Professor of Engineering
Academic Division: Information Engineering
Research group: Control
Telephone: +44 1223 3 32677
Professor Sepulchre’s research aims at developing novel mathematical tools for the modelling, analysis, and synthesis of nonlinear signals and systems.
Many data are inherently constrained to lie on a nonlinear space. Manifold optimization is a novel algorithmic framework that provides generic optimization tools to process data on particular nonlinear spaces. Applications involve nonlinear statistical processing (such as ICA or sparse PCA), low-rank optimization, matrix completion, and diffusion tensor imaging.
Synchronization, coordination, and consensus problems underpin much of the collective dynamics taking place in distributed or multi-scale dynamical systems. Sepulchre’s research focuses on studying those problems in nonlinear spaces, with applications to coordinated robotics or oscillators synchrony.
Neural behaviours offer a particular challenge to system theory because of their nonlinear nature. New sensitivity analysis tools are developed based on a local analysis around singular points that organize the global behaviour. Those tools are applied to address the robustness and homeostasis of neural behaviours.
A main focus of Sepulchre’s current research is to advance the understanding of the role of oscillations in the brain across different time and spatial scales.
Inspiring research through industrial collaboration
Distributed architectures for multi-scale control problems.