Mr Daniel Goldsmith
Contact
- Email: d.goldsmith@kingston.ac.uk
- Location: Penrhyn Road
- Faculty: Faculty of Engineering, Computing and the Environment
- School: School of Computer Science and Mathematics
- Department: Department of Computer Science
Research project: Quantum Machine Learning for Sustainable Energy Optimisation
Abstract
My PhD focuses on Quantum Machine Learning (QML), which aims to leverage the quantum effects of superposition and entanglement to deploy algorithms that have superior performance to classical ML models on contemporary quantum devices. Energy systems has been chosen as the application domain for this proposal because QML has the potential to improve both network resilience and efficiency. Energy systems are changing rapidly, as energy sources are decarbonised to avoid runaway climate change. This research will:
- identify further energy system use cases
- assess the use cases most likely to benefit from QML through active enagement with energy systems companies and
- develop a novel QML algorithm for one energy system use case, simulate this on a classical simulator with real life data, and compare this model to the best of breed classical ML model.
- Research degree: PhD
- Title of project: Quantum Machine Learning for Sustainable Energy Optimisation
- Research supervisor: Dr Xing Liang
- Other research supervisor: Professor Dimitrios Makris
Biography
I am currently working as a Senior Quantum Computing Technologist at Digital Catapult, a not for profit organisation which aims to accelerate the adoption of advanced digital technology in the UK. I was responsible for developing technical content for the Digital Catapult Quantum Technology Access Programme (QTAP). I studied quantum mechanics, quantum circuit design and linear algebra in my Quantum Technology Masters at UCL. Before that I worked in IT as an SAP consultant, leading teams to design and build international SAP solutions, mainly in Finance and management accounting. I studied Physics as an Undergraduate at Jesus College, Cambridge, and qualified as a chartered accountant.
I am a keen cyclist.
Areas of research interest
- Quantum Machine Learning
- Sustainable Energy
- Quantum Optimisation
Qualifications
- Masters in Quantum Technology, UCL
- Chartered Accountant
- Physics undergraduate degree at Jesus College, Cambridge.
Publications
Goldsmith D, Day-Evans J. Beyond QUBO and HOBO formulations, solving the Travelling Salesman Problem on a quantum boson sampler [Internet]. arXiv; 2024. Available from: http://arxiv.org/abs/2406.14252 (submitted for journal publication)
Goldsmith D, Mahmud MM Hassan. Machine Learning for Quantum Computing Specialists [Internet]. arXiv; 2024 Available from: http://arxiv.org/abs/2404.18555