M. Ethan MacDonald
Postdoctoral Fellowship in Radiology
PhD in Biomedical Engineering
MSc in Biomedical Engineering
BEng in Electrical Engineering
Electronics Engineering Technologist Diploma
Electronics Engineering Technician Diploma
BMEN 415 - Sensor Systems and Data Analytics - Winter 2021
Preferred method of communication
Research and teaching
- Magnetic Resonance Imaging
- Big Data and Machine Learning
- Next Generation Artificial Intelligence
Magnetic Resonance Imaging
Acquisition and reconstruction of MRI data. Pulse sequence programming. Specialization in brain imaging methods including: vascular, functional magnetic resonance imaging, and diffusion tensor imaging.
Big Data and Machine Learning
Working with large databases and supercomputing resources for analytics, neuroinfomatics, brain morphology, aging physiology, and genetics. Machine learning for generative modelling and prediction. Segmentation and classification of brain tissue and diseases.
Next Generation Artificial Intelligence
Exploring new neural network architectures based on the human brain connectome. Using findings from MRI for brain simulation. Feedback and resonance in neural networks to obtain consciousness and adaptive learning.
Ethan MacDonald is an Assistant Professor in the Department of Electrical and Computer Engineering. He completed technical diplomas in electronics engineering at the Nova Scotia Community College, before doing a bachelor’s degree at Lakehead University where he obtained a first class standing. He was awarded the Dean Brawn Medal for highest ranking graduating student and the Professional Engineers of Ontario Medal for Academic Achievement. He moved to Calgary to pursue his passion of skiing, where he completed a MSc and PhD in Biomedical Engineering under the supervision of Richard Frayne, and then completed a Post-doctoral Fellowship with Bruce Pike in the department of Radiology also at the University of Calgary. Dr MacDonald was appointed as an Assistant Professor in the Department of Electrical and Computer Engineering in 2020.
MacDonald’s research has including a breadth of experiments involving the use of Magnetic Resonance Imaging (MRI), including endovascular catheter tracking, quantitative cerebrovascular imaging, imaging of brain aging physiology. Currently his research focuses on big data and machine learning for MRI applications. His research program has three core themes: Theme 1 – Image acquisition and reconstruction for MRI visualization, Theme 2 – Big Data science for biomedical application using data integration, statistics and machine learning, Theme 3 – Modeling of brain circuits to inspire the next generation of intelligent algorithms.
Applicants with backgrounds in Electrical and Computer Engineering, Biomedical Engineering, and Computer Science are a good fit with this supervisor. Applicants with other Engineering or Science Degrees can be considered. Skills in programming, image processing, machine learning, and medical imaging are considered an asset. High GPA, previous research productivity, enthusiasm and work-ethic is weighted considerably. Applications should provide a CV, transcripts, and letter describing their interests and alignment with the research program.
Our program promotes one of skill development, including: programming, writing and presentation skills. In addition to conducting cutting edge research, we aim to have highly successful trainees move into top industry and academic positions. A lab culture promoting healthy work-life balance, equity, diversity and inclusion is intended to yield an idea meritocracy to have high impact with research.