Shawn Thorne
Software Engineer at CoreBridge
Logan, Utah, United States
Summary
🤩
Rockstar🎓
Top SchoolShawn Thorne is a software engineer with 12 years of hands-on experience building mobile and full-stack applications, currently based in Logan, Utah and working at CoreBridge. He has a strong Android background demonstrated by contributions to TensorFlow image-classification samples and Android TV Leanback/input projects, where he optimized image preprocessing, memory usage, and UX for rich media apps. At Maiden Voyage Software he delivered more than ten web and mobile products, slashing real-estate search times from minutes to seconds through SQL and workflow optimization and integrating payment and CRM systems. Comfortable across frontend, backend, and mobile domains, he combines practical performance tuning with product-focused feature work and has a track record of shipping polished client-facing solutions. An unusual plus: his open-source contributions touch both embedded ML on-device workloads and platform-level TV services, showing breadth from low-latency processing to user experience refinements.
12 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Utah State University
Github Skills (20)
image-processing10
ui-design10
android-development10
java10
javas10
uid10
front-end-development10
android10
android-tv10
leanback10
camera-api9
user-interface9
graphical-user-interface9
tensorflow9
xml9
Programming languages (4)
Github contributions (5)
googlearchive/androidtv-Leanback
Jul 2014 - Jun 2015
:tv: Android TV Leanback Support Library sample app
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:50 commits, 9 PRs, 21 pushes in 11 months
Contributions summary:Shawn primarily worked on enhancing the Android TV Leanback sample application, adding features, and fixing bugs. They implemented global search functionality and made updates to the PlaybackOverlayFragment, including the addition of fast-forward and rewind controls. Further contributions include fixing memory issues, adding a guided step activity, and improving the overall user experience and navigation within the app. They also refactored the code for memory optimization.
androidsupport-libraryleanbackandroidtvkotlin
androidthings/sample-tensorflow-imageclassifier
Jan 2017 - Aug 2017
Classify camera images locally using TensorFlow models
Role in this project:Mobile Developer (Android)
Mobile Developer (Android)Contributions:12 commits in 6 months
Contributions summary:Shawn primarily contributed to the Android application for image classification using TensorFlow. Their work included initial setup, code refactoring, and improvements in image pre-processing and data handling. The user enhanced the performance of image processing through various code optimizations. Further commits addressed JPEG image capture and removal of permission requests.
pythonedgetpucameralocallytensorflow-models
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