Jessica Hullman is an Americancomputer scientist and the Ginni Rometty professor ofComputer Science atNorthwestern University. Hullman was formerly faculty at theUniversity of Washington Information School (2015-2018). She is known for her research inInformation visualization andUncertainty quantification.
Hullman graduatedmagna cum laude fromOhio State University with a Bachelor of Arts degree in Comparative Studies. She obtained a Masters of Fine Arts degree in Writings and Poetics fromNaropa University. Hullman received her Master of Science in Information and Ph.D in Information Science from theUniversity of Michigan - School of Information, where she was advised by Eytan Adar. She completed a postdoctoral fellowship at theUniversity of California, Berkeley Computer Science Department withManeesh Agrawala.[1]
Hullman has made contributions to topics including uncertainty visualization,Bayesian cognition, human-AI interaction, decision-making under uncertainty, and evaluation of software and interfaces. Her work has contributed new visualization types to help readers develop an intuitive sense of uncertainty, such as hypothetical outcome plots.[2]
Hullman has given many invited lectures and keynote presentations, including "Strategic Communication of Uncertainty" to the President's Council of Advisors on Science & Technology. Hullman is co-director of the Midwest Uncertainty (MU) Collective atNorthwestern University.
Hullman has written articles for the popular press related to communicating uncertainty, including forWired (withAndrew Gelman),[3]Scientific American,The Hill andNational Review (with Allison Schrager).[4] She is a contributor toAndrew Gelman's blog, Statistical Modeling, Causal Inference, and Social Science.
Hullman was selected as a Microsoft Research Faculty Fellowship in 2019.[5] She is the recipient of numerous best paper awards.[6]
