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- Laura E. Matzen
![[0000-0002-7720-2896]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-7720-2896")
Sandia National Laboratories, Albuquerque, NM, USA
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Publication search results
found 30 matches
- 2024
- Laura E. Matzen
, Breannan C. Howell, Marie Tuft, Kristin Divis:
Transparent Risks: The Impact of the Specificity and Visual Encoding of Uncertainty on Decision Making. Comput. Graph. Forum 43(3) (2024) - Emily Wall, Laura E. Matzen, Mennatallah El-Assady, Peta Masters, Helia Hosseinpour, Alex Endert, Rita Borgo, Polo Chau, Adam Perer, Harald T. Schupp, Hendrik Strobelt, Lace M. K. Padilla:
Trust Junk and Evil Knobs: Calibrating Trust in AI Visualization. PacificVis 2024: 22-31 - 2023
- Laura E. Matzen, Breannan C. Howell, Michael C. Trumbo, Kristin M. Divis:
Numerical and Visual Representations of Uncertainty Lead to Different Patterns of Decision Making. IEEE Computer Graphics and Applications 43(5): 72-82 (2023) - 2022
- Michael C. Trumbo, Aaron P. Jones, Bradley M. Robert, Derek M. Trumbo, Laura E. Matzen:
A Method of Developing Video Stimuli that Are Amenable to Neuroimaging Analysis: An EEG Pilot Study. HCI (9) 2022: 183-201 - Kristin Divis, Breannan C. Howell, Laura E. Matzen, Mallory C. Stites, Zoe N. Gastelum:
The Cognitive Effects of Machine Learning Aid in Domain-Specific and Domain-General Tasks. HICSS 2022: 1-8 - 2021
- Laura E. Matzen, Christina L. Ting, Mallory C. Stites:
Using Machine Learning to Predict Bilingual Language Proficiency from Reaction Time Priming Data. CogSci 2021 - Aaron P. Jones, Michael C. Trumbo, Laura E. Matzen, Mallory C. Stites, Breannan C. Howell, Kristin M. Divis, Zoe N. Gastelum:
Evaluating the Impact of Algorithm Confidence Ratings on Human Decision Making in Visual Search. HCI (4) 2021: 192-205 - Mark A. Livingston, Laura E. Matzen, Derek P. Brock, Andre V. Harrison, Jonathan W. Decker:
Testing the Value of Salience in Statistical Graphs. Visualization and Data Analysis 2021 - 2020
- Mark A. Livingston, Laura E. Matzen, Andre V. Harrison, Alexander Lulushi, Mikaila Daniel, Megan Dass, Derek P. Brock, Jonathan W. Decker:
A Study of Perceptual and Cognitive Models Applied to Prediction of Eye Gaze within Statistical Graphs. SAP 2020: 6:1-6:9 - Laura E. Matzen, Kristin Divis, Deborah Cronin, Michael Haass:
Task Matters When Scanning Data Visualizations. CoRR abs/2009.14465 (2020) - 2019
- Emily Wall, Meeshu Agnihotri, Laura E. Matzen, Kristin Divis, Michael Haass, Alex Endert, John T. Stasko:
A Heuristic Approach to Value-Driven Evaluation of Visualizations. IEEE Trans. Vis. Comput. Graph. 25(1): 491-500 (2019) - Laura E. Matzen, Mallory C. Stites, Heidi A. Smartt, Zoe N. Gastelum:
The Impact of Information Presentation on Visual Inspection Performance in the International Nuclear Safeguards Domain. HCI (4) 2019: 56-75 - Mallory C. Stites, Laura E. Matzen, Heidi A. Smartt, Zoe N. Gastelum:
Effects of Note-Taking Method on Knowledge Transfer in Inspection Tasks. HCI (4) 2019: 594-612 - 2018
- Laura E. Matzen, Michael J. Haass, Kristin M. Divis, Zhiyuan Wang, Andrew T. Wilson:
Data Visualization Saliency Model: A Tool for Evaluating Abstract Data Visualizations. IEEE Trans. Vis. Comput. Graph. 24(1): 563-573 (2018) - 2017
- Laura E. Matzen, Michael J. Haass, Kristin M. Divis, Mallory C. Stites:
Patterns of Attention: How Data Visualizations Are Read. HCI (14) 2017: 176-191 - 2016
- Laura A. McNamara, Travis L. Bauer, Michael J. Haass, Laura E. Matzen:
Information Theoretic Measures for Visual Analytics: The Silver Ticket? BELIV 2016: 53-61 - Michael J. Haass, Laura E. Matzen, Karin M. Butler, Mika Armenta:
A new method for categorizing scanpaths from eye tracking data. ETRA 2016: 35-38 - Michael J. Haass, Andrew T. Wilson, Laura E. Matzen, Kristin M. Divis:
Modeling Human Comprehension of Data Visualizations. HCI (10) 2016: 125-134 - Susan M. Stevens-Adams, Michael J. Haass, Laura E. Matzen, Saskia King:
Assessment of Expert Interaction with Multivariate Time Series 'Big Data'. HCI (14) 2016: 222-230 - Laura E. Matzen, Michael J. Haass, Jonathan Tran, Laura A. McNamara:
Using Eye Tracking Metrics and Visual Saliency Maps to Assess Image Utility. HVEI 2016: 1-8 - 2015
- Michael J. Haass, Laura E. Matzen, Susan M. Stevens-Adams, Allen R. Roach:
Methodology for Knowledge Elicitation in Visual Abductive Reasoning Tasks. HCI (15) 2015: 401-409 - Laura E. Matzen, Michael J. Haass, Laura A. McNamara, Susan M. Stevens-Adams, Stephanie N. McMichael:
Effects of Professional Visual Search Experience on Domain-General and Domain-Specific Visual Cognition. HCI (15) 2015: 481-491 - Laura A. McNamara, Kerstan S. Cole, Michael J. Haass, Laura E. Matzen, J. Daniel Morrow, Susan M. Stevens-Adams, Stephanie N. McMichael:
Ethnographic Methods for Experimental Design: Case Studies in Visual Search. HCI (15) 2015: 492-503 - Austin Silva, Glory Emmanuel, Jonathan T. McClain, Laura E. Matzen, J. Chris Forsythe:
Measuring Expert and Novice Performance Within Computer Security Incident Response Teams. HCI (15) 2015: 144-152 - Michael C. Trumbo, Laura E. Matzen, Austin Silva, Michael J. Haass, Kristin Divis, Ann E. Speed:
Through a Scanner Quickly: Elicitation of P3 in Transportation Security Officers Following Rapid Image Presentation and Categorization. HCI (15) 2015: 348-360 - 2011
- Erik W. Anderson, Kristin C. Potter, Laura E. Matzen, Jason F. Shepherd, Gilbert Preston, Cláudio T. Silva:
A User Study of Visualization Effectiveness Using EEG and Cognitive Load. Comput. Graph. Forum 30(3): 791-800 (2011) - Alisa Bandlow, Laura E. Matzen, Kerstan S. Cole, Courtney C. Dornburg, Charles J. Gieseler, John A. Greenfield, Laura A. McNamara, Susan M. Stevens-Adams:
Evaluating Information Visualizations with Working Memory Metrics. HCI (22) 2011: 265-269 - Michael J. Haass, Laura E. Matzen:
Using Computational Modeling to Assess Use of Cognitive Strategies. HCI (20) 2011: 77-86 - Laura E. Matzen:
Cultural Neuroscience and Individual Differences: Implications for Augmented Cognition. HCI (20) 2011: 194-198 - 2009
- Courtney C. Dornburg, Laura E. Matzen, Travis L. Bauer, Laura A. McNamara:
Working memory load as a novel tool for evaluating visual analytics. IEEE VAST 2009: 217-218
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