ESR

Here you will soon find information about our early stage researchers and their research bio and background.

ESR 01 – Djordje Batic
Towards interpretable ML models for low-carbon technologies
ESR 04 – Stavros
Adaptable semi-supervised recurrent deep learning and concepts of tensor algebra for extracting meaningful patterns from energy signals
ESR 07 – Chiara Tellarini
Influence of smart metering and micro-generation on prosumer’s energy demand
ESR 10 – Vinicius Juliani
CHT for low-energy scripting
ESR 13 – Md Shajalal


Explainable AI (XAI) for smart, domestic technologies


ESR 02 – Apostolos Vavouris
Co-design of information extraction methods to meet privacy and trust requirements
ESR 05 – Milad Bohlouli
Designing CHT for energy efficient and sufficient consumption practices and domestic routines

ESR 08 – Fernanda Guasselli
Smart building designs and closing the energy performance gap
ESR 11 – Joe
Design methodology for user centred perspective of smart grids recognising diversity of user groups
ESR 14 – Sotiris


Responsible ML models that prevent undesirable outcomes for low-carbon CHT

ESR 03 – Tamara Todic
Evaluation of the responsibility of AI
ESR 06 – Somayeh ZamaniKasbi
Using computational and explainable ML methods to support end consumers to renovate domestic infrastructure
ESR 09 – Nickhil Sharma
Smart energy technologies and the energy poor
ESR 12 – Lu Jin
Intelligent Personal Assistants (IPA) for energy-related routines
ESR 15 – Christoforos Menos-Aikateriniadis
Implementation of trustworthy ML-driven software solutions for energy demand measures and optimal flexibility aggregation and management strategies