Guillermo Alonso-linaje
Quantum Scientist - Compilation
Spain
Summary
🤩
Rockstar🎓
Top SchoolGuillermo Alonso-linaje is a Quantum Scientist specializing in compilation and quantum machine learning with six years of experience bridging research, education, and production software. Based at Xanadu, he has progressed from educator and researcher to software and now compilation-focused roles, contributing to core features and rigorous tests in the widely used PennyLane library (including batching, multi-amplitude embeddings, and QFT/adjoint fixes). He teaches and creates outreach—running the Ket.G YouTube project—and has four-plus years of formal teaching experience in quantum computing. Trained in mathematics and computer science, he combines theoretical rigor with practical engineering to ship reliable quantum software. Colleagues value his ability to surface subtle bugs in quantum transformations and to turn research concepts into clear tutorials and robust code.
6 years of coding experience
4 years of employment as a software developer
Master's degree, Mathematics and Computer Science, Master's degree, Mathematics and Computer Science at UNIR | Universidad Internacional de La RiojaMatemáticas e Informática, Mathematics and Computer Science, Matemáticas e Informática, Mathematics and Computer Science at Universidad de Valladolid
Github Skills (19)
pytorch10
learn-ruby-on-rails10
python10
user-manual10
basics10
automatic-differentiation10
tensorflow10
qml10
quantum-computing10
q-learning10
documentation10
unit-testing9
pytest9
unit-test9
differentiable-programming8
Programming languages (4)
Github contributions (5)
PennyLaneAI/qml
Aug 2022 - Jan 2023
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
Role in this project:
Technical Writer & Contributor
Technical Writer & ContributorContributions:566 reviews, 71 commits, 338 PRs in 5 months
Contributions summary:Guillermo contributed significantly to the documentation and tutorial sections of the repository, specifically focusing on quantum machine learning concepts and demonstrations. Their work includes adding and updating tutorials on quantum algorithms like classical shadows and QFT, as well as adding image assets and metadata. These contributions improve the educational resources and usability of the PennyLane QML library. The user also addressed typos and minor rendering issues.
automatic-differentiationtensorflowkey-conceptsqqml
PennyLaneAI/pennylane
Nov 2021 - Jan 2023
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
Role in this project:ML Engineer
ML EngineerContributions:458 reviews, 25 commits, 106 PRs in 1 year 2 months
Contributions summary:Guillermo contributed significantly to the PennyLane quantum computing library, focusing on the implementation and testing of new features. They worked on batching techniques for operations like `AngleEmbedding`, developing corresponding tests and addressing related errors. Furthermore, the user developed a `Barrier` operation, implemented multi-amplitude embedding with transformations, and addressed issues related to QFT and adjoint methods within the library. Their work involved modifying multiple core files and implementing unit tests, showing a deep understanding of the codebase.
pythonautomatic-differentiationdifferentiable-computingcomputerstensorflow
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