Chris Briggs

Background

I am a PhD researcher funded under the Smart Energy Network Demonstrator (SEND) project and the School of Computing and Mathematics at Keele university. I am researching the intersection of privacy preserving machine learning and smart energy applications under the supervision of Prof. Zhong Fan and Prof. Peter Andras. Prior to my PhD study, I worked as a software engineer in industry for over 10 years.

Research interests

My main research focus is on privacy preseving machine learning for smart energy applications. I am particularly interested in a form of collaborative machine learning over distributed data known as federated learning. Although federated learning demonstrates a promising way forward to provide private analytics over sensitive user data, the protocol suffers when data is not ideally distributed between the connected users. My research focuses on training multiple specialised models that acheive good performance for subsets of users by clustering users who provide similar model updates to the global model. As part of the SEND project, I aim to apply my work to forecasting energy consumption in a privacy preserving way using deep learning.

Additional to my main research focus, I have worked on several projects in/outside of the university such as:

Recent publications & conferences

Contact details