October useR Meetup: Lightning Talks!

This meetup will feature a series of 10-minute lightning talks on various topics.

Talk #1
Presented by Michael Thomas
Beyond #rstats: Workflow Management & Data Engineering in R

R has gained a reputation for being a great programming language for statistical analysis. Did you know that R has a vast amount of tools available for executing traditional data engineering and workflow tasks? We don’t buy the narrative that Python is the only “production-quality” data science language and will showcase R’s ability to interface with the command line, manage files and directories, access environmental variables, talk to SQL databases, and more!

Michael Thomas is the Chief Data Scientist at Ketchbrook Analytics, a software and analytics consulting firm out of Hartford, CT. He holds a B.S. in Accounting and Mathematics from Stonehill College, and an M.S. in Business Intelligence & Analytics from Saint Joseph’s University. He has worked across a multitude of industries during his career, including public accounting, marketing, banking, financial services, agriculture, insurance, and information technology. He is passionate about combining data, analytics, and software to help everyday businesses make better decisions and operate more efficiently.

Talk #2
Presented by Leo PeBenito

This lightning talk is a brief introduction to computational methods for addressing the current COVID-19 pandemic using R and the tidyverse. The classic SIR model will be applied to the Johns Hopkins University CSSE data set. Elements of the tidyverse will be explored through three vignettes: analysis using dplyr and purrr, visualization using tidyr and ggplot2, and when to return a tibble from a function.

Leo PeBenito's background is in chemistry and biophysics, and his favorite molecule is melittin. He currently works as a data scientist on topics related to signal processing and ML. Two people that inspire him are Esther Duflo and Hadley Wickham.

Talk #3
Presented by Arafath Hossain

This talk is about how we used R to productionalize a predictive model that helps business users interact with the model and use it as a powerful tool in their decision making. This application enables the business users to interact with the data, slice and dice the data and recalculate predictions based on their input changes.

Arafath Hossain is a data scientist at Illinois State University. Arafath received his bachelor in business administration from the University of Dhaka, Bangladesh, then worked in the market research and telecommunication industry before moving to the US and completing his MS in Technology. He works as a data scientist helping business partners improve student retention by identifying at-risk students early and prescribing possible interventions.

Talk #4
Presented by David Zimmermann
A brief introduction to the rintrojs package.

This talk shows how you can use the rintrojs package to create tours for shiny applications. A guided tour allows the developer of an app to show its users how the UI is designed to be used and to thoroughly explain certain aspects of an app increasing the user experience. The talk gives a brief introduction to the package and also shows how rintrojs can work with shinydashboards, tables, or leaflet maps.

David is a senior data scientist at Cologne Intelligence, a consulting firm specialised in software and data solutions, based in Cologne. He holds a PhD in economics/computational finance from the University of Witten/Herdecke, an MSc in Finance and Investment from the University of Edinburgh, UK, and a BA in economics and international politics from Zeppelin University, but eventually ventured off into data science, machine learning, and more and more R programming. He is interested in everything R related, be it the tidyverse, shiny, tidymodels, or raw performance using Rcpp.