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The Leeds Beckett University website occasionally uses animations to page elements and animated gifs to add impact to pages. If you wish to stop them from playing for accessibility purposes or for personal preference then please see the guidance below. Please note that browsers sometimes change how they operate, so please refer to your browser help files to find their latest information.
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Chrome

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Firefox

Type about:config in Firefox address bar and hit Enter to open Settings. Search for the image.animation_mode flag and change its value from Normal to None. Once you restart Firefox this will disable animations.

Professor Jiamei Deng

Professor

Dr. Jiamei Deng joined Leeds Beckett University as a Professor in Artificial Intelligence, Control, and Energy in 2015. Her research has been focused on data analytics, artificial intelligence, and control system design for different applications, such as biomedical engineering, civil engineering, automotive engineering, nuclear power plants, other energy systems. She is holding two EU patents. Jiamei is also the sole author of one monograph, the main author of three book chapters, and has authored /co-authored over one hundred papers including prestigious journals, such as IEEE Transactions on Neural Networks and Learning Systems, IEEE Transaction on Industrial Electronics, Engineering Applications of Artificial Intelligence.

Jiamei’s recent government funded projects:

Leading Principal Investigator (PI) for three linked projects (EP/M018717/1, EP/M018709/1, EP/M018415/1), Smart on-line monitoring for nuclear power plants (SMART) , EPSRC, 2015-2018. This project used data science and artificial intelligence to generate monitoring tools for nuclear power plants.
PI: Fault tolerant control for increased safety and security of nuclear power plants , EPSRC, 2018-2022. This project has been using data science, artificial intelligence, and control theory to design an integrated module for increased safety and security of nuclear power plants.
Co-I: Smart Meter Research Portal, EPSRC, 2017-2022.

The Information about the above three projects can be found here: https://gtr.ukri.org/person/61E85F70-6E06-40DF-9345-EB87626602E8

PI: Research on Fault tolerant control, Royal Academy of Engineering, 2018.

Professional memberships

Member of EPSRC Peer Review College
Member of Smart Energy Research Lab - https://serl.ac.uk/about-who-we-are/
Senior Member of IEEE
Fellow of Higher Education Academy

Current Teaching

PhD supervision
Master level individual project supervision

Teaching Master level modules:

Data analytics and visualization
Research practice
Engineering systems control

Research Interests

Big data, artificial intelligence, control system design, energy system efficiency and safety

Professor Deng welcomes any enquiry about these topics either from industry or research organization. She also welcomes motivated and qualified applicants who are interested in PhD study in her group.