I am completing my Ph.D. in information visualization and HCI at the University of Michigan School of Information with advisor Eytan Adar. Prior degrees include an M.S.I. in Information Analysis & Retrieval from the University of Michigan School of Information as well as an M.F.A. (Experimental Poetics and Prose) from the Jack Kerouac School for Disembodied Poetics at Naropa University.
I am passionate about visual analysis and communication around data. As used online by news organizations, scientists, and data enthusiasts, information visualizations provide context and support deeper analytical insights related to data and text information. Yet supporting the production of high quality visualizations is challenging, as design processes are complex and tacit and professionals hard to find. Moreover, as abstract representations, visualizations have the potential to mislead or bias interpretations if not designed carefully. My work focuses on deepening understanding of trade-offs that affect visualization practice, including those that occur in the complex design processes used to create interactive visualizations and those related to heuristics that users bring to interpretation. I develop tools and mechanisms to address trade-offs in design to enhance the efficiency of visualization production and intepretation among diverse audiences of online users.
I have worked in depth on topics in narrative visualization, or the use of graphics to tell stories around data. I've demonstrated an approach for automatically generating and annotating visualizations to accompany news, proposed a rhetorical framework for understanding how narrative visualizations persuade users to accept a given framing of data, and more recently, studied and proposed a model for supporting effective visualization presentation structuring by non-professional designers (forthcoming, IEEE InfoVis). I am also interested in social factors affecting interaction around visualizations, such as the effects of social influences on individual and group level accuracy in crowdsourced visual analysis. Finally, I study how uncertainty can be conveyed for complex visualization formats in ways that are intuitive for a large number of users. Find out more about current and past research here.
To contact me directly, email me at jessica dot hullman at gmail or jhullman at umich dot edu.