Olivia Di Matteo
Assistant Professor at The University of British Columbia
Vancouver, British Columbia, Canada
Summary
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Rockstar🎓
Top SchoolOlivia Di Matteo is an Assistant Professor and quantum computing researcher with 11 years of experience specializing in compilation, circuits and algorithms, tomography and characterization, and quantum education. She blends academic research with practical open-source engineering—contributing backend improvements to the widely used PennyLane library by adding matrix representations, eigensystems, and fuller Pauli handling, plus updating quantum ML tutorials. Her career spans academia and industry roles at UBC, Xanadu, TRIUMF, and Microsoft, reflecting a mix of teaching, tooling, and hands-on research. Olivia’s work bridges theory and usable software, making advanced quantum techniques more accessible to researchers and students. An accomplished musician trained at the Royal Conservatory (ARCT), she brings creativity and discipline from a long history as an accompanist and organist to her technical collaborations.
11 years of coding experience
5 years of employment as a software developer
HBSc, HBSc at Lakehead UniversityARCT, ARCT at Royal Conservatory of MusicPhD, PhD at University of Waterloo
English, French, Japanese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (17)
quantum-chemistry10
lan10
develop10
python10
numpy10
automatic-differentiation10
quantum-computing10
differentiable-programming10
q-learning10
ane10
unit-testing9
optimization8
autograd8
tensorflow8
machine-learning8
Programming languages (9)
Github contributions (5)
PennyLaneAI/qml
Sep 2020 - Oct 2021
Introductions to key concepts in quantum programming, as well as tutorials and implementations from cutting-edge quantum computing research.
Role in this project:
ML Engineer
ML EngineerContributions:317 reviews, 25 commits, 55 PRs in 1 year
Contributions summary:Olivia primarily contributed to the development and refinement of tutorials and examples related to quantum machine learning within the PennyLane framework. Their work focused on modifying and updating existing tutorials, such as the variational classifier and VQE, to align with the latest PennyLane versions and incorporate new features. The user also expanded the project's glossary of key concepts, incorporating new terms and information to assist readers and developers. Their contributions demonstrate a solid understanding of quantum machine learning algorithms and PennyLane's capabilities.
automatic-differentiationtensorflowkey-conceptsqqml
PennyLaneAI/pennylane
Dec 2019 - Mar 2022
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:Back-end Developer
Back-end DeveloperContributions:711 reviews, 33 commits, 89 PRs in 2 years 2 months
Contributions summary:Olivia primarily contributed to the `pennylane` repository by implementing and enhancing quantum operations. Their work involved adding matrix representations and eigensystems to existing quantum gate classes, improving the functionality and providing a more complete description of them. Furthermore, the user added handling for single-qubit Paulis and the all-identity Pauli matrix to existing quantum operations. Their changes included code refactoring, documentation updates, and addition of tests.
pythonautomatic-differentiationdifferentiable-computingcomputerstensorflow
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