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Matthias D. Ziegler
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Conference and Workshop Papers
- 2021
- [c9]Yanqiu Tian, Alexander G. Minton, Howe Yuan Zhu, Gina Notaro, Raquel Galvan-Garza, Yu-Kai Wang, Hsiang-Ting Chen, James Allen, Matthias D. Ziegler, Chin-Teng Lin:
A Comparison of Common Video Game versus Real-World Heads-Up-Display Designs for the Purpose of Target Localization and Identification. ISMAR Adjunct 2021: 228-233 - 2019
- [c8]Jesse Mark, Adrian Curtin, Amanda E. Kraft, Trevor M. Sands, William D. Casebeer, Matthias D. Ziegler, Hasan Ayaz:
Eye Tracking-Based Workload and Performance Assessment for Skill Acquisition. AHFE (2) 2019: 129-141 - [c7]Hasan Ayaz, Adrian Curtin, Jesse Mark, Amanda E. Kraft, Matthias D. Ziegler:
Predicting Future Performance based on Current Brain Activity: An fNIRS and EEG Study. SMC 2019: 3925-3930 - 2018
- [c6]William D. Casebeer, Matthias D. Ziegler, Amanda E. Kraft, Jason Poleski, Bartlett A. H. Russell:
Human Performance Augmentation in Context: Using Artificial Intelligence to Deal with Variability - An Example from Narrative Influence. HCI (16) 2018: 32-42 - [c5]Alison M. Perez, Amanda E. Kraft, Raquel Galvan-Garza, Matthew Pava, Amanda Barkan, William D. Casebeer, Matthias D. Ziegler:
A Multi-sensor Approach to Linking Behavior to Job Performance. HCI (15) 2018: 59-68 - 2017
- [c4]Jesse Mark, Neha Thomas, Amanda E. Kraft, William D. Casebeer, Matthias D. Ziegler, Hasan Ayaz:
Neurofeedback for Personalized Adaptive Training. AHFE (2) 2017: 83-94 - [c3]Amanda E. Kraft, Jon Carmelo Russo, Michael Krein, Bartlett A. H. Russell, William D. Casebeer, Matthias D. Ziegler:
A systematic approach to developing near real-time performance predictions based on physiological measures. CogSIMA 2017: 1-7 - 2016
- [c2]Matthias D. Ziegler, Amanda E. Kraft, Michael Krein, Li-Chuan Lo, Bradley D. Hatfield, William D. Casebeer, Bartlett A. H. Russell:
Sensing and Assessing Cognitive Workload Across Multiple Tasks. HCI (13) 2016: 440-450 - 2014
- [c1]Suhas E. Chelian, Matthias D. Ziegler, Peter Pirolli, Rajan Bhattacharyya:
Learning to Prognostically Forage in a Neural Network Model of the Interactions between Neuromodulators and Prefrontal Cortex. BICA 2014: 32-39
Coauthor Index
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