Jessica Hullman

Jessica Hullman is an American computer scientist and the Ginni Rometty professor of Computer Science at Northwestern University. Hullman was formerly faculty at the University of Washington Information School (2015-2018). She is known for her research in Information visualization and Uncertainty quantification.

Education

Hullman graduated magna cum laude from Ohio State University with a Bachelor of Arts degree in Comparative Studies. She obtained a Masters of Fine Arts degree in Writings and Poetics from Naropa University. Hullman received her Master of Science in Information and Ph.D in Information Science from the University of Michigan - School of Information, where she was advised by Eytan Adar. She completed a postdoctoral fellowship at the University of California, Berkeley Computer Science Department with Maneesh Agrawala.^[1]

Work

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 at Northwestern University.

Hullman has written articles for the popular press related to communicating uncertainty, including for Wired (with Andrew Gelman),^[3] Scientific American, The Hill and National Review (with Allison Schrager).^[4] She is a contributor to Andrew Gelman's blog, Statistical Modeling, Causal Inference, and Social Science.

Awards

Hullman was selected as a Microsoft Research Faculty Fellowship in 2019.^[5] She is the recipient of numerous best paper awards.^[6]