Fireside Chat: Tidyverse Discussion

About the speakers

Jenny is a software engineer on the tidyverse team. She is a recovering biostatistician who takes special delight in eliminating the small agonies of data analysis. Jenny is known for smoothing the interfaces between R and spreadsheets, web APIs, and Git/GitHub. She’s been working in R/S for over 20 years and is a member of the R Foundation. She also serves in the leadership of rOpenSci and Forwards and is an adjunct professor at the University of British Columbia.

Mine Çetinkaya-Rundel

Professional Educator and Data Scientist

Mine Çetinkaya-Rundel is Professional Educator and Data Scientist at RStudio as well as Senior Lecturer in the School of Mathematics at University of Edinburgh (on leave from Department of Statistical Science at Duke University). Mine’s work focuses on innovation in statistics and data science pedagogy, with an emphasis on computing, reproducible research, student-centered learning, and open-source education as well as pedagogical approaches for enhancing retention of women and under-represented minorities in STEM. Mine works on integrating computation into the undergraduate statistics curriculum, using reproducible research methodologies and analysis of real and complex datasets. She also organizes ASA DataFest and works on the OpenIntro project. She is also the creator and maintainer of and she teaches the popular Statistics with R MOOC on Coursera.

Max Kuhn is a software engineer at RStudio. He is currently working on improving R’s modeling capabilities. He was a Director of Nonclinical Statistics at Pfizer Global R&D in Connecticut. He was applying models in the pharmaceutical and diagnostic industries for over 18 years. Max has a Ph.D. in Biostatistics. Max is the author of numerous R packages for techniques in machine learning and reproducible research and is an Associate Editor for the Journal of Statistical Software. He, and Kjell Johnson, wrote the book Applied Predictive Modeling, which won the Ziegel award from the American Statistical Association, which recognizes the best book reviewed in Technometrics in 2015. Their latest book, Feature Engineering and Selection, was published in 2019.

Hadley Wickham is the Chief Scientist at RStudio, a member of the R Foundation, and Adjunct Professor at Stanford University and the University of Auckland. He builds tools (both computational and cognitive) to make data science easier, faster, and more fun. You may be familiar with his packages for data science (the tidyverse: including ggplot2, dplyr, tidyr, purrr, and readr) and principled software development (roxygen2, testthat, devtools, pkgdown). Much of the material for the course is drawn from two of his existing books, Advanced R and R Packages, but the course also includes a lot of new material that will eventually become a book called “Tidy tools”.

Mara Averick (better known as @dataandme) is our tidyverse developer advocate. She got into R by way of a long-time love of the NBA and (fantasy) basketball. When not catering to the every whim of her dogs, she can be found: perusing weird words; indulging her bibliomania; and/or quantifying, visualizing, and watching Archer.