Quantum Companies, Quantum People

Tim Baxter, former Samsung CEO, joins IonQ’s board with quantum focus.

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August 25, 2026 by Ivy Delaney

IonQ has appointed Timothy Baxter, former CEO of Samsung North America, to its board of directors following the company’s recent acquisition of SkyWater Technology, where Baxter served as Chairman until the deal closed. Baxter brings over four decades of experience launching technologies such as 5G, HDTV, and Blu-ray, skills IonQ intends to leverage as it pursues manufacturing in quantum computing.

“This is a significant step for IonQ,” said IonQ Chairman and CEO Niccolo de Masi. The move also adds Dr. Eric Ball, who arranged $52 billion in financing during his time as Senior Vice President and Treasurer at Oracle, to the board.

IonQ Expansion Fueled by SkyWater Technology Acquisition

Dr. Eric Ball complements Baxter’s technology launch expertise with substantial financial acumen. He also authored two books and holds a PhD in Management Economics, further diversifying the board’s expertise. These appointments reflect IonQ’s strategy of integrating all components of its quantum platform, positioning the company to capitalize on advancements in quantum computing. Both Baxter and Ball currently serve on multiple corporate and non-profit boards, demonstrating a commitment to governance and strategic oversight.

We’re making the leap to rapid scalability in quantum computing manufacturing, in parallel with integrating all components of our unique quantum platform.

Niccolo de Masi, IonQ Chairman and CEO
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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