Research

Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts

P. Sarkar, A. Beirami, A. Etemad

Neural Information Processing Systems, (NeurIPS), 2023. Spotlight

[paper] [code] [website]

XKD: Cross-modal Knowledge Distillation with Domain Alignment for Video Representation Learning

P. Sarkar, A. Etemad

AAAI Conference on Artificial Intelligence, (AAAI), 2024.

[paper] [code] [website]

Region-Disentangled Diffusion Model for High-Fidelity PPG-to-ECG Translation

D. Shome, P. Sarkar, A. Etemad

AAAI Conference on Artificial Intelligence, (AAAI), 2024.

[paper]

Self-supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Synchronicity

P. Sarkar, A. Etemad

AAAI Conference on Artificial Intelligence, (AAAI), 2023. Oral

[paper] [code] [website]

AVCAffe: A Large Scale Audio-Visual Dataset of Cognitive Load and Affect for Remote Work

P. Sarkar, A. Posen, A. Etemad

AAAI Conference on Artificial Intelligence, (AAAI), 2023.

[paper] [code] [website]

CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG

P. Sarkar, A. Etemad

AAAI Conference on Artificial Intelligence, (AAAI), 2021.

[paper] [code] [video]

Happy Driver: Investigating the Effect of Mood on Preferred Style of Driving in Self-Driving Cars

R. Phinnemore, G. Cimolino, P. Sarkar, A. Etemad, T.C. Nicholas Graham

International Conference on Human-Agent Interaction, (HAI), 2021.

[paper] [short video] [long video]

Detection of Maternal and Fetal Stress from ECG with Self-supervised Representation Learning

P. Sarkar*, S. Lobmaier*, B. Fabre, G. Berg, A. Mueller, M. G. Frasch, M. C. Antonelli, A. Etemad

Nature Scientific Reports, 2021.

[paper] [code]

Self-supervised ECG Representation Learning for Emotion Recognition

P. Sarkar, A. Etemad

IEEE Transactions on Affective Computing, (TAFFC), 2020.

[paper] [code]

Self-supervised Learning for ECG-based Emotion Recognition

P. Sarkar, A. Etemad

IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), 2020. Oral

[paper] [code]

The Future of Simulation-based Medical Education: Adaptive Simulation Utilizing a Deep Multitask Neural Network

A. Ruberto, D. Rodenburg, K. Ross, P. Sarkar, P. Hungler, A. Etemad, D. Howes, D. Clarke, J. McLellan, D. Wilson, A. Szulewski

AEM Education and Training (AEMET), 2021.

[paper]

Classification of Cognitive Load and Expertise for Adaptive Simulation using Deep Multitask Learning

P. Sarkar, K. Ross, A. Ruberto, D. Rodenburg, P. Hungler, A. Etemad

IEEE Affective Computing and Intelligent Interaction, (ACII), 2019. Oral

[paper]

Toward Dynamically Adaptive Simulation: Multimodal Classification of User Expertise using Wearable Devices

K. Ross, P. Sarkar, D. Rodenburg, A. Ruberto, P. Hungler, D. Howes, A. Szulewski, A. Etemad

Sensors, 2019

[paper]

Computer-Aided Diagnosis using Class-Weighted Deep Neural Networks

P. Sarkar, V. Davoodnia, A. Etemad

IEEE International Conference on Machine Learning and Applications, (ICMLA), 2019.

[paper]