Richard Burke

Staff

Department of Mechanical Engineering

Professor Richard Burke

Richard’s research focuses on understanding, modelling and optimising powertrain systems operating under transient conditions. Powertrains consist of many components (engines, transmissions, catalysts, electric motors, batteries) that can each be seen as non-linear, dynamic and time dependent sub-systems. At the same time, most of the large fuel consumption gains have already been achieved, and improvements tend to happen in small steps. This requires high precision modelling and testing methods to be able to demonstrate these benefits. The following research topics would therefore benefit from more mathematical and statistical insights: Frequency domain analysis and time series modelling of powertrains, statistical techniques to integrate a form of process control in powertrain testing facilities (such as multivariate statistics), methods for analysing diverse and random on-road data.

University of Bath Research Portal:

https://researchportal.bath.ac.uk/en/persons/richard-burke/

Second Supervisors

Alessandro Leronni

Department of Mechanical Engineering

Research interests

Continuum modelling of electrochemo-mechanical systems
Finite element implementation of multiphysics frameworks
Smart materials, energy storage, and developmental biology

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Da Chen

Department of Computer Science

Research interests:

Computer vision, deep learning, multimodal learning: general CV/ML tasks in practical scenarios.
Learning with limited data: Learning with imbalanced data, long-tailed data, open-set data, out-of-distribution data, etc; incremental learning, few-shot learning, etc.
Video processing: multimodal learning with video with visual, textual, and audio information.