Hi!

I am a fourth year Ph.D. student in the intersection of HCI and AI at the University of Washington. I am advised by Jeffrey Heer and Daniel Weld, and I collaborate closely with Ranjay Krishna.

My work centers on using AI for data-driven discovery while incorporating rather than replacing human judgement. I am motivated to explore questions such as: How can validation and user guidance be built into AI-backed tools? How can AI chaining architectures support meaningful user interactions? How can these tools support scientists and data analysts in discovering robust and reproducible findings?

I am especially interested in exploring these questions for environmental 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
pdf

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
Best paper honorable mention awarded to the top 23 papers
pdf

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
pdf, 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
pdf, benchmark data, video, blog post

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

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
pdf

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
pdf

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
pdf

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

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
pdf