Brian Coyle
Senior Researcher
Research Interests:
Quantum computing
Quantum machine learning,
Variational quantum algorithms
I received my PhD from the University of Edinburgh in 2021 in quantum computing and quantum machine learning, with a previous BSc and MSc in the area of theoretical physics. I then completed a 1 year postdoc at UCL working on tensor network methods, before becoming a Staff Scientist at QCWare. I am also working as a senior researcher (part time) at the Quantum Software Lab in Edinburgh. My primary interests are in developing algorithms and applications for quantum computers, taking insights from the success of classical machine learning.
Featured Publications Hyper Compressed Fine-Tuning of Large Foundation Models with Quantum Inspired Adapters https://arxiv.org/abs/2502.06916 Training-efficient density quantum machine learning https://arxiv.org/abs/2405.20237 Machine learning applications for noisy intermediate-scale quantum computers https://arxiv.org/abs/2205.09414 Robust data encodings for quantum classifiers [https://arxiv.org/abs/2003.01695] The Born Supremacy: Quantum Advantage and Training of an Ising Born Machine https://arxiv.org/abs/1904.02214