Patrick M. Pilarski
Appointment
Canada CIFAR AI Chair
Pan-Canadian AI Strategy
About
Patrick Pilarski is a Canada CIFAR AI Chair and a fellow at Amii, where he also serves as a member of the Board of Directors.. He is also an associate professor in the Division of Physical Medicine and Rehabilitation, Department of Medicine and an Adjunct associate professor in the Department of Computing Science at the University of Alberta. He holds a Canada Research Chair in Machine Intelligence for Rehabilitation and is a principal investigator in the Reinforcement Learning and Artificial Intelligence Laboratory, the Bionic Limbs for Improved Natural Control Lab and the Sensory Motor Adaptive Rehabilitation Technology Network at the University of Alberta. Patrick is also a Senior Staff Research Scientist at DeepMind in Edmonton, Alberta.
Pilarski 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, he 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. Pilarski has 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.
Edwards, A.L., Dawson, M. R., Hebert, J. S., Sherstan, C., Sutton, R. S., Chan, K. M., Pilarski, P. M. (2015). « Application of Real-time Machine Learning to Myoelectric Prosthesis Control: A Case Series in Adaptive Switching », Prosthetics & Orthotics International, 40(5):573-581.
Edwards, A.L., Dawson, M. R., Hebert, J. S., Sherstan, C., Sutton, R. S., Chan, K. M., Pilarski, P. M. (2015). « Application of Real-time Machine Learning to Myoelectric Prosthesis Control: A Case Series in Adaptive Switching », Prosthetics & Orthotics International, 40(5):573-581.
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). 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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