Academic Division: Energy, Fluid Mechanics and Turbomachinery
Research group: Energy
Scott is part of Dr Jonathan Cullen’s group - the Resource Efficiency Collective - at the Department of Engineering. His research is in Reinforcement Learning (RL), a subfield of Artificial Intelligence, where he designs agents that learn to reduce emissions from energy-intensive industrial processes autonomously. He works with Emerson Electric, a US Fortune-500 company, and operator of 10,000 cold storage facilities in North America. Together, they use cold-store facility data to make predictions of future occupancy, weather, produce-levels, and grid carbon intensities that inform energy-efficient control policies.
- ETB4: Energy Systems and Efficiency
- 4M22: Climate Change Mitigation
- Sustainability steering committee member at the Alan Turing Institute
Scott is interested in machine intelligence and its capacity to help humans mitigate climate change. In practice, this means writing machine learning algorithms – primarily model-based Reinforcement Learning agents (RL) with Gaussian Processes (GPs) – to optimise the control of equipment in buildings and industrial processes. He’s particularly interested in an RL agent’s ability to take actions that, at first, seem counter-intuitive to humans, but later provide us a richer understanding of the system than we could have achieved alone. In the past, Scott has completed engineering degrees at the University of Cambridge and the University of Edinburgh, conducted research with the Use Less Group at Cambridge, and worked as a management consultant. His research is generously funded by the EPSRC, Emerson Electric and Sir Sean Connery’s Scottish International Education Trust.
Department role and responsibilities
- Division A seminar series coordinator