Matthew Kay

Projects

Below is a smattering of research areas I have worked in or am currently working in. The list of projects for the cross-institutional lab that I co-direct with Jessica Hullamn, the MU collective, is also a good source for projects I am working on.

Communicating uncertainty

We are increasingly exposed to sensing and prediction in our daily lives (“how many steps did I take today?”, “how long until my bus shows up?”, “how much do I weigh?”). Uncertainty is both inherent to these systems and usually poorly communicated. To build understandable data presentations, we must study how people interpret their data and what goals they have for it. This informs the way that we should communicate results from our models, which in turn determines what models we must use in the first place.

  1. ggdist: Visualizations of distributions and uncertainty (R package)

  2. tidybayes: Tidy data and geoms for Bayesian models (R package)

  3. A probabilistic grammar of graphics

    Xiaoying Pu and Matthew Kay

  4. Visual reasoning strategies for effect size judgments and decisions

    Alex Kale, Matthew Kay, and Jessica Hullman

  5. Uncertainty displays using quantile dotplots or CDFs improve transit decision-making

    Michael Fernandes, Logan Walls, Sean Munson, Jessica Hullman, and Matthew Kay

  6. When (ish) is my bus? User-centered visualizations of uncertainty in everyday, mobile predictive systems

    Matthew Kay, Tara Kola, Jessica Hullman, and Sean Munson

  7. How good is 85%? A survey tool to connect classifier evaluation to acceptability of accuracy

    Matthew Kay, Shwetak N. Patel, and Julie A. Kientz

  8. Challenges in personal health tracking: The data isn’t enough

    Matthew Kay

  9. There’s no such thing as gaining a pound: Reconsidering the bathroom scale user interface

    Matthew Kay, Dan Morris, mc schraefel, and Julie A. Kientz

    • Ubicomp 2013
    • Best paper award (top 1%)
    • PDF
    • BibTeX

Usable statistics

Science is failing all around us! Nothing replicates! Things may not be as dire as all that, but in fields like HCI and psychology, the statistical tools we use are failing us: these tools let users wander around without guidance and produce results without assisting users in interpretation. What would usable statistical tools look like?

My work in usable statistical tools is nascent, but follows from my existing work in improving statistical communication in the fields of HCI and Information Visualization. For more information on that work, see the publications below and the Special Interest Group on Transparent Statistics in HCI.

  1. Increasing the transparency of research papers with Explorable Multiverse Analyses

    Pierre Dragicevic, Yvonne Jansen, Abhraneel Sarma, Matthew Kay, and Fanny Chevalier

  2. The garden of forking paths in visualization: A design space for reliable exploratory visual analytics

    Xiaoying Pu, Matthew Kay

  3. Imagining replications: Graphical prediction & discrete visualizations improve recall & estimation of effect uncertainty

    Jessica Hullman, Matthew Kay, Yea-Seul Kim, and Samana Shrestha

  4. Researcher-centered design of statistics: Why Bayesian statistics better fit the culture and incentives of HCI

    Matthew Kay, Gregory Nelson, and Eric Hekler

  5. Beyond Weber’s Law: A second look at ranking visualizations of correlation

    Matthew Kay and Jeffrey Heer

Personal informatics for health

  1. Cognitive rhythms: Unobtrusive and continuous sensing of alertness using a mobile phone

    Saeed Abdullah, Elizabeth Murnane, Mark Matthews, Matthew Kay, Julie Kientz, Geri Gay, and Tanzeem Choudhury

  2. There’s no such thing as gaining a pound: Reconsidering the bathroom scale user interface

    Matthew Kay, Dan Morris, mc schraefel, and Julie A. Kientz

    • Ubicomp 2013
    • Best paper award (top 1%)
    • PDF
    • BibTeX

  3. Challenges in personal health tracking: The data isn’t enough

    Matthew Kay

  4. PVT-Touch: Adapting a reaction time test for touchscreen devices

    Matthew Kay, Kyle Rector, Sunny Consolvo, Ben Greenstein, Jacob O. Wobbrock, Nathaniel F. Watson, and Julie A. Kientz

  5. Lullaby: A capture & access system for understanding the sleep environment

    Matthew Kay, Eun Kyoung Choe, Jesse Shepherd, Benjamin Greenstein, Nathaniel Watson, Sunny Consolvo, and Julie A. Kientz

    • Ubicomp 2012
    • Best paper award (top 1%)
    • PDF
    • BibTeX

Gender representation in image search

  1. Unequal representation and gender stereotypes in image search results for occupations

    Matthew Kay, Cynthia Matuszek, and Sean Munson