Evolving the global energy sector to affordable, abundant, and low-carbon energy within a generation is the top priority for the energy and utilities sector and requires a drastic shift for many. Capgemini believes in focusing on what the energy transition enables in our economy and society, rather than just what it must avert.
In this talk, Capgemini will present two research projects and two of their offers that demonstrate how data and advanced analytics can help manage energy use at home, forecast air quality, and optimise asset maintenance in power grids.
Wednesday 14 August 2024
12pm
Online
Duration: 1 hr
Register nowYuchen Shang is a data scientist and software engineer at Hybrid Intelligence, Capgemini Engineering with a deep background in science and engineering. His project experience at HI includes developing reinforcement learning agents for household energy management, multimodal single-cell integration and prediction, and data science consulting for rail-transport.
Dominic McEwen is a data scientist and software engineer. Since joining Hybrid Intelligence Dominic has worked on a variety of data science projects in the life science and energy domain, including a research project looking into temporal graph neural networks and the development of a clinical trial site selection and enrolment forecasting tool.
Danica Vukadinovic Greetham is an analytics consultant at Hybrid intelligence, Capgemini Engineering. She has 20 years of experience in predictive analytics of large human activity datasets, including smart energy, brain networks and social media, more than 50 publications, and has helped companies across different sectors to create data & digitalization vision, strategy and roadmaps.
Find out more about how Energy Systems Catapult can help you and your teams
Find out more about how Energy Systems Catapult can help you and your teams