Jessica Hullman

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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.

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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]

References

  1. ↑ "Hullman, Jessica | Faculty | Northwestern Engineering". www.mccormick.northwestern.edu. Retrieved 2021-05-18.
  2. ↑ Hullman, Jessica; Resnick, Paul; Adar, Eytan (2015-11-16). "Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering". PLOS One. Public Library of Science. doi: 10.1371/journal.pone.0142444 . PMC   4646698 . Retrieved 2025-04-23.
  3. ↑ "Is Your Chart a Detective Story? Or a Police Report?". Wired. ISSN   1059-1028 . Retrieved 2021-05-18.
  4. ↑ "We Need Better Risk Communication to Combat the Coronavirus". National Review. 2020-08-19. Retrieved 2021-05-18.
  5. ↑ "Microsoft Research Faculty Fellows" . Retrieved 2025-04-23.
  6. ↑ "iSchool Directory | Information School | University of Washington". ischool.uw.edu. Retrieved 2021-04-06.
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