Jessica Hullman

From Infogalactic: the planetary knowledge core
Jump to: navigation, search

Jessica Hullman is a computer scientist and the Ginni Rometty associate professor of Computer Science at Northwestern University. She is known for her research in Information visualization.

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, automated design of data visualizations, narrative visualization, 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]
  • A deeper understanding of sequence in narrative visualization[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 "How to Visually Communicate Uncertain Data", "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 and is the founder and editor of Multiple Views, a blog on visualization research.

Awards

References

  1. Lua error in package.lua at line 80: module 'strict' not found.
  2. Lua error in package.lua at line 80: module 'strict' not found.
  3. Lua error in package.lua at line 80: module 'strict' not found.
  4. Lua error in package.lua at line 80: module 'strict' not found.
  5. Lua error in package.lua at line 80: module 'strict' not found.
  6. Lua error in package.lua at line 80: module 'strict' not found.
  7. Lua error in package.lua at line 80: module 'strict' not found.
  8. Lua error in package.lua at line 80: module 'strict' not found.
  9. Lua error in package.lua at line 80: module 'strict' not found.
  10. Lua error in package.lua at line 80: module 'strict' not found.
  11. Lua error in package.lua at line 80: module 'strict' not found.
  12. 12.0 12.1 12.2 12.3 12.4 12.5 12.6 12.7 Lua error in package.lua at line 80: module 'strict' not found.
  13. Lua error in package.lua at line 80: module 'strict' not found.

External links