Daniel Duckworth
Senior Research Scientist at Google DeepMind
Berlin, Germany
Summary
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Rockstar🎓
Top SchoolDaniel Duckworth is a Senior Research Scientist based in Berlin with 15 years of experience building scalable machine learning and 3D reconstruction systems at Google and DeepMind. He combines deep research instincts with production engineering—shipping NeRF and neural scene-flow training pipelines and contributing optimized rendering code to prominent repos like Google Research and jax3d. His background spans scalable ML for recommendation and language at Google, applied research in computer vision, and foundational work on Kalman filtering and scikit-learn visualizations, reflecting a rare mix of theoretical rigor and pragmatic code-quality focus. Known for improving training infrastructure and documentation as much as model performance, he often bridges dataset engineering, visualization, and high-performance rendering in the same project.
15 years of coding experience
12 years of employment as a software developer
Master of Science (MS) Artificial Intelligence, Master of Science (MS) Artificial Intelligence at University of California, BerkeleyComputer Science, Computer Science at Summer Academy in Applied Science and Technology at UPenn
Japanese, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (27)
data-visualizations10
serf10
lib10
python10
scikit10
raytracing10
machine-learning10
data-visualisation10
code-library10
glsl10
n10
kalman-filter10
tensorflow10
f10
scikit-learn10
Programming languages (10)
Github contributions (5)
pykalman/pykalman
Aug 2012 - Jul 2013
Kalman Filter, Smoother, and EM Algorithm for Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:30 commits, 5 PRs, 4 pushes in 11 months
Contributions summary:Daniel primarily worked on setting up and maintaining the codebase, as evidenced by the initial setup code and subsequent refactoring. They also contributed to the documentation structure, reorganizing the documentation files and adding class references. Further contributions involved renaming methods and library names, suggesting a focus on code quality and project maintainability.
kalman-filterpython
google-research/jax3d
Feb 2022 - Mar 2022
Role in this project:ML Engineer
ML EngineerContributions:7 commits, 3 comments, 1 issue in 1 month
Contributions summary:Daniel's commits primarily focus on the initial export and subsequent modifications of the NeSF (Neural Scene Flow) codebase within the jax3d repository. This includes adding dataset-specific files, integrating testing infrastructure, and configuring NeRF training parameters. The contributions demonstrate an involvement in setting up training pipelines, potentially for novel scene understanding, as well as enabling the use of the NeRF model within the overall system. The user also made changes to the core dataset loading, including defining a batch size field and integrating with training configurations.
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