George-cristian Muraru
Senior Research Engineer at Google DeepMind
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolGeorge-cristian Muraru is a Senior Research Engineer at Google DeepMind with 11 years of software engineering experience and an MSc in Artificial Intelligence. He combines production-grade backend engineering with research-oriented tooling, contributing to high-profile open-source privacy projects like Facebook Research’s CrypTen and OpenMined’s PySyft and SyMPC. His work spans secure multi-party computation, encrypted-tensor autograd fixes, and robust plan execution/state management—skills honed both as an OpenMined core contributor and former SMPC team lead. A longtime teaching assistant in computer science, he brings strong systems and low-level programming experience (C, x86 assembly) to research engineering problems. Colleagues describe him as pragmatic and detail-focused: he often surfaces subtle correctness checks (e.g., Beaver triple validation) that improve reliability in privacy-preserving ML stacks.
11 years of coding experience
7 years of employment as a software developer
"Dimitrie Ghika" Technical CollegePOLITEHNICA București National University for Science and Technology
English, Romanian
Github Skills (8)
pytorch10
debug10
federated-learning10
python10
cryptography10
testing9
machine-learning9
documentation7
Programming languages (13)
Github contributions (5)
OpenMined/PySyft
Oct 2019 - Nov 2022
Perform data science on data that remains in someone else's server
Role in this project:
Back-end Developer
Back-end DeveloperContributions:541 reviews, 281 commits, 273 PRs in 3 years 1 month
Contributions summary:George-cristian primarily focused on adding, modifying, and testing the core functionality of Syft's plan execution, specifically concerning registration and state management within the base workers. Their contributions centered on adding a Python context to activate or deactivate registration on the base workers, which involved changes to tests for plans and stateful plans. Additionally, they worked on re-using existing `PointerPlans` and their associated pointers. The user also contributed to the development of the SyMPC module.
pytorchcryptographyacquiringpythonscience
facebookresearch/CrypTen
Jan 2020 - Apr 2021
A framework for Privacy Preserving Machine Learning
Role in this project:Back-end Developer
Back-end DeveloperContributions:35 reviews, 9 commits, 19 PRs in 1 year 3 months
Contributions summary:George-cristian primarily contributed to bug fixes and minor feature enhancements within the CrypTen framework. Their work involved addressing typos in documentation and code comments, along with resolving issues related to the loading of encrypted tensors and autograd functionality. Furthermore, the user made changes to the MPC autograd CNN example by adding a constant size, demonstrating a focus on the framework's core functionality. They also added a check for validating Beaver triples.
privacydeep-learningprivacy-preserving-machine-learningdifferential-privacymachine-learning
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