Theodor Isacsson is a quantum software engineer and manager with nine years of experience building hybrid quantum tools and developer-facing libraries, currently leading Tools at D-Wave. He combines hands-on Python and C++ engineering with machine learning expertise to ship production tooling for gate-model and hybrid quantum workflows. His open-source work includes substantive contributions to prominent projects like Strawberry Fields and PennyLane—implementing core CV optics features, optimizers, and QML tutorials—highlighting both deep technical skill and a passion for developer education. With a background in quantum photonics from MIT and engineering physics from KTH, he bridges experimental quantum optics and practical software systems. Colleagues describe him as a developer-manager who still ships code, integrates third-party scientific libraries, and prioritizes robust testing and clear documentation.
9 years of coding experience
7 years of employment as a software developer
Exchange program Engineering Physics, Exchange program Engineering Physics at Purdue University College of Engineering
Master's degree project Quantum Photonics, Master's degree project Quantum Photonics at Massachusetts Institute of Technology
Master's degree in Engineering Physics Nano physics, Master's degree in Engineering Physics Nano physics at KTH Royal Institute of Technology
High School Mathematics and physics, High School Mathematics and physics at Danderyds Gymnasium, Matematik-/Fysikgymnasiet
Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing continuous variable (CV) quantum optical circuits.
Role in this project:
Back-end Developer & ML Engineer
Contributions:4 releases, 354 reviews, 160 commits in 2 years 5 months
Contributions summary:Theodor's primary contributions revolve around implementing new methods and features related to two-mode squeezing gates within the Strawberry Fields library. They added methods for two-mode squeezing, modified existing methods, fixed related spelling errors and contributed significant test code to ensure proper functionality. Additionally, they incorporated the thewalrus library for the calculation of displacement, squeezing, and beamsplitter in the Fock backend, demonstrating an integration of the library within the system.
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 / Technical Writer
Contributions:93 reviews, 13 commits, 22 PRs in 1 year 3 months
Contributions summary:Theodor contributed significantly to the documentation and example implementations within the repository, focusing on quantum machine learning. They added and updated tutorials, including those for quantum optical neural networks (QONN) and other QML algorithms, ensuring correct code and thorough descriptions. They also contributed to the demos hub, improving the organization, descriptions, and appearance of the project's tutorials. This indicates a strong focus on educational content and practical application of quantum machine learning techniques.
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