Company: Assured Systems -
Brief description of the project:
Energy-efficient, privacy preserving machine learning for Internet-of-things applications.
The project involves researching methods for training machine learning algorithms without compromising user privacy or model accuracy in an energy-efficient manner. Applications for such machine learning models include smart energy monitoring, smart transportation and wearables.
This project is partnered with Assured Systems (UK) Ltd, a leading technology company offering high quality and innovative computer solutions to the embedded, industrial, and digital-out-of-home market sectors. Assured systems are keen to combine SEND research performed at Keele with new products and applications tailored towards the renewable and smart energy markets.
Student: Chris Briggs
Supervisor: Professor Zhong Fan; Professor Peter Andras