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Engineering

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Dr. Dawei Qiu is a Lecturer in Smart Enery Systems (E&R) within the Department of Engineering at the University of Exeter since 2024.

Dr. Qiu received the B.Eng. degree in Electrical and Electronic Engineering from Northumbria University in 2014, the M.Sc. degree in Power System Engineering from University College London in 2015, and the Ph.D. degree in Electrical Engineering from Imperial College London in 2020. After graduation, Dr. Qiu was employed as a Research Associate at Imperial College London. Since June 2023, Dr. Qiu has been promoted to be a Research Fellow in Market Design for Low-Carbon Energy Systems at Imperial College London.

His research focuses on advanced energy system modelling, which has proven to be highly valuable in providing a comprehensive assessment of future low-carbon energy systems. These modelling techniques cover various aspects, including electricity, heat, gas, and transportation. His research has made a significant contribution by creating novel market-driven approaches and modelling methodologies that have been widely applied to analyse and evaluate the energy cost, carbon emission, and ancillary service of future low-carbon energy systems. The insights derived from his research have contributed to a better understanding of the complexities and opportunities in future energy systems, including the role and value of emerging technologies such as flexible demand, energy storage, electric vehicles, and microgrids. His expertise on AI-driven reinforcement learning has motivated him to currently lead its development and application to various energy system problems. He has published more than 50 peer-reviewed papers, including top journal publications in IEEE Transactions and Applied Energy, as well as one world A-class AI conference IJCAI2021.

As the project/task/work package leader, Dawei has contributed to several EU and UK research projects focused on energy market modelling, energy system decarbonisation, and energy resilience analysis: the EU's Horizon 2020 projects "TradeRES" (864276) and "R2D2" (101075714), as well as the UK's EPSRC projects "IDLES" (EP/R045518/1) and "NetworkPlus" (EP/W034204/1).

PhD applications are welcome.

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