 23, 2022
A new research center at the University of California, Berkeley, funded by alumni Eric and Wendy Schmidt, will tackle major environmental challenges including climate change and biodiversity loss by combining data science and environmental science.