| Deeptake: Prediction of driver takeover behavior using multimodal data E Pakdamanian, S Sheng, S Baee, S Heo, S Kraus, L Feng Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021 | 74 | 2021 |
| Medirl: Predicting the visual attention of drivers via maximum entropy deep inverse reinforcement learning S Baee, E Pakdamanian, I Kim, L Feng, V Ordonez, L Barnes Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 57* | 2021 |
| A Case Study of Trust on Autonomous Driving S Sheng, E Pakdamanian, K Han, BG Kim, P Tiwari, I Kim, L Feng 2019 IEEE Intelligent Transportation Systems(ITSC), 4368-4373, 2019 | 35 | 2019 |
| The effect of whole-body haptic feedback on driver’s perception in negotiating a curve E Pakdamanian, L Feng, I Kim Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62 (1 …, 2018 | 22 | 2018 |
| Trust-based route planning for automated vehicles S Sheng, E Pakdamanian, K Han, Z Wang, J Lenneman, L Feng Proceedings of the ACM/IEEE 12th International Conference on Cyber-Physical …, 2021 | 18 | 2021 |
| Toward minimum startle after take-over request: A preliminary study of physiological data E Pakdamanian, N Namaky, S Sheng, I Kim, JA Coan, L Feng 12th International Conference on Automotive User Interfaces and Interactive …, 2020 | 17 | 2020 |
| Enjoy the ride consciously with CAWA: Context-aware advisory warnings for automated driving E Pakdamanian, E Hu, S Sheng, S Kraus, S Heo, L Feng Proceedings of the 14th international conference on automotive user …, 2022 | 10 | 2022 |
| Planning for automated vehicles with human trust S Sheng, E Pakdamanian, K Han, Z Wang, J Lenneman, D Parker, L Feng ACM Transactions on Cyber-Physical Systems 6 (4), 1-21, 2022 | 8 | 2022 |
| A study on learning and simulating personalized car-following driving style S Sheng, E Pakdamanian, K Han, Z Wang, L Feng 2022 IEEE 25th International Conference on Intelligent Transportation …, 2022 | 4 | 2022 |
| Formal Analysis of a Neural Network Predictor in Shared-Control Autonomous Driving JM Grese, C Pasareanu, E Pakdamanian AIAA Scitech 2021 Forum, 1580, 2021 | 4 | 2021 |
| Fundamentals and emerging trends of neuroergonomic applications to driving and navigation I Kim, E Pakdamanian, V Hiremath Neuroergonomics: Principles and Practice, 389-406, 2020 | 4 | 2020 |
| Exploring gaze behavior to assess performance in digital game-based learning systems B An, I Kim, E Pakdamanian, DE Brown 2018 winter simulation conference (WSC), 2447-2458, 2018 | 4 | 2018 |
| Simulating the effect of workers' mood on the productivity of assembly lines E Pakdamanian, N Shiyamsunthar, D Claudio 2016 Winter Simulation Conference (WSC), 3440-3451, 2016 | 4 | 2016 |
| Discrete Event Simulation of Driver’s Routing Behavior Rule at a Road Intersection B Benzaman, E Pakdamanian 2019 Winter Simulation Conference (WSC), 1801-1812, 2019 | 2 | 2019 |
| Exploring the experiential impact of online propaganda using eye-gaze and pupil dilation: A comparison across three ideological groups M Heidarysafa, S Dalpe, S Kiefner, E Pakdamanian, I Kim, DE Brown, ... US Department of Justice O ce of Justice Programs, 2019 | 1 | 2019 |
| 1.2. 1 Considering human/machine interactions E Pakdamanian, S Sheng, S Baee, S Heo, S Kraus, L Feng | | 2021 |
| MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning (Supplementary Material) S Baee, E Pakdamanian, I Kim, L Feng, V Ordonez, L Barnes | | |
Lu FengAssociate Professor of Computer Science, University of VirginiaVerified email at virginia.edu
