Automation in today’s world has helped human operators having several tasks accomplished in limited time. Therefore, human’s role in automated environments are shifting from operational tasks to supervisory tasks.
In complex environments, supervisory tasks become sometimes difficult to manage as the operator needs to have a clear understanding of different operational levels in the system and make decisions safely and efficiently. My work focuses on strengthening human analytical reasoning by visualizing the constraints and relationships between system parameters to them. My research expertise includes domain problem characterization through work domain analysis, visual encoding design, evaluation study design and simulation design.
I have a M.Sc. degree in Transportation Systems Engineering and Logistics from the division of communication and transport (KTS) and a Ph.D. degree in Visualization and Media Technology from the division of media and information technology (MIT) at the Institute of science and technology (ITN) in Linköping University.
Elmira Zohrevandi
Principal Research Engineer
Assistant professor in information visualization with focus on design and evaluation of visual analytics interfaces to strengthen human-automation collaboration.
Publications
2026
Design and Visualisation of Time-Series Based Explanation Mechanisms for Industrial AI Applications
International Congress and Workshop on Industrial AI and eMaintenance 2025, p. 723-735
(Conference paper)
https://dx.doi.org/10.1007/978-3-032-03725-1_51
Design of an AI-Based Decision-Support Framework to Enhance Road Safety in Varying Autonomy Conditions Using Virtual Reality
SN Computer Science, Vol. 7, Article 126
(Article in journal)
https://dx.doi.org/10.1007/s42979-025-04580-3
2025
Engaging Safety-Critical Operators in Visualization Design
2025 IEEE Conference on Engaging Critical Workforce In co-Design aNd Assessment (ECWIDNA), p. 29-33
(Conference paper)
https://dx.doi.org/10.1109/ecwidna68506.2025.00014
Towards Visual Analytics for Explainable AI in Industrial Applications
Analytics, Vol. 4, Article 7
(Article in journal)
https://dx.doi.org/10.3390/analytics4010007
Designing Explainable and Counterfactual-Based AI Interfaces for Operators in Process Industries
Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP '25): Volume 1: GRAPP, HUCAPP and IVAPP, p. 831-842
(Conference paper)
https://dx.doi.org/10.5220/0013107700003912
