Stephen Wood
Retired at IBM
Rochester, Minnesota, United States
Summary
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RockstarStephen Wood is a retired software engineer with eight years of hands-on experience in quantum computing software, formerly contributing at IBM from Rochester, MN. He has practical back-end and algorithm engineering experience across the Qiskit ecosystem, improving optimizers, variational forms, quantum chemistry drivers, and MP2/Hartree–Fock tooling. Stephen’s contributions span code, reproducibility fixes (seed usage), memory and data-handling improvements, and sustained documentation and tutorial updates that kept widely used projects like Qiskit and its tutorials current. His background combines practical algorithm work with meticulous technical writing—an uncommon mix that helped both developer productivity and user-facing clarity in open-source quantum software.
8 years of coding experience
Github Skills (19)
algorithm10
apim10
algorithms10
quantum-chemistry10
python10
optimizers10
back-end-development10
machine-learning10
optimizer10
computational-chemistry10
api10
quantum-computing10
jupyter-notebook10
qiskit10
documentation10
Programming languages (7)
Github contributions (5)
qiskit-community/qiskit-nature
Feb 2019 - Apr 2022
Qiskit Nature is an open-source, quantum computing, framework for solving quantum mechanical natural science problems.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1125 reviews, 88 commits, 104 PRs in 3 years 2 months
Contributions summary:Stephen made significant contributions to the Qiskit Nature project, focusing on the implementation of utility classes and features related to quantum chemistry calculations. Their work involved adding and improving functionalities for Moller-Plesset 2nd order (MP2) calculations, and support for Hartree-Fock methods in drivers such as PySCF and PyQuante. Furthermore, they modified components to improve code quality and convergence for the described methods. They also made improvements to the existing code base related to the mapping of fermionic operators to qubit operators.
qiskitquantum-computing
qiskit-community/qiskit-machine-learning
Apr 2019 - Jun 2021
An open-source library built on Qiskit for quantum machine learning tasks at scale on quantum hardware and classical simulators
Role in this project:ML Engineer
ML EngineerContributions:753 reviews, 30 commits, 100 PRs in 2 years 2 months
Contributions summary:Stephen contributed to the quantum machine learning project by implementing and improving several components. They added usage of random seeds in the code, ensuring reproducibility. Furthermore, the user made minor cleanup and PEP8 fixes. Finally, they updated the documentation for the project, reflecting their involvement in various aspects of the codebase.
hardwaremachine-learningqiskitquantum-computing
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