RML at ICASSP 2026: PC-SSL for EEG Emotion Recognition
Niki Sheibani and Dr. Khan present PC-SSL at ICASSP 2026 — a predictive coding self-supervised learning framework for EEG-based emotion recognition, achieving state-of-the-art …
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PC-SSL: A Predictive Coding-Based Self-Supervised Learning Framework for EEG Emotion Recognition
We introduce a predictive coding self-supervised learning (PC-SSL) approach to overcome the limitations of traditional supervised methods hindered by the high cost of labeling EEG …
niki-sheibani
Stress Classification From ECG Signals Using Vision Transformer
Vision transformers have shown tremendous success in numerous computer vision applications; however, they have not been exploited for stress assessment using physiological signals …
zeeshan-ahmad
Enhanced Cross-Dataset Electroencephalogram-Based Emotion Recognition Using Unsupervised Domain Adaptation
We propose an enhanced unsupervised domain adaptation framework for EEG-based emotion recognition that achieves robust cross-dataset generalization without requiring target-domain …
Md Niaz Imtiaz
RML at IEEE EMBC 2024
RML presents three papers at the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
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Multilevel Stress Assessment from ECG in a Virtual Reality Environment Using Multimodal Fusion
We propose a multilevel stress assessment framework that fuses ECG signals with contextual data from a virtual reality environment. The system classifies multiple levels of …
zeeshan-ahmad
Multimodal Affective Computing
Emotion Recognition and Stress Assessment using Multimodal Signals for therapy and training
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NSERC Alliance Grant: Therapeutic VR Games for Children
Dr. Khan receives $400K NSERC Alliance grant with Wellwave Inc. to develop therapeutic VR games with multimodal stress assessment for children.
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RML at IEEE EMBC 2020
RML members present two papers on multimodal physiological stress assessment at the 42nd Annual IEEE Engineering in Medicine and Biology Conference.
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NSERC CRD Award: Cloud-based Stress and Engagement Assessment in VR
Dr. Khan, Dr. Guan, and Dr. Krishnan receive $450K NSERC CRD grant with Shaftesbury for multimodal stress and engagement assessment in virtual reality.
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