Sebastian Goodfellow is a Senior Research Associate at Laussen Labs. He obtained a Ph.D. in Geophysics, with a specialization in Seismology, from the University of Toronto. Sebastian also holds Master’s and Bachelor’s degrees in Aerospace Engineering and Mechanical Engineering respectively. At Laussen Labs, Sebastian focuses on applying signal processing, machine learning, and deep learning technologies to continuous, real-time, multidimensional, physiological data to make meaningful predictions and classifications.
In his spare time, Sebastian enjoys traveling the world including such destinations as Namibia, Morocco, South Africa, and Turkey. Sebastian is John Lennon is a Beatles cover band, enjoys surfing the Great Lakes and enjoys the history of the ancient Near East.
Keywords/Tags: artificial intelligence, deep learning, machine learning, time series analysis
- Goodfellow, S. D., A. Goodwin, R. Greer, P. C. Laussen, M. Mazwi, and D. Eytan (2018), Atrial fibrillation classification using step-by-step machine learning, Biomed. Phys. Eng. Express, 4, 045005. DOI: 10.1088/2057-1976/aabef4
- Goodfellow, S. D., A. Goodwin, R. Greer, P. C. Laussen, M. Mazwi, and D. Eytan, Towards understanding ECG rhythm classification using convolutional neural networks and attention mappings, Proceedings of Machine Learning for Healthcare 2018 JMLR W&C Track Volume 85, Aug 17–18, 2018, Stanford, California, USA.
- Goodfellow, S. D., A. Goodwin, R. Greer, P. C. Laussen, M. Mazwi, and D. Eytan, Classification of atrial fibrillation using multidisciplinary features and gradient boosting, Computing in Cardiology, Sept 24–27, 2017, Rennes, France.
Location: Toronto, Canada