Cesar Angeles

Head Data Scientist - Yottar LTD

How Digital Twins are helping Decarbonise the Energy Sector

30 min talk Entry level 🤖 Data + AI

“Digital twins have been defined as virtual models of existing products or systems able to exchange information between the real and virtual representation for purposes of parameters estimation, uncertainty reduction, scenario planning, decision-making support and control.

The ever-increasing deployment of DERs will require of faster decision making and control to optimally utilise their stochastic generation nature. Digital twins within the energy grid promise to optimally utilise current grid infrastructure to keep the rollout of renewable and low carbon technologies in a safe, efficient and fair manner.”

Key Takeaways

  • How Machine Learning, Data Science and AI can be used to aid to create technologies and processes where environment, society and industry form symbiotic relations for a better future.

Bio (continued)

Cesar has published papers in journals such as Scientific Reports Nature and presented novel research projects in conferences around the world.
In the past, he has work in academia as a lecturer in the fields of Data Science, control theory and engineering within the department of Engineering for Innovation Studies at the Iberoamerican University in Mexico City.
His background is in Electrical and Electronics Engineering with a Master’s degree in Nanoelectronics and Nanotechnology from the University of Southampton and an Control Systems Engineering diploma at the University of Stanford, California.
He further specialised with graduate studies in the fields of Data Science, Machine Learning and Embedded Intelligence at the University of Southampton and Heriot-Watt University in the UK applied to control systems and digital twin development.
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Cesar Arturo Angeles Ruiz, is a full-time PhD researcher within the CDT in Environmental Intelligence at the University of Exeter in the UK and part-time Data Scientist for the energy system at Yottar LTD.

His work mainly focuses on the application of novel artificial intelligence and data science algorithms to understand the behaviour of cyber-physical systems - more specifically the energy system to improve people’s quality of life and their environment through technology.

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