Name: Tidier.jl: The Story Behind Rebuilding the {tidyverse} in Julia
Start: 2025-04-24T18:30:00-07:00
End: 2025-04-24T20:30:00-07:00
Location: Keck Center

How far would you be willing to go to make {tidyverse} faster? Would you learn C? Would you learn C++? For the people and teams behind packages like {data.table} and {collapse}, writing low-level code was the secret sauce for producing substantial performance gains over the canonical {tidyverse}. Yet tidyverse remains popular because of its interface and consistent design. Even within R, this interface has been reimplemented for multiple backends in packages like {dtplyr}, {tidytable}, {duckplyr}, {dbplyr}, and {tidypolars}. So many backends exist because as an interpreted language, R itself isn’t ideal for writing performant backend code – hence the popularity of {Rcpp}.

In January of 2023, Karandeep Singh decided to make {tidyverse} go faster by rewriting it in Julia, a just-in-time compiled language that has syntax similar to R but performance akin to C/C++. It began as a single package: [Tidier.jl](https://tidierorg.github.io/Tidier.jl/dev/)

With contributions from around the world, it has since expanded to 10+ packages implementing a majority of the {tidyverse}. This talk tells the story behind how Tidier.jl came to be, what it can do, and why Julia is worth a look for R users.

**Meeting Location:**
We'll be meeting at the Keck Center @ Chapman University room N107/N109. The space has a 40-person limit - If you RSVP but are unable to attend, please update your RSVP promptly to accommodate others interested in attending. If you show up prior to 6:30pm, please note that the doors to the facility may be locked.

**Meeting Time:**
We meet at 6:30pm to eat and socialize and presentations starts at 7pm.

**Food:**
Food and beverages will be catered by SoCal RUG for this event.

**Parking:**
The best parking option will be the Anderson Parking Structure conveniently next to the Chapman's Keck Center. From the entrance of the Anderson Parking Structure, navigate to the elevator on the far side of the parking structure. Take the elevator to the 1st floor, and you'll find yourself in an outdoor atrium. As you’re exiting the elevator, turn left through the glass doors into Swenson Hall. Continue down the hallway past the MakerSpace and the Ideation Zone (rooms N107/109) will be on your left. While street parking is an option, it may require a valid Chapman parking pass depending on the street you're on - Please pay attention to street signage and see everyone tonight!

***Legal Disclaimer:***
*The advice and/or information provided at this event is not endorsed by nor should it be construed as educational/legal advice from Chapman University.*

Southern California RUG

SoCal R Users Group (SoCal RUG)

R User Groups

R Consortium

UCI Merage School of Business

The Donald Bren’s School of Information

Chapman University's Fowler School of Engineering

Fowler School of Engineering

Technology

Statistical Computing

Big Data

Machine Learning

Data Analytics

Data Visualization

Predictive Analytics

Data Mining

R Project for Statistical Computing

Data Science

Programming in R

Applied Statistics

Business Intelligence

Open Source

Data Management

Karandeep Singh, MD, MMSc, is the Chief Health AI Officer for UC San Diego Health, and Joan and Irwin Jacobs Chancellor’s Endowed Chair and Associate Professor of Medicine in Biomedical Informatics at UC San Diego. In these roles, Dr. Singh oversees AI strategy and governance for the health system and leads AI initiatives within the Jacobs Center for Health Innovation.
 
He completed his internal medicine residency at UCLA Medical Center, where he served as chief resident, and a nephrology fellowship in the combined Brigham and Women’s Hospital and Massachusetts General Hospital program. He completed his medical education at the University of Michigan Medical School and holds a master’s degree in Biomedical Informatics from Harvard Medical School.
 
Prior to coming to UC San Diego, Dr. Singh was an associate professor at the University of Michigan, where he served as the Associate Chief Medical Information Officer of Artificial Intelligence at Michigan Medicine. His research focuses on addressing translational issues related to bringing AI into clinical practice, including transportability, generalizability, dataset shift, and clinical and operational outcomes. His research lab performed the first independent evaluations of several proprietary clinical prediction models, including the Epic Deterioration Index and the Epic Sepsis Model. His research has been cited in several policy documents, including the White House’s Blueprint for an Artificial Intelligence Bill of Rights, U.S. Department of Health and Human Services, U.S. Government Accountability Office, National Academy of Medicine, the UK Government Regulatory Horizons Council, New Zealand Ministry of Health, and in New York City’s Artificial Intelligence Strategy.

SoCal R Users Group (SoCal RUG)

Tidier.jl: The Story Behind Rebuilding the {tidyverse} in Julia

SoCal R Users Group (SoCal RUG)

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