Shyamal Dharia
I am a Senior Researcher at The University of Winnipeg, working under the supervision of Dr. Camilo Valderrama, Dr. Qian Liu, and Dr. Stephen D. Smith. My research focuses on machine learning–driven approaches for healthcare and neuroimaging applications.
I completed my MSc in Applied Computer Science at the University of Winnipeg. Prior to this, I earned a B.Eng. in Electronics and Communication Engineering from Gujarat Technological University.
My research interests include machine learning, deep learning, and computer vision, with an emphasis on developing interpretable and data-efficient models for healthcare and biomedical signal analysis.
Publications
Dharia, S. Y., Liu, Q., Smith, S. D., Valderrama Cuadros, C. E., “A Novel Approach for the Early Identification of Genetic Risk Factors for Alzheimer's Disease Using EEG and Psychometric Data,” IEEE Journal of Biomedical and Health Informatics, 2025. DOI: https://doi.org/10.1109/JBHI.2025.3639217
Dharia, S. Y., Valderrama Cuadros, C. E., Liu, Q., Fredborg, B. K., Desroches, A. S., Smith, S. D., “Fractal Dimension of Resting-State EEG as a Biomarker for Autonomous Sensory Meridian Response (ASMR),” IEEE Journal of Biomedical and Health Informatics, vol. 29, no. 12, pp. 8751–8758, Dec. 2025. DOI: https://doi.org/10.1109/JBHI.2025.3612301
Bipartite Graph Adversarial Network for Subject-Independent Emotion Recognition
Niaki, M., Dharia, S. Y., Chen, Y., Valderrama Cuadros, C. E., “Bipartite Graph Adversarial Network for Subject-Independent Emotion Recognition,” IEEE Journal of Biomedical and Health Informatics, vol. 29, no. 10, pp. 7234–7247, Oct. 2025. DOI: https://doi.org/10.1109/JBHI.2025.3570187
Dharia, S. Y., Liu, Q., Smith, S. D., Valderrama Cuadros, C. E., “Dual-Transformer Cross-Attention Framework for Alzheimer's Disease Detection Via dPTE-Guided EEG Channel Selection and Multi-Modal Integration,” Biomedical Signal Processing and Control, 2025. DOI: https://doi.org/10.1016/j.bspc.2025.108390
Dharia, S. Y., Hojjati, M., Camorlinga, S. G., Smith, S. D., Desroches, A. S., “Leveraging Machine Learning and Threshold-Free Cluster Enhancement to Unravel Perception of Emotion and Implied Movement,” Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), Houston, TX, USA, 2024, pp. 1–8. DOI: https://doi.org/10.1109/BHI62660.2024.10913664
Dataset-Independent EEG Channel Selection for Emotion Recognition
Dharia, S. Y., Camorlinga, S. G., Valderrama Cuadros, C. E., Hojjati, M., “Dataset-Independent EEG Channel Selection for Emotion Recognition,” Proceedings of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA, 2024, pp. 1–4. DOI: https://doi.org/10.1109/EMBC53108.2024.10782444
Multimodal Deep Learning Model for Subject-Independent EEG-based Emotion Recognition
Dharia, S. Y., Valderrama Cuadros, C. E., Camorlinga, S. G., “Multimodal Deep Learning Model for Subject-Independent EEG-based Emotion Recognition,” Proceedings of the IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), Regina, SK, Canada, 2023, pp. 105–110. DOI: https://doi.org/10.1109/CCECE58730.2023.10289007