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Patrick Pilarski-BW_F

Patrick M. Pilarski

Appointment

  • Canada CIFAR AI Chair
  • Pan-Canadian AI Strategy

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About

Patrick Pilarski’s research interests include reinforcement learning, real-time machine learning, human-machine interaction, rehabilitation technology, and assistive robotics. He leads the Amii Adaptive Prosthetics Program—an interdisciplinary initiative focused on creating intelligent artificial limbs to restore and extend abilities for people with amputations. As part of this research, Patrick explores new machine learning techniques for sensorimotor control and prediction, including methods for human-device interaction and communication, long-term control adaptation, and patient-specific device optimization. He has also pioneered techniques for rapid cancer and pathogen screening through work on biomedical pattern recognition, robotic micro-manipulation of medical samples, and hand-held diagnostic devices.

Awards

  • Canada Research Chair in Machine Intelligence for Rehabilitation, CRC, 2016
  • Senior Member, IEEE, 2016

Relevant Publications

  • Günther, J., Ady, N. M., Kearney, A., Dawson, M. R., & Pilarski, P. M. (2020). Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures. Frontiers in Robotics and AI, 7, 34.
  • Günther, J., Ady, N. M., Kearney, A., Dawson, M. R., & Pilarski, P. M. (2020). Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures. Frontiers in Robotics and AI, 7, 34.
  • Günther, J., Pilarski, P. M., Helfrich, G., Shen, H., & Diepold, K. (2016). Intelligent laser welding through representation, prediction, and control learning: An architecture with deep neural networks and reinforcement learning. Mechatronics, 34, 1-11.
  • Pilarski, P. M., Dawson, M. R., Degris, T., Carey, J. P., Chan, K. M., Hebert, J. S., & Sutton, R. S. (2013). Adaptive artificial limbs: A real-time approach to prediction and anticipation. IEEE Robotics & Automation Magazine, 20(1), 53-64.
  • Pilarski, P. M., Dawson, M. R., Degris, T., Fahimi, F., Carey, J. P., & Sutton, R. S. (2011, June). Online human training of a myoelectric prosthesis controller via actor-critic reinforcement learning. In 2011 IEEE international conference on rehabilitation robotics (pp. 1-7). IEEE.

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CIFAR is a registered charitable organization supported by the governments of Canada, Alberta and Quebec, as well as foundations, individuals, corporations and Canadian and international partner organizations.

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