Rebecca Roelofs
Research Scientist at Google
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolRebecca Roelofs is a research scientist at Google with a Ph.D. in Computer Science from UC Berkeley and 11 years of experience focused on making machine learning more reliable. Her work centers on robustness and generalization of ML models, with contributions spanning optimization algorithms, implicit bias in deep learning, trajectory optimization with safety constraints, and distributed optimization. She has published at ICML and NeurIPS and routinely applies AWS, PyTorch, and TensorFlow to run large-scale, parallel experiments for distributed algorithms. Based in Berkeley, Rebecca pairs deep theoretical insight with practical systems engineering—evident in her ADMM-style trajectory optimizer prototype from a Google internship and her scalable use of cloud resources for research-grade evaluations.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, BerkeleyBS & BA, Engineering, Computer Science, BS & BA, Engineering, Computer Science at Swarthmore CollegeThe Charter School of Wilmington
Github Skills (26)
machine-learning10
google10
ai10
generalization10
robustness9
python8
reinforcement-learning8
datasets8
machine-translation8
gpu7
deep-learning7
matrix7
tensorflow6
numpy6
scala6
Programming languages (4)
Github contributions (5)
modestyachts/CIFAR-10.1
Jun 2018 - Apr 2020
Release of CIFAR-10.1, a new test set for CIFAR-10.
Contributions:47 commits, 29 pushes, 1 comment in 1 year 10 months
datasetcifar-10generalization
google-research/adamatch
Jul 2021 - Jan 2023
Contributions:5 commits, 3 pushes, 1 branch in 1 year 5 months
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