Research Bio
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
In the News
Berkeley Launches Agile Metabolic Health and Open Platforms Initiative
Experts at UC Berkeley and UC San Francisco have begun working to improve the treatment of diabetes and metabolic health using a first-of-its-kind open-source platform with broad societal benefits.
New UC Berkeley Center Will Apply Data Science to Solving Environmental Challenges
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.
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