Jonathan Michaels
Assistant Professor at York University
Old Toronto, Ontario, Canada
Summary
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Senior🎓
Top SchoolJonathan Michaels is an Assistant Professor and systems neuroscientist with a decade of research experience probing how brains and machines control movement. Trained with a PhD from Georg-August-Universität Göttingen and shaped by postdoctoral fellowships at Stanford, Deutsches Primatenzentrum, and Western (Banting and BrainsCAN), he leads the Neural Control & Computation lab at York University studying neural mechanisms of motor control and computational models that bridge biology and robotics. His work blends experimental neurophysiology with computational modeling, translating fundamental insights into algorithms for artificial systems. Based in Old Toronto, he combines deep academic pedigree with collaborative, cross-disciplinary projects and a track record of securing competitive fellowships.
10 years of coding experience
Doctor of Philosophy - PhD, Systems Neuroscience, Doctor of Philosophy - PhD, Systems Neuroscience at Georg-August-Universität GöttingenBachelor of Science - BSc (Honours), PSYCHOLOGY, Bachelor of Science - BSc (Honours), PSYCHOLOGY at Queen's University
Github Skills (55)
multi-camera10
electrophysiology9
recurrent-neural-networks9
spike9
neuroscience8
drift8
baduk8
calculator8
mediapipe7
video-processing7
audio-processing7
android7
matlab7
marching-cubes7
computer-vision6
Programming languages (4)
Github contributions (5)
JonathanAMichaels/hebbRNN
May 2016 - Jul 2021
A Reward-Modulated Hebbian Learning Rule for Recurrent Neural Networks
Contributions:6 releases, 5 commits, 3 PRs in 5 years 3 months
recurrent-neural-networks
JonathanAMichaels/hfopt-matlab
Nov 2019 - Oct 2022
A parallel, cpu-based matlab implemention of the Hessian Free (HF) optimization (feed forward networks, recurrent neural networks (RNN), multiplicative recurrente neural networks (MRNN)).
Contributions:22 commits, 17 pushes in 2 years 11 months
matlabneural-networkrecurrent-neural-networks
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