JooYoung Seo is a Ph.D. candidate (ABD) in Learning, Design, and Technology program at the Pennsylvania State University, RStudio’s trusted data-science instructor (e.g., Tidyverse & Shiny), and internationally certified accessibility professional.

As a learning scientist and software engineer, his research topics involve accessible computing for all learners with dis/abilities, inclusive makerspaces, and Computer-Supported Collaborative Learning (CSCL) and Human-Computer Interaction (HCI) with special focus on accessibility and universal design. Recently for his dissertation research, he employs quantitative ethnography based on Knowledge Discovery in Databases (KDD) that combines reproducible data science/computational linguistics/machine learning with conventional ethnographic perspectives on a large-scale and/or big-data-sized textual archives longitudinally produced by the National Federation of the Blind (NFB) mailing listservs. Through the novel and scientifically rigorous mixed-methods, he strives to uncover informal learning cultures and shared knowledge patterns of blind individuals pursuing STEM disciplines to better identify the challenges and solutions of current STEM accessibility voiced by the world-largest blind community.

As an emerging young scholar, he has first-authored several top-tier conferences and journal papers in the learning sciences, educational technology, and assistive technology fields (e.g., International Conference of the Learning Sciences; International Conference on Computer-Supported Collaborative Learning; TechTrends; Journal on Technology & Persons with Disabilities).

He is an avid R and Python programmer who has developed and published some statistical computing packages to the peer-reviewed Comprehensive R Archive Network (CRAN) including “ezpickr” , “mboxr” , and “youtubecaption” while leading the projects on reproducible research templates for Journal of Learning Analytics and Journal of Educational Data Mining.

He is also an official code-contributor (CTB) for some notable data science packages, such as shiny, rmarkdown, bookdown, distill, and more.

His expertise in both data science and accessibility offered opportunity for him to intern at RStudio in summer 2020 to officially be involved in accessibility-related projects for RStudio Server/Desktop IDE and their other products (e.g., shiny).

For more information on JooYoung Seo can be found in his downloadable/online CV, and reproducible source code behind the CV is also available on his GitHub repository.