Joel Pendleton is a founder and hands-on CTO building silicon-chip quantum computers from San Francisco, combining 11 years of applied research and ML engineering with startup leadership. He co-founded Conductor Quantum after a string of research roles where he developed ML-driven control and automation for superconducting and quantum-dot devices, and previously led an AI-driven science assistant startup. Joel bridges deep physics (MSci first-class, DPhil in progress at Oxford) with practical tooling—contributing to open-source ML interoperability work such as tensor frontends and NumPy extensions to make research code portable. He’s comfortable moving between low-level quantum hardware challenges and high-level software systems, and brings a rare mix of simulator, ML, and lab automation expertise to scale qubit control.
11 years of coding experience
2 years of employment as a software developer
DPhil, Engineering Science, DPhil, Engineering Science at University of Oxford
Contributions:5 reviews, 9 commits, 24 PRs in 3 months
Contributions summary:Joel contributed to the TensorFlow frontend, adding a `pinv` function and implementing `rank` and `einsum` functionalities. They also implemented the `shape` function for the TensorFlow frontend. Furthermore, the user introduced the `clip` instance method for NumPy's ndarray class. These changes indicate a focus on expanding the framework compatibility of the project and enhancing the functionality of NumPy and TensorFlow.
Contributions:66 commits, 56 pushes, 6 branches in 7 months
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Joel Pendleton - Co-Founder And CTO at Conductor Quantum