Gavia Gray
Senior Member Of Technical Staff at Cerebras Systems
Old Toronto, Ontario, Canada
Summary
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Senior🎓
Top SchoolGavia Gray is a Senior Member of Technical Staff at Cerebras Systems with 13 years of experience bridging research and production in ML, computer vision, and neuroinformatics. With a PhD from the University of Edinburgh and postdoctoral work at the Vector Institute and University of Toronto, she combines deep academic rigor with hands-on engineering at scale. Her recent contributions include practical model and config engineering on ROMP, a notable monocular multi-person 3D pose and trajectory project, reflecting expertise in model training, precision management, and reproducible experiment infrastructure. At Cerebras she progressed rapidly from Research Scientist to senior staff, demonstrating an ability to translate cutting-edge research into deployable systems. Based in Old Toronto, she brings a rare blend of neuroscience-informed ML insight and production-focused software craftsmanship. Colleagues can expect a thoughtful engineer who balances principled research methods with pragmatic code and configuration work.
13 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Neuroinformatics, Doctor of Philosophy - PhD Neuroinformatics at The University of Edinburgh
Stackoverflow
484reputation
75kreached
14answers
0questions
Github Skills (11)
configuration-management10
pytorch10
machine-learning10
python10
einops6
neural-network6
deep-learning6
maxpooling6
tensorflow6
loss6
hyperparameters6
Programming languages (7)
Github contributions (5)
Arthur151/ROMP
Jul 2021 - Jul 2021
Monocular, One-stage, Regression of Multiple 3D People and their 3D positions & trajectories in camera & global coordinates. ROMP[ICCV21], BEV[CVPR22], TRACE[CVPR2023]
Role in this project:
ML Engineer
ML EngineerContributions:9 commits, 1 PR in 1 day
Contributions summary:Gavia primarily focused on modifying configuration files and core code related to the ROMP model. They addressed argument parsing, refactoring the configuration management system, and ensuring proper loading of configuration variables. The commits also included adjustments to model precision and file paths, indicating involvement in training and potentially inference processes within the project.
pytorchregressionpose-estimationcomputer-vision3d-reconstruction
BayesWatch/sequential-imagenet-dataloader
Nov 2017 - Aug 2021
Contributions:27 commits, 10 pushes, 7 comments in 3 years 9 months
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