TJ Mahr
Assistant Scientist at University of Wisconsin-Madison
Madison, Wisconsin, United States
Summary
👤
Senior🎓
Top SchoolTJ Mahr is an Assistant Scientist and data-savvy language researcher with 13 years of experience using code and advanced statistical models to turn complex longitudinal and experimental data into actionable insights. Based at UW–Madison, he applies Bayesian, mixed-effects, GAMs, IRT and other methods to study language development in children with cerebral palsy while also developing R packages and reproducible pipelines to scale analyses. TJ blends research, software engineering, and teaching—mentoring students, presenting at conferences, and co-authoring NIH grant work—so his outputs are both scientifically rigorous and usable by collaborators. An active open-source contributor, he improved user-facing progress filtering and testing in the widely used drake R pipeline, reflecting a focus on reliability and user experience in research software.
13 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Communication Sciences and Disorders, Doctor of Philosophy (Ph.D.), Communication Sciences and Disorders at University of Wisconsin-Madison
English, Spanish
Stackoverflow
3,896reputation
203kreached
24answers
0questions
r
top-5%
dplyr
top-5%
Github Skills (24)
reproducible-research10
r-package10
r10
drake10
data-science9
testing9
dplyr9
rmarkdown9
workflow-engine8
cluster-computing7
parallel-computing7
accelerated-computing7
high-performance7
scientific-computing7
pandoc6
Programming languages (12)
Github contributions (5)
ropensci/drake
Mar 2019 - Mar 2019
An R-focused pipeline toolkit for reproducibility and high-performance computing
Role in this project:
Data Scientist
Data ScientistContributions:15 commits, 2 PRs, 5 comments in 1 day
Contributions summary:TJ primarily contributed to enhancing the `drake` R package, focusing on features related to progress tracking and filtering. They implemented functionality to filter build progress results based on various states ("done", "running", "failed", "none"). The user simplified argument checking and refactored the code for better efficiency. Also, they added tests to validate the values returned by the `progress()` function. The contributions demonstrate a focus on improving the user experience and the reliability of the `drake` package.
pipelinehigh-performance-computingscientific-computingfocusedperformance
tjmahr/tjm.praat
May 2020 - Mar 2021
Contributions:18 commits, 13 pushes, 1 branch in 10 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.