No conference would be what it is without the support of those speaking, and EARL is no exception. Our speakers come from around the world to present their ideas and approaches. They represent companies of all sizes and give their time to share their knowledge and experience with attendees. We're currently interested in receiving abstracts from anyone who has an interesting R-related story to tell, particularly if that story relates to a commercial use of the R language.

Keynote speakers:

Ricardo Bion

Ricardo Bion is a Data Science manager at Airbnb, where he leads two teams focused on product research and experimentation. He obtained his PhD from Stanford University, and also has graduate degrees from the University of Milan, University of Potsdam, and University of Eastern Finland. He has published over 20 peer-reviewed articles, with more than 500 citations combined. Ricardo is interested in reproducible research, and in building tools and developing education resources to scale the impact of Data Science teams. He is an active R developer, and has built internal R packages at Airbnb and open source R packages. He can be followed on Twitter @ricardobion.

Jenny Bryan

Jenny Bryan is an Associate Professor of Statistics at the University of British Columbia and part of the leadership of rOpenSci. She teaches data analysis and wrangling with R in STAT 545 and the Master of Data Science Program. She's the author of the googlesheets package and generally kvetches a lot about spreadsheets, version control, and workflow. Follow Jenny on Twitter as @jennybryan or on GitHub as @jennybc.


Tanya Cashorali

Popular Cross-Industry Applications of R

Aedin Culhane

R in Cancer Research - Integrating Big Data in Genomics

Danielle Dean & Jaya Mathew

Building an on-prem SQL Server Predictive Maintenance Solution

Aniruddha Deshmukh

Harnessing the Power of R to Enrich Software Applications

Amar Dhand

Understanding hospital networks to improve patient outcomes and reduce healthcare costs

Aimee Gott

Replacing SAS by Stealth

Daniel Hadley

Using R to Save Taxpayer Dollars

Mark Hornick

Architectural Elements for Enabling R for Big Data

Kaori Ito

Data cleaning, visualization, and meta-analysis for literature data using Shiny

Tareef Kawaf

Communicating and sharing your analyses with R Markdown and RStudio Connect

Jared Lander

R for Everything

Francesca Lazzeri

Load Forecasting in Microgrid Systems with R and Cortana Intelligence Suite

Alexey Masyutin

Risk Model Validation with No Single Line of Code

Andy Nicholls

Replacing SAS by Stealth

Jeff Schneider

Computing Domain-Based Stratified Sample Allocations using R Shiny

Ritesh Srivastava

Movie Analytics 2.0: Predicting the next 100 million dollar movie through R

David Smith

Microsoft and the R Ecosystem

Filip Stachura

Rapid shiny development to blend experts knowledge into machine learning models

Simon Urbanek

RCloud - Collaborative Environment for Visualization and Big Data Analytics

Chetna Warade

Reddit sentiment analysis in R notebook