| Systems and methods for deep reinforcement learning using a brain-artificial intelligence interface P Sajda, S Saproo, V Shih, SB Roy, D Jangraw US Patent 11,755,108, 2023 | 83 | 2023 |
| Neural mechanisms underlying catastrophic failure in human–machine interaction during aerial navigation S Saproo, V Shih, DC Jangraw, P Sajda Journal of neural engineering 13 (6), 066005, 2016 | 21 | 2016 |
| Cortically coupled computing: A new paradigm for synergistic human-machine interaction S Saproo, J Faller, V Shih, P Sajda, NR Waytowich, A Bohannon, ... Computer 49 (9), 60-68, 2016 | 21 | 2016 |
| Closed-loop regulation of user state during a boundary avoidance task J Faller, S Saproo, V Shih, P Sajda 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016 | 6 | 2016 |
| Deep reinforcement learning using neurophysiological signatures of interest V Shih, D Jangraw, S Saproo, P Sajda Proceedings of the Companion of the 2017 ACM/IEEE International Conference …, 2017 | 5 | 2017 |
| Predicting decision accuracy and certainty in complex brain-machine interactions V Shih, L Zhang, C Kothe, S Makeig, P Sajda 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016 | 4 | 2016 |
| Towards personalized human AI interaction-adapting the behavior of AI agents using neural signatures of subjective interest V Shih, DC Jangraw, P Sajda, S Saproo arXiv preprint arXiv:1709.04574, 2017 | 1 | 2017 |
| Evoked EEG signatures index cognitive workload in human-machine interaction S Saproo, D Jangraw, V Shih, P Sajda 21st Annual Meeting of the Organization for Human Brain Mapping, 2015 | | 2015 |
