Hello!

I am a third year Ph.D. student in Computer Science at the University of Washington under the guidance of Jeffrey Heer and Daniel Weld.

I’m motivated to make AI-backed tools work for people. How can we make technology that is quickly adaptable to novel and specific domains? How can we bridge the communication gap between researchers, developers, and domain experts? How can we support oversight of AI systems by people with limited background in the technology?

I am especially interested in exploring these questions related to environmental and data science applications.

Curriculum Vitae - Google Scholar - mgrunde at cs.washington.edu

Publications

How Do Data Analysts Respond to AI Assistance? A Wizard-of-Oz Study
Ken Gu, Madeleine Grunde-McLaughlin, Andrew M McNutt, Jeffrey Heer, Tim Althoff
ACM Conference on Human Computer Interaction, 2024
paper

Explanations can Reduce Overreliance on AI Systems during Decision-Making
Helena Vasconcelos, Matthew Jorke, Madeleine Grunde-McLaughlin, Ranjay Krishna, Tobias Gerstenberg, Michael S. Bernstein
ACM Conference on Computer-Supported Cooperative Work and Social Computing, 2023
paper

Measuring Compositional Consistency for Video Question Answering
Mona Gandhi, Mustafa Omer Gul, Eva Prakash, Madeleine Grunde-McLaughlin, Ranjay Krishna, Maneesh Agrawala
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
paper, benchmark data

AGQA: A Compositional Benchmark for Spatio-Temporal Reasoning
Madeleine Grunde-McLaughlin, Ranjay Krishna, Maneesh Agrawala
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021
paper, benchmark data, video, blog post

Bayesian-Assisted Inference from Visualized Data
Yea-Seul Kim, Paula Kayongo, Madeleine Grunde-McLaughlin, Jessica Hullman
IEEE InfoVis 2020
paper

Preprints and workshop papers

Designing LLM Chains by Adapting Techniques from Crowdsourcing Workflows
Madeleine Grunde-McLaughlin, Michelle S Lam, Ranjay Krishna, Daniel S Weld, Jeffrey Heer
ArXiv, 2023
paper

Semantic Navigator: Query Driven Active Learning for Historical Narrative Understanding
Eva Maxfield Brown, Madeleine Grunde-McLaughlin, Isabelle Pestovski, Lanyi Zhu, Nicholas Weber
ACM Conference on Computer-Supported Cooperative Work and Social Computing, Community-Driven AI Workshop, 2023
paper

When do XAI Methods Work? A Cost-Benefit Approach to Human-AI Collaboration
Helena Vasconcelos, Matthew Jorke, Madeleine Grunde-McLaughlin, Ranjay Krishna, Tobias Gerstenberg, Michael S. Bernstein
TRAIT Workshop at ACM Conference on Human Computer Interaction, 2022
paper

AGQA 2.0: An updated benchmark for compositional spatio-temporal reasoning
Madeleine Grunde-McLaughlin, Ranjay Krishna, Maneesh Agrawala
ArXiv, 2022
paper

Model Comparison of the Effects of Stimulus Structure on Visual Working Memory Recall
Madeleine Grunde-McLaughlin, Cheng Qiu, Alan Stocker
Honors Thesis in Cognitive Science
Recipient of the College Alumni Society Prize in Cognitive Science, 2021
paper