Scholar
Matthew Kay
Google Scholar ID: NO5adqUAAAAJ
Associate Professor, Northwestern University
Citations & Impact
Citations
5,933
H-index
35
i10-index
62
Publications
20
Co-authors
12
list available
Contact
Publications
Cited
0
Resume (English only)
Academic Achievements
- He has published multiple papers and received several awards, including:
- - 'In dice we trust: Uncertainty displays for maintaining trust in election forecasts over time' at CHI 2024, which won the Best Paper Award (top 1%).
- - 'Watching the election sausage get made: How data journalists visualize the vote counting process in U.S. elections' at CHI 2024, which received an Honorable Mention (top 5%).
- - 'Odds and insights: Decision quality in exploratory data analysis under uncertainty' at CHI 2024, which received an Honorable Mention (top 5%).
- - 'Swaying the public? Impacts of election forecast visualizations on emotion, trust, and intention in the 2022 U.S. midterms' at VIS 2023, which won the Best Paper Award (top 1%).
- - 'ggdist: Visualizations of distributions and uncertainty in the grammar of graphics' at VIS 2023, with an associated R package.
Research Experience
- He has extensive research experience in areas such as uncertainty visualization and usable statistical tools. His current research focuses on: 1. Communicating uncertainty: Studying how people interpret their data and what goals they have for it to improve data presentations. 2. Usable statistics: Exploring the limitations of current statistical tools and developing more user-friendly alternatives.
Education
- Previously, he was an Assistant Professor at UMSI.
Background
- An Associate Professor in Computer Science and Communication at Northwestern University, focusing on human–computer interaction and information visualization. His research includes work on visualizing uncertainty, usable statistics, and visualization literacy. He uses a multi-faceted approach, including qualitative and quantitative analysis of behavior, building and evaluating interactive systems, and designing and testing visualization techniques. He co-directs the Midwest Uncertainty Collective (MU collective) and is the author of the tidybayes and ggdist R packages.
Miscellany
- Hobbies and interests not mentioned
