R/Medicine 2025
AN R CONSORTIUM VIRTUAL CONFERENCE
WHY ATTEND
The R/Medicine conference provides a forum for sharing R based tools and approaches used to analyze and gain insights from health data. Conference workshops provide a way to learn and develop your R skills. Midweek demos allow you to try out new R packages and tools, and our hackathon provides an opportunity to learn how to develop new R tools. The conference talks share new packages, and successes in analyzing health, laboratory, and clinical data with R and Shiny with a vigorous ongoing discussion with speakers (with pre-recorded talks) in the chat.
November Webinar: Containerization and R for Reproducibility and More
Abstract
Containerization has become a dominant computing paradigm for computing in the past decade due to its many advantages: isolation and security, scalability and efficiency with lightweight containers sharing an operating kernel and resources, and portability across cloud computing providers. For the researcher, analyst, or R user, containers have applications ranging from reproducible analytical environments to packaging statistical code to use in web applications. I will discuss how biomedical researchers can make use of containerization technology, particularly the tools provided by the Rocker Project, which publishes powerful standardized containers for the R language.
Registration
Speaker Bio
Noam Ross is a computational disease ecologist and Executive Director of rOpenSci, a nonprofit dedicated to promoting open science and validating data science and computational methods. He is a core member of the Rocker Project, which maintains standardized containers for the R computer language. Noam’s work includes spearheading rOpenSci’s work in software peer review, developing a widely emulated system for leveraging the academic peer-review process coupled with state-of-the art automated code analysis to improve code quality in the scientific software in ecosystem, as well as using review as a mechanism for community building and training. His research interests and contributions span a wide range of topics, including disease ecology, zoonotic spillover, mechanistic modeling of disease dynamics, and non-parametric data science methods. His applied work includes creating early outbreak assessment models for the U.S. Defense Threat Reduction Agency, and modeling and forecasting for New York State’s COVID-19 emergency response. Noam holds a Ph.D. in theoretical ecology from the University of California-Davis and a B.Sc. from Brown University.
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