Fernando Pérez

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

Teaching

Courses taught during the three most recent terms
2026 Spring
  • Individual Study Leading to Higher Degrees  [STAT 299]  

  • Supervised Research: Interdisciplinary Studies  [UGIS 192E]  

2025 Fall
  • Reproducible and Collaborative Statistical Data Science  [STAT 159]  

  • Reproducible and Collaborative Statistical Data Science  [STAT 259]  

  • Directed Study for Graduate Students  [STAT 298]  

  • Individual Study Leading to Higher Degrees  [STAT 299]  

  • Supervised Research: Interdisciplinary Studies  [UGIS 192E]  

2025 Summer
  • Individual Study Leading to Higher Degrees  [STAT 299]  

2025 Spring
  • Individual Study Leading to Higher Degrees  [STAT 299]