PeopleofSuperintelligence

Researcher

Adam Smith

Also known as Adam Gammon-Smith

Adam Smith is a condensed-matter physicist who applies machine learning and quantum computing to many-body physics. He studied mathematics at Leeds and physics at Cambridge, then held research posts at Imperial College London and the Technical University of Munich. At Nottingham, he received a 2020 Royal Commission for the Exhibition of 1851 research fellowship for work on strongly correlated matter and quantum computers. His research includes a 2022 quantum machine-learning method and a 2023 quantum convolutional neural-network study of quantum phases. He is an associate professor at Nottingham, and his 2026 review examines topological order on quantum processors.

Works
269
Citations
23,415
h-index
57

Publication numbers from OpenAlex, as of 15 October 2026.

Timeline

  1. 2010–2018

    Studying mathematics and physics

    He studies mathematics at the University of Leeds from 2010 to 2014, physics at Cambridge from 2014 to 2015, and completes his Cambridge PhD in 2018.

  2. 2018–2020

    Research at Imperial and TUM

    At Imperial College London, he works with Myungshik Kim and Johannes Knolle from September 2018 to November 2018 on a collaboration with Samsung to simulate quantum systems on IBM computers. From December 2018 to November 2020, he works with Frank Pollmann at the Technical University of Munich.

  3. 2020–2021

    An 1851 research fellowship

    In 2020, he receives an 1851 Research Fellowship to study strongly correlated matter and many-body quantum physics with quantum computers at Nottingham. The fellowship runs from December 2020 to December 2021.

  4. 2022

    Compressing data for quantum learning

    With Rohit Dilip, Yu-Jie Liu and Frank Pollmann, he develops a quantum machine-learning method to compress and load classical data on quantum devices. The 2022 approach controls the number of qubits and the circuit depth.

  5. 2022–2024

    Assistant professor at Nottingham

    He becomes an assistant professor at the University of Nottingham in January 2022 and serves in the role through August 2024.

  6. 2023

    A quantum neural-network protocol

    With Yu-Jie Liu, Michael Knap and Frank Pollmann, he trains a quantum convolutional neural network to identify phases and locate a phase boundary in a 2023 paper.

  7. October 2025

    Reviewing topological order

    With Michael Knap and Frank Pollmann, he posts a review of progress toward topological order on quantum processors to arXiv in October 2025.

  8. Since 2024

    Associate professor at Nottingham

    He becomes an associate professor at the University of Nottingham in August 2024 and remains in that role in 2026. In January 2026, his review with Michael Knap and Frank Pollmann appears in Nature Reviews Physics and surveys work on simulating topological order on quantum processors.

Sources and credits

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  1. Adam Gammon-Smith adamsmith-physics.github.io. Checked 15 October 2026.
  2. Royal Commission for the Exhibition 1851 royalcommission1851.org. Checked 15 October 2026.
  3. [2204.11170] Data compression for quantum machine learning arxiv.org. Checked 15 October 2026.
  4. [2211.11786] Model-Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks arxiv.org. Checked 15 October 2026.
  5. [2510.07023] Simulating Topological Order on Quantum Processors arxiv.org. Checked 15 October 2026.
  6. Simulating topological order on quantum processors | Nature Reviews Physics nature.com. Checked 15 October 2026.