Brandon Lin
Hsinchu, Taiwan Province
Summary
👤
Senior🎓
Top SchoolBrandon Lin is a software engineer with a decade of hands-on experience building performance-critical systems across graphics rendering, AI infrastructure, and query compiler design. He currently contributes to Figma’s C++/TypeScript rendering engine that compiles to WebAssembly and WebGPU, and previously built a unified SQL compiler and ML tooling at Meta. Brandon pairs strong theoretical foundations in math and CS with pragmatic engineering to drive correctness, performance, and reliability in production systems. He’s an educator and mentor—TAing graduate deep learning and algorithms courses and mentoring on Coursera—bringing clarity to complex technical topics. Outside of engineering, he channels his obsession with speed and optimization into competitive speedcubing and organizing competitions, which informs his focus on measurable performance gains.
10 years of coding experience
8 years of employment as a software developer
Master's degree, Electrical and Electronics Engineering, Master's degree, Electrical and Electronics Engineering at National Taiwan UniversityBachelor of Engineering - BE, Electrical and Electronics Engineering, Bachelor of Engineering - BE, Electrical and Electronics Engineering at National Central UniversityNano-degrees, Computer Science, Nano-degrees, Computer Science at Udacity
English, Chinese
Github Skills (5)
latex10
deep-neural-networks6
data-science6
neural-network5
keypoint1
Programming languages (2)
Github contributions (5)
Brandon-HY-Lin/coursera_How-to-Win-a-Data-Science-Competition-Learn-from-Top-Kagglers
Apr 2019 - Sep 2019
Labs and Project from the course "How to Win a Data Science Competition: Learn from Top Kagglers"
Contributions:27 commits, 18 pushes, 1 branch in 4 months
data-science
Brandon-HY-Lin/deep-reinforcement-learning
Jan 2019 - Feb 2020
Repo for the Deep Reinforcement Learning Nanodegree program
Contributions:91 pushes, 2 branches in 1 year
pytorchnanodegreedeep-learningreinforcement-learningdeep-reinforcement-learning
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