Peter Grindrod is Professor in the Mathematical Institute, University of Oxford.
His research interests are:
- The theory and applications of dynamically evolving networks, including nonlinear node-based dynamics, fully coupled through time dependent network dynamics. Stochastic modelling and classification of behaviour within evolving peer-to-peer communication and social networks. Memory dependent network dynamics. Generalisations of centrality to continuous time networks.
- Applications of mathematics to social media, digital media and marketing, and the digital economy. Design of algorithms that run in real time over vast peer-to-peer networks. Applications of mathematics to the emergence of social norms and attitudes.
- Dynamical systems and Delay Differential Equations. Theory and appications of semilinear parabolic systems. Non-Fickian dispersion.
- Analysis of fMRI scans of human brains, including measures of network "fragility" as predictors of future performance and early cognitive degradation. The human brain as a complex information processing system: implications for novel computing paradigms.
- Modelling, analysis and forecasting of domestic and small business energy consumption on low voltage networks including dynamic behaviour driven segmentations of consumers via smart meter data; novel methods of forecasting peaks in demand; and future scenarios for energy use and uptake to technologies. Probabilistic forecasting of spiky timeseries.
- Inference and forecasting problems for the retail, consumer goods, and telecommunications sectors. Behaviour-based risk measures and targetted-marketing applications.
- Models for counter terrorism and real time recognition of anomalies within vast communications data sets.
- Strategy for investment in science and technology research and innovation. Knowledge exchange and balancing open public research with confidential commercial interests through open innovation.