I am a Ph.D. student at the LiNC Lab studying biologically plausible deep learning algorithms.
I am also a Data Scientist Intern at Ivado Labs. Living in Montréal, Canada.

Research Interests

I am interested in researching deep semi-supervised and unsupervised learning models and extending them to novel learning domains.

Education

Ph.D. in Computational Neuroscience, University of Toronto, Canada.
Expected completion: Summer 2020.

Hon. B.Sc. in Mathematics and Physics, University of Toronto, Canada.
Graduated June 2014.

Work Experience

Data Scientist Intern, Ivado Labs, Montréal, Canada.
November 2019 - Present.

Publications

Burst-dependent synaptic plasticity can coordinate learning in hierarchical circuits
Alexandre Payeur, Jordan Guerguiev, Friedemann Zenke, Blake Richards and Richard Naud (2020). bioRxiv. Code available here.
Spike-based causal inference for weight alignment
Jordan Guerguiev, Konrad Kording, and Blake Richards (2020). International Conference on Learning Representations (ICLR). Code available here.
Towards deep learning with segregated dendrites
Jordan Guerguiev, Timothy Lillicrap, and Blake Richards (2017). eLife, 6, e22901. Code available here.
Irrelevance by inhibition: Learning, computation, and implications for schizophrenia
Nathan Insel, Jordan Guerguiev, and Blake Richards (2018). PLOS Computational Biology, 14(8), e1006315. Code available here.