Gerry Chen
Senior Robotics Machine Learning Engineer at Tesla
Atlanta, Georgia, United States
Summary
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Rockstar🎓
Top SchoolGerry Chen is a Senior Robotics Machine Learning Engineer and Georgia Tech PhD candidate with eight years of hands-on experience building perception, estimation, and control systems for robots from robotaxis to humanoids. He has shipped 3D multi-object tracking and sensor fusion pipelines at Zoox, contributed VIO, mapping, and CUDA-accelerated vision work at Verdant, and now focuses on estimation and control for Tesla’s Optimus humanoid. Gerry’s background blends ME/ECE undergrad training from Duke with deep research in robotics and practical teaching experience instructing an undergraduate robotics course. He is an active contributor to foundational robotics tooling—improving GTSAM’s factor graph unit tests and Python bindings—underscoring a strong emphasis on correctness and reproducible evaluation. Colleagues describe him as equally comfortable in low-level C++/CUDA optimization and higher-level Python experimentation, with a knack for turning research prototypes into production-ready components. Based in Atlanta, he combines academic rigor with product-driven instincts to tackle real-world robotic autonomy challenges.
8 years of coding experience
1 year of employment as a software developer
B.S.E., Electrical and Computer Engineering, Mechanical Engineering, CS (minor), Math (minor), B.S.E., Electrical and Computer Engineering, Mechanical Engineering, CS (minor), Math (minor) at Duke UniversityPhD, Robotics, Computer Science, PhD, Robotics, Computer Science at Georgia Institute of TechnologyHigh School Diploma, High School Diploma at Fox Chapel Area High School
Github Skills (9)
unit-testing10
gtsam10
c-language10
cprogramming-language10
python10
testing10
computer-vision9
machine-vision9
robotics9
Programming languages (12)
Github contributions (5)
borglab/gtsam
Oct 2019 - Jan 2023
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.
Role in this project:
Back-end Developer & QA Engineer / Test Automation Engineer
Back-end Developer & QA Engineer / Test Automation EngineerContributions:174 reviews, 347 commits, 47 PRs in 3 years 4 months
Contributions summary:Gerry primarily contributed to enhancing the Gaussian Factor Graph unittests and performing linearization, with associated Python bindings. Their work focused on adding unit tests to verify the correctness of the library, including tests for marginals and joint marginals. The user's commits also involved modifications to the C++ code, particularly within the testing framework, suggesting a focus on code quality and validation through testing.
smoothingsparsec-plus-plushierarchicalpattern-recognition
gchenfc/gchenfc.github.io
Aug 2017 - Nov 2019
Contributions:84 pushes, 1 branch in 2 years 3 months
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