Jessica Hullman

Jessica Hullman is a computer scientist and the Ginni Rometty professor of Computer Science at Northwestern University. 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]

Hullman started her career as faculty at the University of Washington Information School, where she was also adjunct assistant professor in Computer Science, and affiliated with the Interactive Data Lab and DUB (Design Use Build) group.

Work

Jessica Hullman has published peer-reviewed journal articles on topics including uncertainty visualization, Bayesian cognition, human-AI interaction, decision-making under uncertainty, and evaluation of visualizations. Her work has contributed new visualization types to help readers develop an intuitive sense of uncertainty, such as hypothetical outcome plots. Notable works include

  • Visual Reasoning Strategies for Effect Size Judgments and Decisions[2]
  • In Pursuit of Error: A Survey of Uncertainty Visualization Evaluation[3]
  • Visualization rhetoric: Framing effects in narrative visualization[4]
  • Why Authors Don't Visualize Uncertainty[5]
  • Hypothetical Outcome Plots Outperform Error Bars and Violin Plots for Inferences about Reliability of Variable Ordering[6]

Hullman has given many invited lectures and keynote presentations, including "Strategic Communication of Uncertainty" to the President's Council of Advisors on Science & Technology, "How to Visually Communicate Uncertain Data" to the Conference on Global Risk, Uncertainty, & Volatility, "Beyond Visualization: Theories of Inference to Improve Data Analysis & Communication" [7] and "The Visual Uncertainty Experience" at OpenVisConf.[8] Hullman is co-director of the Midwest Uncertainty (MU) Collective at Northwestern University.

In addition to her scholarly work, Hullman has written articles for the popular press related to visualizing uncertainty, including for Wired ("Is Your Chart a Detective Story? Or a Police Report?", with Andrew Gelman),[9] Scientific American, The Hill and National Review ("We Need Better Risk Communication to Combat the Coronavirus", with Allison Schrager).[10] She is a contributor to Andrew Gelman's blog, Statistical Modeling, Causal Inference, and Social Science.

Awards

References

  1. ^ "Hullman, Jessica | Faculty | Northwestern Engineering". www.mccormick.northwestern.edu. Retrieved 2021-05-18.
  2. ^ Kale, Alex; Kay, Matthew; Hullman, Jessica (2021-02-01). "Visual Reasoning Strategies for Effect Size Judgments and Decisions". IEEE Transactions on Visualization and Computer Graphics. 27 (2): 272–282. arXiv:2007.14516. doi:10.1109/TVCG.2020.3030335. ISSN 1077-2626. PMID 33048681. S2CID 221662355.
  3. ^ Hullman, Jessica; Qiao, Xiaoli; Correll, Michael; Kale, Alex; Kay, Matthew (2019-01-01). "In Pursuit of Error: A Survey of Uncertainty Visualization Evaluation". IEEE Transactions on Visualization and Computer Graphics. 25 (1): 903–913. doi:10.1109/TVCG.2018.2864889. ISSN 1077-2626. PMID 30207956. S2CID 51920450.
  4. ^ Hullman, J.; Diakopoulos, N. (2011-12-01). "Visualization Rhetoric: Framing Effects in Narrative Visualization". IEEE Transactions on Visualization and Computer Graphics. 17 (12): 2231–2240. doi:10.1109/TVCG.2011.255. ISSN 1077-2626. PMID 22034342. S2CID 10436985.
  5. ^ Hullman, Jessica (2019-12-01). "Why Authors Don't Visualize Uncertainty". IEEE Transactions on Visualization and Computer Graphics. 26 (1): 130–139. arXiv:1908.01697. doi:10.1109/TVCG.2019.2934287. ISSN 1077-2626. PMID 31425093. S2CID 19410506.
  6. ^ 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. 10 (11): e0142444. Bibcode:2015PLoSO..1042444H. doi:10.1371/journal.pone.0142444. ISSN 1932-6203. PMC 4646698. PMID 26571487.
  7. ^ "Seminar: Jessica Hullman | Human-Computer Interaction Institute". hcii.cmu.edu. Retrieved 2021-04-13.
  8. ^ The Visual Uncertainty Experience - Jessica Hullman, retrieved 2021-04-13
  9. ^ "Is Your Chart a Detective Story? Or a Police Report?". Wired. ISSN 1059-1028. Retrieved 2021-05-18.
  10. ^ "We Need Better Risk Communication to Combat the Coronavirus". National Review. 2020-08-19. Retrieved 2021-05-18.
  11. ^ Birenbaum, Gabby (2019-05-08). "Journalism Prof. Jessica Hullman receives Microsoft Research Faculty Fellowship". The Daily Northwestern. Retrieved 2021-04-06.
  12. ^ a b c d e f "iSchool Directory | Information School | University of Washington". ischool.uw.edu. Retrieved 2021-04-06.
  13. ^ "NSF Award Search: Award # 1749266 - CAREER: Enhancing Critical Reflection on Data by Integrating Users' Expectations in Visualization Interaction". www.nsf.gov. Retrieved 2021-05-18.