publications

Conferences:

[6] Pritam Sarkar, Ali Etemad, "Self-supervised Audio-Visual Representation Learning with Relaxed Temporal Synchronicity", arxiv:2111.05329, 2021.

[5] Rachel Phinnemore, Gabriele Cimolino, Pritam Sarkar, Ali Etemad, T.C. Nicholas Graham, "Happy Driver: Investigating the Effect of Mood on Preferred Style of Driving in Self-Driving Cars", International Conference on Human-Agent Interaction, (HAI), 2021. *Virtual*

[4] P. Sarkar, A. Etemad, "CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG", AAAI Conference on Artificial Intelligence, (AAAI), 2021. *Virtual*

[3] P. Sarkar, A. Etemad, "Self-supervised Learning for ECG-based Emotion Recognition", IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), 2020. *Oral (Virtual)*

[2] P. Sarkar, K. Ross, A. Ruberto, D. Rodenburg, P. Hungler, A. Etemad, "Classification of Cognitive Load and Expertise for Adaptive Simulation using Deep Multitask Learning ", IEEE Affective Computing and Intelligent Interaction, (ACII), 2019. *Oral*

[1] P. Sarkar, V. Davoodnia, A. Etemad, "Computer-Aided Diagnosis using Class-Weighted Deep Neural Networks'', IEEE International Conference on Machine Learning and Applications, (ICMLA), 2019.

Journals:

[4] P. Sarkar, S. Lobmaier, B. Fabre, G. Berg, A. Mueller, M. G. Frasch, M. C. Antonelli, A. Etemad, "Detection of Maternal and Fetal Stress from ECG with Self-supervised Representation Learning", arXiv:2011.02000, 2020.

[3] P. Sarkar, A. Etemad, "Self-supervised ECG Representation Learning for Emotion Recognition", IEEE Transactions on Affective Computing, (TAFFC), 2020.

[2] A. Ruberto, D. Rodenburg, K. Ross, P. Sarkar, P. Hungler, A. Etemad, D. Howes, D. Clarke, J. McLellan, D. Wilson, A. Szulewski, "The Future of Simulation-based Medical Education: Adaptive Simulation Utilizing a Deep Multitask Neural Network ", AEM Education and Training (AEMET), 2021.

[1] K. Ross, P. Sarkar, D. Rodenburg, A. Ruberto, P. Hungler, D. Howes, A. Szulewski, A. Etemad, "Toward Dynamically Adaptive Simulation: Multimodal Classification of User Expertise using Wearable Devices ", Sensors, 2019.

Patents:

[1] P. Sarkar, A. Etemad, “Title withheld”, US Patent Application, 63/085,394, 2020.

Workshops/Posters/Others:

[2] "Toward Wearables of the Future: Affordable Acquisition of Continuous ECG with Deep Learning", Robotics and AI Symposium at Ingunity Labs, Canada, 2021. *Best Poster Award*
[1] "A Deep Learning Approach for AR-based Adaptive Simulation using Wearables", FEAS Research Symposium at Queen's University, Canada, 2019.

Theses:

[1] "Self-supervised ECG Representation Learning for Affective Computing", Queen's University, 2020. [M.A.Sc.]