Colby Banbury
ML Research Scientist at Lila Sciences
Cambridge, Massachusetts, United States
Summary
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Rockstar🎓
Top SchoolColby Banbury is an ML research scientist with a decade of experience bridging academic rigor and production-ready on-device ML, currently leading model work at Lila Sciences after a stint as a Senior Researcher at Microsoft. He completed a PhD at Harvard SEAS focused on embedded ML and edge model design and contributed to MobileNetV4 while interning at Google, giving him deep expertise in efficient neural architectures and distillation for mobile deployment. His background includes hands-on internships at Apple and Arm and practical experience shipping and optimizing vision-language models and computer-use agents. Colby is particularly skilled at translating cutting-edge research into resource-constrained deployments, often focusing on latency, quantization, and model compression trade-offs that aren’t obvious from papers alone.
10 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Harvard John A. Paulson School of Engineering and Applied SciencesBachelor’s Degree Computer Engineering, Bachelor’s Degree Computer Engineering at University of Delaware
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (59)
pytorch10
benchmark10
python10
keyword-search10
machine-learning10
power-systems10
tinyml10
arduino-library10
stem10
data-science9
javascript9
markdown9
census9
keyword-spotting9
few-shot-learning9
Programming languages (7)
Github contributions (5)
tinyMLx/arduino-library
Jan 2021 - Oct 2022
This repository holds the Arduino Library for the EdX TinyML Specialization
Contributions:14 commits, 7 PRs, 7 pushes in 1 year 8 months
stemspecializationembedded-machine-learningtinymltinyml-edx
mlcommons/tiny
Jun 2020 - Nov 2021
MLPerf™ Tiny is an ML benchmark suite for extremely low-power systems such as microcontrollers
Contributions:46 reviews, 48 commits, 99 PRs in 1 year 6 months
benchmark-suitelow-powertinymlperfmachine-learning
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