Chris Beall
Head Of Online Mapping at Nuro
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolChris Beall is a seasoned mapping and localization leader with 16 years of experience translating academic rigor into production-grade autonomy software. Currently Head of Online Mapping at Nuro in Mountain View, he progressed through hands-on engineering and technical leadership roles focused on localization, pose estimation, and scalable map pipelines. His background includes a PhD in Computer Engineering and research-to-product stints at Fyusion and Intel, reflecting deep expertise in perception and SLAM. Chris contributes to core algorithmic work in open-source robotics tooling—most notably on GTSAM—indicating comfort with factor-graph based smoothing and mathematically driven refactors. He combines people leadership with low-level C++ and algorithm development, routinely bridging research proofs-of-concept to dependable fleet systems. Colleagues describe him as a pragmatic engineer who surfaces subtle algorithmic improvements that yield outsized production stability.
16 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Computer Engineering, Doctor of Philosophy (Ph.D.) Computer Engineering at Georgia Institute of TechnologyMaster of Science (MS) Computer Engineering, Master of Science (MS) Computer Engineering at University of Tennessee, Knoxville
Github Skills (13)
algorithm10
algorithms10
c-language10
cprogramming-language10
slam10
linear-algebra10
template-metaprogramming9
factors9
graph9
computer-vision8
machine-vision8
mappings8
bayesian-network8
Programming languages (2)
Github contributions (4)
borglab/gtsam
Jul 2016 - Aug 2020
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 & Algorithm Engineer
Back-end Developer & Algorithm EngineerContributions:65 commits, 20 PRs, 28 pushes in 4 years 1 month
Contributions summary:Chris appears to have been working on implementing and improving core algorithms for smoothing and mapping within the GTSAM library. Their commits reveal significant changes to the VSLAMFactor and other underlying components, indicating they are likely involved in the core mathematical and algorithmic aspects of the library. Their focus seems to be on implementing features related to templates and refactoring existing codebase.
smoothingsparsec-plus-plushierarchicalpattern-recognition
chrisbeall/gtsam
May 2019 - May 2019
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.
Contributions:4 pushes, 10 branches in 7 days
smoothingsparsec-plus-plusgtsamrobotics
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