Erfan Pakdamanian
I am a Ph.D. candidate in Systems and Information Engineering, a Data Science Presidential Fellow, and a member of the Link Lab at the University of Virginia (UVA) advised by Prof. Lu Feng.
My research is focused on finding innovative ways to apply human systems engineering theories, machine learning, and big data analytics in design and analysis of complex human-in-the-loop systems. In particular, I am interested in evaluation of human computer interaction, human factors in automated vehicles, usability testing of in-vehicle technologies, and computational modeling of human behaviors.


Recent News
MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning.
Sonia Baee, Erfan Pakdamanian, Inki Kim, Lu Feng, Vicente Ordonez, Laura Barnes.
[pdf] [project page] [arXiv] [code] [BibTeX]
Recent Publications
DeepTake: Prediction of Driver Takeover Behavior using Multimodal Data.
Erfan Pakdamanian, Shili Sheng, Sonia Baee, Seongkook Heo, Sarit Kraus, Lu Feng.
Proceedings of the 2021 ACM CHI conference on human factors in computing systems. CHI 2021.
Virtual Conference. May 2021. (Acceptance Rate: 731/2844 = 25.7%)
[arXiv] [BibTeX]
Trust-Based Route Planning for Automated Vehicles.
Shili Sheng, Erfan Pakdamanian, Kyungtae Han, Ziran Wang, John Lenneman, Lu Feng.
Proceedings of the 12th ACM/IEEE International Conference on Cyber-Physical Systems. ICCPS 2021.
Virtual Conference. May 2021. (Acceptance Rate: 23.7%)
[arXiv] [BibTeX]
Formal Analysis of a Neural Network Predictor in Shared-Control Autonomous Driving.
John Grese, Corina Pasareanu, Erfan Pakdamanian.
The American Institute of Aeronautics and Astronautics Science and Technology Forum. AIAA SciTech 2021.
Virtual Conference. Jan 2021.
[pdf] [BibTeX]
Toward Minimum Startle After Take-Over Request: A Preliminary Study of Physiological Data.
Erfan Pakdamanian, Nauder Namaky, Shili Sheng, Inki Kim, James Arthur Coan, Lu Feng.
12th International ACM Conference on Automotive User Interfaces and Vehicular Applications. AutoUI 2020.
Virtual Conference. Sep 2020.
[pdf] [BibTeX]