About Us
Research and Implementation Strategy
The Computational Neuroscience Core is led by Dr. Jörn Davidsen, Department of Physics and Astronomy in the Faculty of Science, and Dr. Signe Bray, Scientific Director of the Child and Adolescent Imaging Research Program, Department of Radiology in the Cumming School of Medicine. Drs. Davidsen and Bray, together with Dr. Richard Frayne (Deputy Director of the Hotchkiss Brain Institute), have engaged and mobilized over 60 scholars and leaders from at least 17 faculties, institutes, and centres across campus to develop a Computational Neuroscience research strategy. The strategy has identified three research themes – areas of strength in which we have the potential to become national leaders:
- Research Theme 1. Modeling of brain circuits (led by Dr. Wilten Nicola)
- Research Theme 2. Machine learning tools for neuroscience (led by Dr. Nils Forkert)
- Research Theme 3. Brain-computer interfaces (led by Dr. Adam Kirton)
A comprehensive research strategy and implementation plan including new hires has been developed that leverages existing partnerships and the considerable recent investments made into infrastructure and research excellence by the University of Calgary, Cumming School of Medicine, Hotchkiss Brain Institute and other partners. External partners include Campus Alberta Neuroscience, the Pacific Institute for Mathematical Sciences and AccelNet’s International network for brain-inspired computation (with nodes in Pacific Northwest incl. U Washington & Allen Institute, and Montreal, Paris)
For a full list of faculty supervisors for the Computational Neuroscience Interdisciplinary Specialization Program, please click here
Most Recent Hires
Dr. Jafar Shamsi, PhD
Dr. Shamsi is an Assistant Professor in the Department of Biomedical Engineering at the Schulich School of Engineering, with a joint appointment in Electrical and Software Engineering. He also serves as a Schulich Research Chair in Biomedical Engineering.
With a background in electrical engineering, Dr. Shamsi's work bridges neuroscience and engineering by translating insights from how the brain computes into practical, energy-efficient hardware and algorithms.
He leads the Neo Computing Lab, where his team develops ultra-low-power, brain-inspired computing systems that address the energy demands and limitations of modern AI. The lab’s research spans the full neuromorphic stack, from custom hardware to applications in biomedical wearables, assistive technologies, and edge AI devices.
Learn more about the Neo Computing Lab: https://www.neocomputinglab.ca/