Brett Koonce
CTO at Loiter.ai
Columbia, Missouri, United States
Summary
👤
Senior🎓
Top SchoolBrett Koonce is a CTO and founder with 15 years of experience building ML-first products and developer tools, currently leading Loiter.ai after co-founding Hallway and QuarkWorks. He bridges deep technical expertise in computer vision and neural networks—authoring a book on convolutional nets—with hands-on implementation experience contributing to high-profile open-source projects like tensorflow/swift-models and fastai. His background spans mobile apps and systems engineering (including early mapping tools for pilots and mobile work at Hello Network), giving him a pragmatic product sense alongside research-grade ML skills. Based in Columbia, Missouri, he pursued formal CS training after film school, bringing a creative lens to camera-centric ML products and a belief that we're still early on the AI adoption S-curve.
14 years of coding experience
16 years of employment as a software developer
University of Missouri
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (35)
dependency-management10
formula10
pytorch10
activation-function10
package-management10
image-classification10
model-driven10
machine-learning10
ruby10
mask-rcnn10
homebrew10
model-building10
deep-learning10
tensorflow10
formulas10
Programming languages (18)
Github contributions (5)
Homebrew/legacy-homebrew
Dec 2011 - Apr 2015
💀 The former home of Homebrew/homebrew (deprecated)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2056 commits in 3 years 4 months
Contributions summary:The user, Adam Vandenberg, was primarily involved in maintaining and updating formulas for various software packages within the Homebrew ecosystem. His contributions centered on updating package versions, modifying configuration files to reflect new URLs, and ensuring the correct installation of dependencies within the Homebrew environment. The user's work reflects an active role in curating and maintaining software availability for the Homebrew package manager.
macoshomebrew
tensorflow/swift-models
Mar 2019 - Feb 2021
Models and examples built with Swift for TensorFlow
Role in this project:ML Engineer
ML EngineerContributions:11 reviews, 63 commits, 82 PRs in 1 year 11 months
Contributions summary:Brett primarily contributed to the development and modification of machine learning models within the repository. Their work included refactoring and converting existing MNIST and CIFAR models to utilize new layer APIs, and they added new model implementations such as ResNet, WideResNet, MobileNetV2, MobileNetV3, and VGG16/VGG19. Furthermore, the user updated example code for the CartPole and Catch environments, reflecting changes in the TensorFlow API. The user demonstrated a strong focus on computer vision models and the integration of new features.
swifttensorflowswift-for-tensorflow
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