Daniel Lu
IC5 at NVIDIA
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolDaniel Lu is an experienced roboticist and IC5 software engineer based in San Jose with a decade of hands-on experience building SLAM, perception, and real-time localization systems for autonomous vehicles. He has driven high-impact projects across startups and industry leaders—architecting novel inertial-lidar 6DoF SLAM, large-scale multi-agent point-cloud mapping, and production visual-inertial odometry at companies including Ouster, Tesla, and NVIDIA. Daniel combines deep mathematical rigor (SIMD Lie-group optimizations, spline-based continuous trajectories) with practical C++14 implementations and thorough LaTeX documentation, enabling both high performance and reproducibility. He’s comfortable across sensors (lidar, cameras, IMU), calibration, and autolabelling pipelines, and has repeatedly delivered solutions that scale from research prototypes to fleet-level systems. A less obvious strength is his track record of squeezing real-time performance from complex geometry and sensor fusion problems, often outperforming standard libraries with custom, production-ready implementations.
10 years of coding experience
11 years of employment as a software developer
Bachelor's Degree Engineering Physics, Bachelor's Degree Engineering Physics at The University of British ColumbiaMaster's Degree Robotics, Master's Degree Robotics at Carnegie Mellon University
Github Skills (200)
proton10
vim10
encoding10
compression10
cpp10
robotics10
browser10
camera10
api10
computer-vision10
lichess10
volume-rendering10
odometry10
stdout10
point-cloud10
Programming languages (16)
Github contributions (5)
dllu/discord-woofbot
Jul 2016 - Jul 2017
Contributions:7 commits, 5 pushes, 1 branch in 1 year
dllu/ogdf
May 2018 - Jul 2023
OGDF is a self-contained C++ class library for the automatic layout of diagrams.
Contributions:10 pushes, 4 branches in 5 years 2 months
diagramscppself-containedclass-librarylayout
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