Jessica Hullman
· Ginni Rometty Professor of Computer ScienceNorthwestern University · Chemical Engineering
Active 1800–2026
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About
Jessica Hullman is a faculty member in the Department of Computer Science at Northwestern University, located in the McCormick School of Engineering. Her research focuses on challenges and limitations that arise when people theorize and draw inductive inferences from data. She explores how to best align data-driven interfaces and summaries with human reasoning capabilities, examining the role of interactive analysis across different stages of a statistical workflow. Her work involves evaluating data interfaces, developing tools to support reasoning under uncertainty, and understanding how these tools can be applied in domains such as strategic games and privacy. Hullman approaches these problems by drawing on formal models of rational inference to compare and propose solutions.
Research topics
- Computer Science
- Artificial Intelligence
- Political Science
- Econometrics
- Mathematics
- Data science
- Statistics
- Demography
- Economics
- Psychology
Selected publications
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
Proceedings of the ACM on Human-Computer Interaction · 2020 · 207 citations
As the use of machine learning (ML) models in product development and data-driven decision-making processes became pervasive in many domains, people's focus on building a well-performing model has increasingly shifted to understanding how their model works. While scholarly interest in model interpretability has grown rapidly in research communities like HCI, ML, and beyond, little is known about how practitioners perceive and aim to provide interpretability in the context of their existing workf…
2020 · 79 citations
Senior authorCorrespondingWhen presenting visualizations of experimental results, scientists often choose to display either inferential uncertainty (e.g., uncertainty in the estimate of a population mean) or outcome uncertainty (e.g., variation of outcomes around that mean) about their estimates. How does this choice impact readers' beliefs about the size of treatment effects? We investigate this question in two experiments comparing 95% confidence intervals (means and standard errors) to 95% prediction intervals (means…
Information, incentives, and goals in election forecasts
Judgment and Decision Making · 2020 · 29 citations
Abstract Presidential elections can be forecast using information from political and economic conditions, polls, and a statistical model of changes in public opinion over time. However, these “knowns” about how to make a good presidential election forecast come with many unknowns due to the challenges of evaluating forecast calibration and communication. We highlight how incentives may shape forecasts, and particularly forecast uncertainty, in light of calibration challenges. We illustrate these…
Automating the practice of science: Opportunities, challenges, and implications
Proceedings of the National Academy of Sciences · 2025-01-27 · 26 citations
articleOpen accessAutomation transformed various aspects of our human civilization, revolutionizing industries and streamlining processes. In the domain of scientific inquiry, automated approaches emerged as powerful tools, holding promise for accelerating discovery, enhancing reproducibility, and overcoming the traditional impediments to scientific progress. This article evaluates the scope of automation within scientific practice and assesses recent approaches. Furthermore, it discusses different perspectives t…
Characterizing Photorealism and Artifacts in Diffusion Model-Generated Images
2025-04-25 · 5 citations
articleOpen access
Recent grants
NSF · $104k · 2018–2019
CHS: Small: Collaborative Research: Representing and Learning Visualization Design Knowledge
NSF · $250k · 2019–2023
NSF · $175k · 2016–2018
Frequent coauthors
- 28 shared
Matthew Kay
Northwestern University
- 20 shared
Alex Kale
- 14 shared
Priyanka Nanayakkara
- 13 shared
Yea‐Seul Kim
- 13 shared
Eytan Adar
University of Michigan–Ann Arbor
- 12 shared
Jason D. Hartline
Northwestern University
- 11 shared
Andrew Gelman
Columbia University
- 10 shared
Nicholas Diakopoulos
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