Daniel Rasmussen
Senior Staff Machine Learning Engineer, Co-Founder at Applied Brain Research
Canada
Summary
🤩
Rockstar🎓
Top SchoolDaniel Rasmussen is a Senior Staff Machine Learning Engineer and co-founder with 18 years of experience applying deep learning and theoretical neuroscience to product-grade systems. He leads development at Applied Brain Research, bridging research and engineering to ship scalable simulation and ML tooling informed by a PhD in theoretical neuroscience from the University of Waterloo. Daniel contributes to open-source projects like Nengo, improving backend simulator operations and connection logic for large-scale brain models—work that reflects his knack for turning complex neuroscience abstractions into robust software. His background includes postdoctoral research at Princeton and teaching roles, giving him a rare mix of academic rigor, mentorship, and startup execution.
18 years of coding experience
Bachelor of Arts, Computer Science, Philosophy (Double Major), Bachelor of Arts, Computer Science, Philosophy (Double Major) at Mount Allison UniversityDoctor of Philosophy (PhD), Computer Science (Theoretical Neuroscience), Doctor of Philosophy (PhD), Computer Science (Theoretical Neuroscience) at University of Waterloo
Github Skills (8)
neural-network10
machine-learning10
ng10
python10
algorithms8
data-structures8
algorithm8
data-structure8
Programming languages (8)
Github contributions (5)
nengo/nengo
Sep 2013 - Dec 2021
A Python library for creating and simulating large-scale brain models
Role in this project:
Back-end Developer
Back-end DeveloperContributions:32 reviews, 214 commits, 126 PRs in 8 years 4 months
Contributions summary:Daniel has been working on simplifying connections within the Nengo library, a Python library for creating and simulating brain models. Their contributions involve creating new operations and refactoring connection types to improve the simulator ops. These changes included modifying existing files within the nengo directory, and appear to be focused on enhancing the backend simulation and connection logic of the library.
pythonnengoneuroscienceneural-networks
abr/lmu
Nov 2020 - Nov 2021
LMU metapackage
Contributions:2 releases, 1 review, 6 commits in 1 year
metapackagelmu
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