Amira Abbas is a Quantum Research Scientist with eight years of experience blending quantum physics and machine learning across industry and academia. She holds a PhD in Physics and has progressed from research roles at IBM and Google internships to postdoctoral positions at QuSoft/UvA and a current research role at Google. Her work spans hybrid quantum-classical ML—she contributed to the well-known Qiskit Textbook by implementing PyTorch-Qiskit hybrid neural network notebooks that clarify practical quantum classification models. Based in Santa Monica, she brings a rare mix of actuarial-trained analytical rigor and hands-on quantum software engineering. Colleagues rely on her for translating theoretical quantum algorithms into reproducible, teachable code and experiments. She consistently focuses on making cutting-edge quantum ideas accessible and verifiable through open, educational artifacts.
8 years of coding experience
6 years of employment as a software developer
Bachelor of Business Science (with honours) Actuarial Science, Bachelor of Business Science (with honours) Actuarial Science at University of Cape Town
Doctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at University of KwaZulu-Natal
[ARCHIVED] A university quantum algorithms/computation course supplement based on Qiskit
Role in this project:
ML Engineer
Contributions:22 commits, 3 PRs, 3 comments in 1 month
Contributions summary:Amira contributed to a project focused on hybrid quantum-classical machine learning. Their commits primarily involve developing and updating a Jupyter Notebook that integrates PyTorch and Qiskit. They are focused on demonstrating and explaining the concepts of hybrid quantum-classical machine learning, the code implements a hybrid neural network for classification.
Contributions:1 release, 38 commits, 1 push in 9 days
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Amira Abbas - Quantum Research Scientist at Google