* denotes student advisee at time of submission. I use an authoring convention where students are listed first. Through 2016, I appear earlier in the list when I am the primary faculty mentor. From 2017 - present, I list myself last when I am the primary faculty mentor.


Kale, A.*, Kay, M., and Hullman, J. Visual Reasoning Strategies and Satisficing: How Uncertainty Visualization Design Impacts Effect Size Judgments and Decisions. IEEE VIS 2020 Best Paper Award. preprint

Kim, YS.*, Kayongo, P., Grunde-McLaughlin, M., and Hullman, J. Bayesian-Assisted Inference from Visualized Data. IEEE VIS 2020. preprint

Hong, S., Hullman, J., and Bertini, E. Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs. ACM CSCW 2020. PDF

Hofman, J., Goldstein, D., Hullman, J. How Visualizing Inferential Uncertainty can Mislead Readers About Treatment Effects in Scientific Results. ACM CHI 2020. Honorable Mention (Top 5% Submissions) PDF

Nguyen*, F., Qiao*, X., Heer, J., Hullman, J. Exploring the Effects of Aggregation Choices on Untrained Visualization Users' Generalizations from Data. Computer Graphics Forum 2020. PDF


Hullman, J. Why Authors Don't Visualize Uncertainty. IEEE VIS 2019. PDF

Xiong, C., Shapiro, J., Hullman, J., Franconeri, S. Illusion of Causality in Visualized Data. IEEE VIS 2019. PDF

Kim*, YS., Walls, L., Krafft, P., and Hullman, J. Modeling the Interpretation of Visualized Statistics as Bayesian Cognition. Behavioral Economics Workshop at Economics and Computation (EC) 2019. PDF Github

Hullman, J. Confronting Unknowns: How to Read Common Visualizations of Uncertainty. Scientific American. Sept. 2019. PDF

Kim*, YS., Walls, L., Krafft, P., and Hullman, J. A Bayesian Cognition Approach to Improve Data Visualization. ACM CHI 2019. PDF Github

Kim*, YS., Dontcheva, M., Adar, E., and Hullman, J. Vocal Shortcuts for Creative Experts. ACM CHI 2019. PDF

Kale*, A., Kay, M., and Hullman, J.. Decision-Making Under Uncertainty in Research Synthesis: Designing for the Garden of Forking Paths. ACM CHI 2019. PDF

Phelan, C., Hullman, J., Kay, M., and Resnick, P. Some Prior(s) Experience Necessary: Templates for Getting Started with Bayesian Analysis. ACM CHI 2019. PDF

Nguyen*, F., Shrestha*, S., Germuska, J., Kim*, YS., and Hullman, J.. Belief-Driven Data Journalism. Computation+Journalism 2019. PDF


Hullman, J., Qiao*, X., Correll, M., Kale*, A., and Kay, M. In Pursuit of Error: A Survey of Uncertainty Visualization Evaluation. IEEE VIS 2018. PDF Supplement

Kale*., A., Nguyen*, F., Kay, M., and Hullman, J.. Hypothetical Outcome Plots Help Untrained Observers Judge Trends in Ambiguous Data. IEEE VIS 2018. PDF

Hullman, J., and Bach, B. Picturing Science: Design Patterns in Graphical Abstracts. DIAGRAMS 2018. PDF

Hullman, J., Kim*, YS., Nguyen*, F., Speers, L., and Agrawala, M. Improving Comprehension of Measurements Using Concrete Re-expression Strategies. ACM CHI 2018. PDF

Fernandes, M., Walls, L., Munson, S., Hullman, J., and Kay, M. Uncertainty Displays Using Quantile Dotplots or CDFs Improve Transit Decision-Making. ACM CHI 2018. Honorable Mention (Top 5% Submissions) PDF


Qu*, Z. and Hullman, J.. Keeping Multiple Views Consistent: Constraints, Validations, and Exceptions in Visualization Authoring. IEEE InfoVis 2017. Honorable Mention (Top 3 Papers) PDF

Kim*, YS., Reinecke, K., and Hullman, J.. Data Through Others' Eyes: The Impact of Visualizing Others’ Expectations on Visualization Interpretation. IEEE InfoVis 2017. PDF

Hullman, J., Kay, M., Kim*, YS., and Shrestha, S. Imagining Replications: Graphical Prediction & Discrete Visualizations Improve Recall & Estimation of Effect Uncertainty. IEEE InfoVis 2017. PDF

Hullman, J., Kosara, R., and Lam, H. Finding a Clear Path: Structuring Strategies for Visualization Sequences. EuroVis 2017. PDF

Kim*, YS, Reinecke, K., and Hullman, J. Explaining the Gap: Visualizing One's Predictions Improves Recall and Comprehension of Data. ACM CHI 2017. Best Paper Award (To 1% Submissions) PDF

Kim, Y., Wongsuphasawat, K., Hullman, J., and Heer, J. Graphscape: A Model for Automated Reasoning About Visualization Similarity and Sequencing. ACM CHI 2017. Honorable Mention (Top 5% Submissions) PDF

Adar, E., Gearig, C., Balusubramanian, A., and Hullman, J. Persalog: Personalization of News Article Content. ACM CHI 2017. PDF


Kim*, YS, Hullman, J., Burgess, M., and Adar, E. SimpleScience: Lexical Simplification of Scientific Terminology. EMNLP 2016 PDF

Hullman, J. Why Evaluating Uncertainty Visualization is Error Prone. Proc. BELIV 2016 PDF

Qu*, Z. and Hullman, J. Evaluating Visualization Sets: Trade-offs Between Local Effectiveness and Global Consistency. Proc. BELIV 2016 PDF

Kim*, YS, Hullman, J., and Agrawala, M. Generating Personalized Spatial Analogies for Distances and Areas. ACM CHI 2016 PDF | Data repository | Tapestry Keynote | Atlas of Me Chrome plugin

Kay, M., Kola, T., Hullman, J., and Munson, S. When(ish) is My Bus? User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems. ACM CHI 2016 PDF, Code repository


Hullman, J., Resnick, P., and Adar, E. Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences About Reliability of Variable Ordering. PLOS ONE 2015. Animated PDF (view in Adobe Acrobat) | Animated appendix | Zipped results | Zipped interface/stimuli

Kim*, YS and Hullman, J. Expectation Visualization: Opportunities for Personalized Feedback. IEEE InfoVis 2015 Workshop on Personal Visualization. Chicago, IL (Oct. 25, 2015). PDF

Kim*, YS, Hullman, J., and Adar, E. DeScipher: A Text Simplification Tool for Science Journalism. Computation+Journalism 2015. PDF

Gearig, C, Adar, E., and Hullman, J., Designing for Personalized Article Content. Computation+Journalism 2015. PDF

Hullman, J., Krupka, E., and Adar, E. Evaluating Approaches To Crowdsourced Visual Analytics. Paper selected for presentation at Collective Intelligence 2015.

Hullman, J., Diakopoulos, N., Momeni Roochi, E., and Adar, E. Content, Context, and Critique: Commenting on a Data Visualization Blog, ACM CSCW 2015. PDF


Gao, T., Hullman, J., Adar, E., Hecht, B., and Diakopoulos, N. NewsViews: An Automated Pipeline for Creating Custom Geovisualizations for News. ACM CHI 2014. Demo, PDF


Hullman, J. Understanding and Supporting Trade-offs in the Design of Visualizations for Communication. Dissertation, University of Michigan School of Information, 2013.

Lease, M., Hullman, J., Bigham, J.P., Bernstein, M.S., Kim, J., Lasecki, W.S., Bakhshi, S., Mitra, T., and Miller, R.C. Mechanical Turk is Not Anonymous. Social Science Research Network 2013. [Reached Top Ten Downloaded Articles]. Available here.

Hullman, J., Drucker, S., Henry-Riche, N., Lee, B., Fisher, D., and Adar, E. A Deeper Understanding of Sequence in Narrative Visualization, IEEE InfoVis 2013. PDF

Hullman, J. How Prior Knowledge Affects the Processing of Visualized Data. ACM CHI 2013, Many People Many Eyes workshop. Paris, France (Apr. 28, 2013). PDF

Hullman, J., Diakopoulos, N., and Adar, E. Contextifier: Automatic Generation of Annotated Stock Visualizations. ACM CHI 2013. Demo, PDF


Hullman, J., Rhodes, R., Rodriguez, F., and Shah, P. (2012) Research on Graph Comprehension and Data Interpretation: Implications for Score Reporting. In Zapata, D., & Zwick, R. (Eds.) Recent Research on Score Reporting. Princeton, NJ: Educational Testing Service. PDF


Hullman, J., Adar, E., and Shah, P. Benefitting InfoVis with Visual Difficulties. IEEE InfoVis 2011. Honorable Mention (Top 3 Papers) PDF

Hullman, J., and Diakopolous, D. Visualization Rhetoric: Framing Effects in Narrative Visualization. IEEE InfoVis 2011. PDF

Hullman, J., Adar, E., and Shah, P. The Effect of Social Information on Visual Judgments. ACM CHI 2011. PDF

Hullman, J. Not all HITs are Created Equal: Controlling for Reasoning and Learning Processes in MTurk. Position paper presented at ACM CHI 2011, Workshop on Crowdsourcing and Human Computation. Vancouver, BC (May 8, 2011). PDF, blog post

Hullman, J., McQuaid, M., Chia, Y., Lin, T., and Zhang, Z. Chance-it: Motivating Collaborative Exploration using Spatial Layout on a Multitouch Surface. Position paper presented at ACM CHI 2011, Workshop on Large Displays in Urban Life. Vancouver, BC (May 7, 2011).PDF

2010 and earlier

Hullman, J. Visual Texts: Adapting Narratology for Information Visualization. Position paper and featured presenter at Telling Stories with Data workshop, IEEE InfoVis, Oct. 2010, Salt Lake City, UT. PDF slides

Hullman, J. Framing Artistic Visualization: Aesthetic Object as Evidence. Position paper presented at ACM Creativity & Cognition workshop Understanding the Creative Conversation: Modeling to Engagement, Oct. 2009, Berkeley, CA. PDF