Sheng-dean Chang
Cylon at Battlestar Galatica
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolSheng-dean Chang is a seasoned software engineer with 11 years of experience building scalable mobile and backend systems, having held engineering roles at LinkedIn and Uber before his current position at Battlestar Galatica. He combines a strong academic foundation—a Master of Mathematics in Computer Science from University of Waterloo—with practical expertise in Android platform work and production-grade backend development. Sheng-dean is also an active open-source contributor to GoCV, where he added critical OpenCV bindings and unit tests for contour analysis and template matching, bridging C++ vision functionality into Go. Known for shipping reliable, well-tested code, he’s comfortable working across language and platform boundaries, from mobile clients to computer vision libraries. Based in Old Toronto, he brings a pragmatic, research-informed approach to engineering problems and an appetite for applying vision and systems work in production.
11 years of coding experience
7 years of employment as a software developer
Bachelor of Science, Information & Finance Management - Information Management Group, Bachelor of Science, Information & Finance Management - Information Management Group at National Chiao Tung UniversityMaster of Mathematics, Computer Science, Master of Mathematics, Computer Science at University of Waterloo
Github Skills (8)
golang10
computer-vision10
opencv10
c-language10
go10
cprogramming-language10
image-processing9
unit-testing9
Programming languages (9)
Github contributions (5)
hybridgroup/gocv
Feb 2018 - Feb 2018
Go package for computer vision using OpenCV 4 and beyond. Includes support for DNN, CUDA, OpenCV Contrib, and OpenVINO.
Role in this project:
Backend Developer
Backend DeveloperContributions:6 commits, 3 PRs, 7 comments in 12 days
Contributions summary:Sheng-dean primarily contributed to adding and modifying functionalities related to image processing within the GoCV project, specifically focusing on computer vision tasks. They implemented bindings for OpenCV functions such as `matchTemplate`, `arcLength`, and `approxPolyDP`. These changes involved adding Go wrappers for C++ functions and writing corresponding unit tests to validate the newly added features. This work directly enhances the GoCV library's capabilities in contour analysis and template matching.
face-trackingvideotensorflowcomputervisiondnn
littledot/Permission-Nanny
Oct 2015 - Jan 2017
Contributions:1 release, 82 commits, 4 PRs in 1 year 3 months
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