Jessica Ruth Hullman

  • 382 Citations
20112023

Research output per year

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Personal profile

Research Interests

The goal of my research is to help more people make sense of complex information, and in particular to reason about uncertainty. Information visualizations leverage perception to summarize data in a cognitively efficient format, making them popular in the media and science. However, many visualizations and other data summaries fail to communicate effectively. One problem is that authors often omit uncertainty information, such as that data are interpreted as being more credible than they are. Another problem is that authors often assume that if the right information--data, statistic, finding etc.--is presented, the audience will naturally trust the presentation and make better decisions.

My research addresses these problems in two ways. First, I use of controlled experiments to identify and model how people reason with data, and in particular uncertainty. Secondly, I create novel interactive tools and techniques that aim to extend and amplify users' abilities to think with data by aligning with their internal representations of complex phenomena.

Education/Academic qualification

Information (Visualization), PhD, University of Michigan School of Information

… → 2013

Comparative Studies, BA, Ohio State University

… → 2003

Writing and Poetics, Prose Concentration, MFA, Naropa University

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Grants

  • Research Output

    • 382 Citations
    • 19 Conference contribution
    • 10 Article
    • 2 Software
    • 1 Review article

    Illusion of Causality in Visualized Data

    Xiong, C., Shapiro, J., Hullman, J. & Franconeri, S., Jan 2020, In : IEEE Transactions on Visualization and Computer Graphics. 26, 1, p. 853-862 10 p., 8805448.

    Research output: Contribution to journalArticle

  • Why Authors Don't Visualize Uncertainty

    Hullman, J., Jan 2020, In : IEEE Transactions on Visualization and Computer Graphics. 26, 1, p. 130-139 10 p., 8805422.

    Research output: Contribution to journalArticle

  • 1 Scopus citations

    A Bayesian cognition approach to improve data visualization

    Kim, Y. S., Walls, L. A., Krafft, P. & Hullman, J. R., May 2 2019, CHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, (Conference on Human Factors in Computing Systems - Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 6 Scopus citations

    Decision-making under uncertainty in research synthesis: Designing for the garden of forking paths

    Kale, A., Kay, M. & Hullman, J. R., May 2 2019, CHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, (Conference on Human Factors in Computing Systems - Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • 1 Scopus citations

    HCI for accurate, impartial and transparent journalism: Challenges and solutions

    Aitamurto, T., Birnbaum, L. A., Hullman, J. R., Ananny, M., Diakopoulos, N. A., Ritchie, N., Anderson, C. W. & Hanson, M., May 2 2019, CHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 3299007. (Conference on Human Factors in Computing Systems - Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution