CMU Data Interaction Group

We are a research group at the Human-Computer Interaction Institute at Carnegie Mellon University. Our mission is to empower everyone to analyze and communicate data with interactive systems.

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Research Areas

Our group conducts research in computer science at the intersection of human-computer interaction, machine learning, data science, programming languages, and data management.

Visualization

Visualization leverages human perception to make (potentially large) data accessible. We are developing new languages and tools for analysis and communication.

Human-Centered Data Science

While computers can help us manage data, human judgment and domain expertise is what turns it into understanding. Meeting the challenges of increasingly large and complex data requires methods that richly integrate the capabilities of both people and machines.

Interpretable Machine Learning

Machine learning allows data scientists to summarize, aggregate, and make predictions about their data. But computers don't explain their predictions, which limits interpretability and actionable insights. We create techniques and systems that make models and their decisions understandable.

Design for Machine Learning

To create ML-based applications, we need to understand and design for everyone involved in the development process—the engineers who build the models, the designers who create the experiences, and the people who use the products.

Recent Publications

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Opening the Black Box of 3D Reconstruction Error Analysis with VECTOR Racquel Fygenson, Kazi Jawad, Zongzhan Li, Francois Ayoub, Robert G Deen, Scott Davidoff, Dominik Moritz, Mauricio Hess-Flores, VIS 2024
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Trust Junk and Evil Knobs: Calibrating Trust in AI Visualization Emily Wall, Laura Matzen, Mennatallah El-Assady, Peta Masters, Helia Hosseinpour, Alex Endert, Rita Borgo, Polo Chau, Adam Perer, Harald Schupp, Hendrik Strobelt, Lace Padilla, PacificVis 2024
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Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference Fred Hohman, Chaoqun Wang, Jinmook Lee, Jochen Görtler, Dominik Moritz, Jeffrey P Bigham, Zhile Ren, Cecile Foret, Qi Shan, Xiaoyi Zhang, CHI 2024 Best Paper Honorable Mention
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Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit Nur Yildirim, Susanna Zlotnikov, Deniz Sayar, Jeremy Kahn, Leigh Bukowski, Sher Shah Amin, Kathryn Riman, Billie Davis, John Minturn, Andrew King, Dan Ricketts, Lu Tang, Venkat Sivaraman, Adam Perer, Sarah Preum, James McCann, John Zimmerman, CHI 2024
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The Impact of Imperfect XAI on Human-AI Decision-Making Katelyn Morrison, Philipp Spitzer, Violet Turri, Michelle Feng, Niklas Kühl, Adam Perer, CSCW 2024
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