Christopher Lee
Senior Robotics & AI Engineer at ROCK robotic
Dallas, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolChristopher Lee is a Senior Robotics & AI Engineer based in Dallas with a decade of software experience and over four years architecting perception and localization systems at a robotics startup. He specializes in fusing LiDAR, RGB, GNSS, and IMU data to deliver terabyte-scale LiDAR segmentation, high-fidelity 3D reconstruction (including Gaussian Splatting), and sub-centimeter localization using EKF and factor graphs. Comfortable across the stack, he optimizes low-level C++/CUDA SLAM code and ships customer-facing applications in JavaScript/Electron, while translating research ideas in computer vision into production-grade, scalable inference pipelines. His open-source contributions span deep learning on point clouds and practical tooling improvements—e.g., visualization and normalization transforms in torch-points3d—and even backend work on niche projects like Verovio. Notably, he has hands-on experience overcoming GPU memory limits for massive aerial LiDAR datasets, blending academic rigor with product delivery.
10 years of coding experience
8 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at The University of Texas at Dallas
Github Skills (17)
pytorch10
c-language10
music-notation10
image-segmentation10
imei10
deep-learning10
segmentation10
musicxml10
ei10
cprogramming-language10
point-cloud10
visualization9
python9
visualizations9
midi-instrument9
Programming languages (11)
Github contributions (5)
torch-points3d/torch-points3d
Jul 2020 - Jun 2022
Pytorch framework for doing deep learning on point clouds.
Role in this project:
ML Engineer
ML EngineerContributions:27 reviews, 130 commits, 47 PRs in 1 year 11 months
Contributions summary:Christopher contributed to the implementation of visualization features for several segmentation models (PointNet, PointNet2, and RSConv), enhancing the debugging and understanding of model behavior. They added a feature normalization transform to the data processing pipeline, including a test for its functionality, improving the data preprocessing capabilities. Additionally, they removed a dependency on a hardcoded number of classes, improving the modularity of the code.
pytorchscannetpytorch-frameworkpoint-cloudss3dis
rism-digital/verovio
Jan 2018 - Jun 2018
🎵 Music notation engraving library for MEI with MusicXML and Humdrum support and various toolkits (JavaScript, Python)
Role in this project:Back-end Developer
Back-end DeveloperContributions:17 commits, 6 PRs, 17 comments in 4 months
Contributions summary:Christopher primarily contributed to the back-end logic of the Verovio library. Their commits focused on addressing specific issues and adding functionality related to music notation rendering, particularly concerning chord and note visibility, and MIDI output. They implemented new features for automatic rest placement within beams and integrated sustain pedal functionality for MIDI generation. Further changes included refactoring code and adding parent classes for better data structure.
engravingpythonmusic-compositionpypisvg
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