Jeffrey Heer

About

Jeffrey Michael Heer is the Jerre D. Noe Endowed Professor of Computer Science & Engineering at the University of Washington. He leads the UW Interactive Data Lab and is deeply engaged in teaching data visualization courses, including CSE442 and CSE512. Professor Heer values working with talented and engaging students, mentoring a diverse group of PhD students, post-doctoral scholars, masters, and undergraduate students in areas related to data visualization, interactive machine learning, statistical analysis, and computational visualization interpretation. His research interests encompass authoring interactive documents, visual debugging tools, visualization perception, models and automated design, interactive machine learning, error analysis, and languages and tools for interactive visualization. Through his mentorship, many of his former students and post-doctoral scholars have gone on to prominent roles in academia and industry, contributing to fields such as scalable interactive visualization, uncertainty visualization, genomic data analysis, and visualization recommendation systems.

Research topics

• Computer Science
• Software engineering
• Epistemology
• Natural Language Processing
• Artificial Intelligence
• Data science
• Programming language
• Econometrics
• Mathematics
• Psychology

Selected publications

• Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models

  2021 · 149 citations

  Tongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, Daniel Weld. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.

  DOI

• Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

  Organizational Behavior and Human Decision Processes · 2021 · 133 citations

  In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency…

  PublisherDOI

• Boba: Authoring and Visualizing Multiverse Analyses

  IEEE Transactions on Visualization and Computer Graphics · 2020 · 79 citations

  Senior authorCorresponding

  Multiverse analysis is an approach to data analysis in which all "reasonable" analytic decisions are evaluated in parallel and interpreted collectively, in order to foster robustness and transparency. However, specifying a multiverse is demanding because analysts must manage myriad variants from a cross-product of analytic decisions, and the results require nuanced interpretation. We contribute Baba: an integrated domain-specific language (DSL) and visual analysis system for authoring and review…

  PublisherOA PDFDOI

• Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships

  CHI Conference on Human Factors in Computing Systems · 2022 · 22 citations

  Proper statistical modeling incorporates domain theory about how concepts relate and details of how data were measured. However, data analysts currently lack tool support for recording and reasoning about domain assumptions, data collection, and modeling choices in an integrated manner, leading to mistakes that can compromise scientific validity. For instance, generalized linear mixed-effects models (GLMMs) help answer complex research questions, but omitting random effects impairs the generaliz…

  DOI

• From Pen to Prompt: How Creative Writers Integrate AI into their Writing Practice

  2025-06-22 · 21 citations

  preprintOpen access

  Creative writing is a deeply human craft, yet AI systems using large language models (LLMs) offer the automation of significant parts of the writing process.So why do some creative writers choose to use AI? Through interviews and observed writing sessions with 18 creative writers who already use AI regularly in their writing practice, we find that creative writers are intentional about how they incorporate AI, making many deliberate decisions about when and how to engage AI based on their core v…

  PublisherOA PDFDOI

Recent grants

• III: Medium: Collaborative Research: Composing Interactive Data Visualizations

  NSF · $240k · 2016–2020

• HCC: Small: Graphical Perception Revisited: Developing and Validating Design Guidelines for Data Visualization

  NSF · $250k · 2010–2013

• III: Large: Collaborative Research: Analysis Engineering for Robust End-to-End Data Science

  NSF · $1.6M · 2019–2026

Frequent coauthors

• Dominik Moritz

  Carnegie Mellon University

  25 shared

• Arvind Satyanarayan

  Vassar College

  19 shared

• Maneesh Agrawala

  16 shared

• Christopher D. Manning

  15 shared

• Kanit Wongsuphasawat

  15 shared

• Joseph M. Hellerstein

  University of California, Berkeley

  15 shared

• Tim Althoff

  12 shared

• Diana MacLean

  11 shared

Labs

• Jeffrey Heer LabPI

Education

• B.S.

  UC Berkeley

• M.S.

  UC Berkeley

• Ph.D.

  UC Berkeley

Awards & honors

• MIT Technology Review's TR35 (2009)
• Sloan Fellowship (2012)
• ACM Grace Murray Hopper Award (2016)
• IEEE Visualization Technical Achievement Award (2017)
• induction into the IEEE Visualization (2019)

Similar researchers at University of Washington

• Dieter Foxh-107
• Ali Farhadih-91
• Hannaneh Hajishirzih-75