Aroosa Ijaz
QML Graduate Researcher
Old Toronto, Ontario, Canada
Summary
🤩
Rockstar🎓
Top SchoolAroosa Ijaz is a QML graduate researcher and PhD student at the University of Waterloo with seven years of experience at the intersection of quantum physics and software engineering. She has contributed to high-impact open-source projects like PennyLane—adding controlled rotation gates, custom qubit channels, and state-preparation improvements—bridging quantum research and production-grade tooling. Her career spans industry and national labs, including roles at Xanadu, Los Alamos National Laboratory, and a visiting stint at Freie Universität Berlin, reflecting both applied research and collaborative mentorship. Aroosa combines deep theoretical training from institutions such as ETH Zürich and Ulm University with hands-on machine learning and software development skills, and she has mentored emerging researchers in variational quantum embeddings. Based in Toronto and active at Vector Institute, she documents her evolving work in an academic diary that highlights reproducible experiments and practical implementations.
7 years of coding experience
2 years of employment as a software developer
Master's degree Physics Quantum Information, Master's degree Physics Quantum Information at Ulm UniversityBachelor's degree Physics and computer science, Bachelor's degree Physics and computer science at Lahore University of Management SciencesCertificate of Quantum Excellence Quantum Computing Quantum Machine Learning, Certificate of Quantum Excellence Quantum Computing Quantum Machine Learning at 2021 Qiskit Global Summer School on Quantum Machine LearningDoctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at ETH ZürichDoctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at University of Waterloo
English, Urdu, German, Punjabi
Github Skills (13)
quantum-computing10
pytorch10
q-learning10
python10
testing9
machine-learning9
automatic-differentiation9
unit-testing8
qml7
deep-learning6
deeplearning-ai6
tensorflow6
autograd6
Programming languages (1)
Github contributions (5)
PennyLaneAI/pennylane
Jun 2019 - Sep 2020
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 & Software Engineer
ML Engineer & Software EngineerContributions:2 reviews, 14 commits, 41 PRs in 1 year 3 months
Contributions summary:Aroosa made several significant contributions to the PennyLane library, primarily focused on expanding and improving its quantum machine learning capabilities. They added new features such as controlled rotation gates (CRX, CRY, CRZ, and CRot) and a custom qubit channel. They also fixed code snippets, corrected documentation, and updated test cases to ensure functionality. Their contributions also involved refactoring existing code and enhancing state preparation functionalities.
pythonautomatic-differentiationdifferentiable-computingcomputerstensorflow
AroosaIjaz/Mypennylane
May 2019 - Oct 2019
PennyLane is a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations
Contributions:2 PRs, 96 pushes, 27 branches in 5 months
python-librarypythonquantum-computingautomatic-differentiationdifferentiation
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