Dr Ross Drummond

School of Electrical and Electronic Engineering

Lecturer in Control and Systems Engineering

Photo of Dr Ross Drummond
Profile picture of Photo of Dr Ross Drummond
ross.drummond@sheffield.ac.uk

Full contact details

Dr Ross Drummond
School of Electrical and Electronic Engineering
Amy Johnson Building
Portobello Street
Sheffield
S1 3JD
Profile

Ross Drummond received an MEng degree from the Department of Aeronautical Engineering at Imperial College London (2009-2013). He then moved to the Control Group at the University of Oxford (2013-2017) to complete his DPhil degree. After some time as a research assistant (2017-2020) working on battery modelling, he was awarded a UK Intelligence Community research fellowship from the Royal Academy of Engineering. He is set to begin a lectureship in the Department of Automatic Control and Systems Engineering at the University of Sheffield upon completion of his fellowship.

Research interests

My research focuses on the use of modelling, control theory and optimisation to improve the performance of energy storage devices, notably lithium ion batteries. By using ideas from control theory to make our energy storage devices smarter, the goal of this research is to enable better batteries through more efficient management and control.

Understanding lithium ion batteries requires understanding the dynamics of nonlinear systems. For that reason, another aspect of my research is on developing tools to characterise stability properties of nonlinear systems. A particular focus is on the absolute stability problem where my collaborators and I have developed several results including on the search for Zames-Falb multipliers and Lyapunov functions.

Using these methods on the stability analysis of nonlinear systems, I have been motivated to address the problem of the lack of robustness of machine learning algorithms, particularly those driven by neural networks. As well as quantifying neural network robustness, I am also interested in drawing connections between model-based and datadriven control. The goal of this research is to exploit control theory’s understanding of nonlinear system dynamics to facilitate the deployment of data-driven control to safety-critical systems.

Publications

Journal articles

Conference proceedings papers

Preprints

Grants

Research Grants

  • High energy density battery pack design without compromising on safety, Royal Academy of Engineering, UK Intelligence Community Research Fellowship, 10/2020 - 11/2023, £200,000 as PI
Teaching activities

ACS133 Physical Systems