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email: d.szczepaniak.1@research.gla.ac.uk
Research title: Evaluating and Shaping Cognitive Training with Artificial Intelligence Agents
My work revolves around trying to improve cognitive training. Through the combination of Virtual Reality, EEG and Machine Learning I aim to create a feedback loop that will analyse the EEG and eye-tracking data and use it to modulate the training environment to increase the efficiency of the intervention.
Szczepaniak, D., Harvey, M. and Deligianni, F. (2024) ML-Driven Cognitive Workload Estimation in a VR-based Sustained Attention Task. In: 23rd IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Bellevue, WA, USA, 21-25 Oct 2024, pp. 557-560. ISBN 9798331506919 (doi: 10.1109/ISMAR-Adjunct64951.2024.00160)
Szczepaniak, D., Harvey, M. and Deligianni, F. (2024) Predictive Modelling of Cognitive Workload in VR: An Eye-Tracking Approach. In: 2024 Symposium on Eye Tracking Research and Applications (ETRA '24:), Glasgow, Scotland, 4-7 June 2024, ISBN 9798400706073 (doi: 10.1145/3649902.3655642)
Szczepaniak, D., Harvey, M. and Deligianni, F. (2024) ML-Driven Cognitive Workload Estimation in a VR-based Sustained Attention Task. In: 23rd IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Bellevue, WA, USA, 21-25 Oct 2024, pp. 557-560. ISBN 9798331506919 (doi: 10.1109/ISMAR-Adjunct64951.2024.00160)
Szczepaniak, D., Harvey, M. and Deligianni, F. (2024) Predictive Modelling of Cognitive Workload in VR: An Eye-Tracking Approach. In: 2024 Symposium on Eye Tracking Research and Applications (ETRA '24:), Glasgow, Scotland, 4-7 June 2024, ISBN 9798400706073 (doi: 10.1145/3649902.3655642)