| 2026 | CHI | SwEYEpinch and Beyond: Exploring Intuitive, Efficient Text Entry for Extended Reality via Eye and Hand Tracking. | Ziheng 'Leo' Li, Xichen He, Mengyuan Wu, Zeyi Tong, Haowen Wei, Benjamin Yang, Steven Feiner, Paul Sajda |
| 2026 | ETRA | Gaze patterns predict preference and confidence in pairwise AI image evaluation. | Nikolas Papadopoulos, Shreenithi Navaneethan, Sheng Bai, Ankur Samanta, Paul Sajda |
| 2025 | ETRA | Using Eye Tracking and AI-Powered Experimental Design to Create Patient-Centric Clinical Studies. | Linbi Hong, Corbin Ping, Diego E. Arias, Nikolas Papadopoulos, Victoria Liu, Paul Sajda, Christopher Sege, Lisa M. McTeague |
| 2025 | ICRA | Enabling Multi-Robot Collaboration from Single-Human Guidance. | Zhengran Ji, Lingyu Zhang, Paul Sajda, Boyuan Chen |
| 2024 | ICMI | Gaze-Informed Vision Transformers: Predicting Driving Decisions Under Uncertainty. | Sharath C. Koorathota, Nikolas Papadopoulos, Jia Li Ma, Shruti Kumar, Xiaoxiao Sun, Arunesh Mittal, Patrick Adelman, Paul Sajda |
| 2023 | ACII | Capturing Interactions between Arousal and Cortical Dynamics with Simultaneous Pupillometry and EEG-fMRI. | Linbi Hong, Hengda He, Paul Sajda |
| 2023 | ACII | Reciprocal Dyadic Affective Interaction: from Facial Expressions to Brain Networks. | Ray Lee, Joshua Friedman, Paul Sajda, Nim Tottenham |
| 2022 | MICCAI | Enhancing Portable OCT Image Quality via GANs for AI-Based Eye Disease Detection. | Kaveri A. Thakoor, Ari Carter, Ge Song, Adam Wax, Omar Moussa, Royce W. S. Chen, Christine Hendon, Paul Sajda |
| 2022 | VR | Predictive Power of Pupil Dynamics in a Team Based Virtual Reality Task. | Yinuo Qin, Weijia Zhang, Richard Lee, Xiaoxiao Sun, Paul Sajda |
| 2021 | CVPR | Editing Like Humans: A Contextual, Multimodal Framework for Automated Video Editing. | Sharath C. Koorathota, Patrick Adelman, Kelly Cotton, Paul Sajda |
| 2020 | ETRA | Sequence Models in Eye Tracking: Predicting Pupil Diameter During Learning. | Sharath C. Koorathota, Kaveri A. Thakoor, Patrick Adelman, Yaoli Mao, Xueqing Liu, Paul Sajda |
| 2020 | ICRA | Accelerated Robot Learning via Human Brain Signals. | Iretiayo Akinola, Zizhao Wang, Junyao Shi, Xiaomin He, Pawan Lapborisuth, Jingxi Xu, David Watkins-Valls, Paul Sajda, Peter K. Allen |
| 2018 | CVPR | Relating Deep Neural Network Representations to EEG-fMRI Spatiotemporal Dynamics in a Perceptual Decision-Making Task. | Tao Tu, Jonathan Koss, Paul Sajda |
| 2017 | HRI | Deep Reinforcement Learning Using Neurophysiological Signatures of Interest. | Victor Shih, David C. Jangraw, Sameer Saproo, Paul Sajda |
| 2016 | SMC | Closed-loop regulation of user state during a boundary avoidance task. | Josef Faller, Sameer Saproo, Victor Shih, Paul Sajda |
| 2016 | SMC | Predicting decision accuracy and certainty in complex brain-machine interactions. | Victor Shih, Ludan Zhang, Christian Kothe, Scott Makeig, Paul Sajda |
| 2016 | SMC | Unsupervised adaptive transfer learning for Steady-State Visual Evoked Potential brain-computer interfaces. | Nicholas R. Waytowich, Josef Faller, Javier O. Garcia, Jean M. Vettel, Paul Sajda |
| 2013 | ICMI | Feature selection for gaze, pupillary, and EEG signals evoked in a 3D environment. | David C. Jangraw, Paul Sajda |
| 2006 | IJCNN | Classifying Single-Trial ERPs from Visual and Frontal Cortex during Free Viewing. | Akaysha C. Tang, Matthew T. Sutherland, Christopher J. McKinney, Jingyu Liu, Yan Wang, Lucas C. Parra, Adam D. Gerson, Paul Sajda |
| 2000 | ICIP | Hierarchical Image Probability (HIP) Models. | Clay Spence, Lucas C. Parra, Paul Sajda |
| 1995 | ICIP | A hierarchical neural network architecture that learns target context: applications to digital mammography. | Paul Sajda, Clay Spence, John C. Pearson |
| 1992 | CVPR | Object segmentation and binding within a biologically-based neural network model of depth-from-occlusion. | Paul Sajda, Leif H. Finkel |