David Burlinson
Information Science
david.burlinson@colorado.edu

David Burlinson earned a PhD in computer science from the University of North Carolina at Charlotte and has spent the past nine years expanding his love of computer science and computational thinking. His focus has been on research related to visual encoding, visualization and visual analytics, environmental impact, and pedagogically-sound computer science education. He has a particular affinity for web application design and responsive, interactive interfaces and visualizations and has self-taught up and down the full stack. His favorite language is JavaScript. In his "spare time," he enjoys honing his cooking skills and playing real-time strategy games.

 

Publications

  • K. Wu, E. Petersen, T. Ahmad, D. Burlinson, E. S. Tanis, & D. Albers Szafir. 2021. Understanding Data Accessibility for People with Intellectual and Developmental Disabilities. (to appear) In Proceedings of the 2021 Conference on Human Factors in Computing Systems (CHI ‘21). (Yokohama, Japan–May 8-13, 2021). DOI: https://doi.org/10.1145/3411764.3445743. [Best Paper Award]. pdf.
  • David Burlinson & Danielle Albers Szafir. 2020. Shape size judgments are influenced by fill and contour closure. In Proceedings of the Annual Meeting of the Vision Sciences Society, (St. Pete Beach, Florida (virtual) –June 19-24, 2020). doi:https://doi.org/10.1167/jov.20.11.1640

 

In the news

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ATLAS @ CHI 2021

May 14, 2021

ATLAS researchers have 10 published works and one special interest group associated with the CHI 2021 conference, the world’s preeminent conference for the field of human-computer interaction. Held virtually, CHI 2021, also known as ACM’s Conference on Human Factors in Computing Systems, took place May 8-13.

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Data accessibility: Leveling the field for those with intellectual and developmental disabilities

May 10, 2021

In a world where decisions of all kinds are based on statistical information, maximizing access to data is more important than ever. However, a recent study finds that common practices may be cutting large portions of the population out of the picture.