Professor Jiamei Deng, Professor

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:

  1. 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.
  2. 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.
  3. Co-I: Smart Meter Research Portal, EPSRC, 2017-2022.
  4. The Information about the above three projects can be found here: https://gtr.ukri.org/person/61E85F70-6E06-40DF-9345-EB87626602E8

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

Professional memberships

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

Current Teaching

  1. PhD supervision
  2. 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.

Professor Jiamei Deng, Professor

Selected Outputs

  • Tian D; Deng J; Vinod G; Santhosh TV; Tawfik H (2018) A Neural Networks Design Methodology for Detecting Loss of Coolant Accidents in Nuclear Power Plants. In: Applications of Big Data Analytics. Springer International Publishing, pp. 43-61.

  • Santosh TV; Vinod G; Vijayan PK; Deng J (2018) PCA-Based Neural Network Model for Identification of Loss of Coolant Accidents in Nuclear Power Plants. In: Technology for Smart Futures. Springer International Publishing, pp. 345-354.

  • Deng J; Stobart R; liu C; Winward E (In press) Explicit Model Predictive Control of the Diesel Engine Fuel Path. In: SAE 2012 World Congress & Exhibition. SAE International.

    https://doi.org/10.4271/2012-01-0893

  • Banerjee S; Deng J; Gorse C; Vajpayee V; Becerra VM; Bausch N; Shimjith SR; Arul J (2020) ANN Based Sensor and Actuator Fault Detection in Nuclear Reactors. In: 2020 The 8th International Conference on Control, Mechatronics and Automation, 6 November 2020 - 8 November 2020.

    https://doi.org/10.1109/ICCMA51325.2020.9301579

    View Repository Record

  • Naimi A; Deng J; Abdulrahman A; Vajpayee, V; Victor B; Bausch N (2020) Dynamic Neural Network-based System Identification of a Pressurized Water Reactor. In: 2020 The 8th International Conference on Control, Mechatronics and Automation, 6 November 2020 - 8 November 2020.

    https://doi.org/10.1109/ICCMA51325.2020.9301483

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  • Vajpayee V; Becerra V; Bausch N; Banerjee S; Deng J; Shimjith SR; Arul AJ (2020) Disturbance Observer-based Subspace Predictive Control of a Pressurized Water-type Nuclear Reactor. In: 7th International Conference on Control, Decision and Information Technologies (CoDIT'2020), 29 June 2020 - 2 July 2020, Prague, Czech Republic. IEEE.

    https://doi.org/10.1109/CoDIT49905.2020.9263802

    View Repository Record

  • Vajpayee V; Becerra V; Bausch N; Banerjee S; Deng J; Shimjith SR; Arul AJ (2020) Robust Subspace Predictive Control based on Integral Sliding Mode for a Pressurized Water Reactor. In: 7th International Conference on Control, Decision and Information Technologies (CoDIT'2020), 29 June 2020 - 2 July 2020, Prague, Czech Republic. IEEE.

    https://doi.org/10.1109/CoDIT49905.2020.9263955

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  • Vajpayee V; Becerra V; Bausch N; Banerjee S; Deng J; Shimjith SR; Arul AJ (2020) Gain Scheduled Subspace Predictive Control of a Pressurized Water-type Nuclear Reactor. In: 28th Mediterranean Conference on Control and Automation (MED), 16 September 2020 - 18 September 2020, Saint-Raphaël, France. IEEE.

    https://doi.org/10.1109/MED48518.2020.9182853

    View Repository Record

  • Deng J; Banerjee S; Vajpayee V; Becerra V; Bausch N; Shimjith SR; Arul J (2020) LMI based robust PID controller design for PWR with bounded uncertainty using interval approach. In: 7th International Conference on Control, Mechatronics and Automation, 6 November 2019 - 8 November 2019, Netherlands. IEEE.

    https://doi.org/10.1109/ICCMA46720.2019.8988755

    View Repository Record

  • Deng J; Vajpayee V; Becerra V; Bausch N (2020) Wavelet-based Model Predictive Control of PWR Nuclear Reactor using Multi-Scale Subspace Identification. In: 15th European Workshop on Advanced Control and Diagnosis, 21 November 2019 - 22 November 2019, Bologona, Italy. Springer Verlag.

    https://eventi.unibo.it/acd2019

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  • Tian D; Deng J; Vinod G; Santhosh TV (2019) A constraint-based random search algorithm for optimizing neural network architectures and ensemble construction in detecting loss of coolant accidents in nuclear power plants.

    https://doi.org/10.1109/DeSE.2018.00036

    View Repository Record

  • Tian D; Deng J; Zio E; Maio F; Liao F (2018) Failure Modes Detection of Nuclear Systems Using Machine Learning. In: 2018 5th International Conference on Dependable Systems and Their Applications (DSA), 22 September 2018 - 23 September 2018. IEEE.

    https://doi.org/10.1109/dsa.2018.00017

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  • Tian D; Deng J; Vinod G; Santhosh TV (2018) Selecting a minimum training set for neural networks using Short-Time fourier transform in detecting loss of coolant accidents in nuclear power plants.

  • Wang M; Deng J; Pattinson C; Richardson S (2017) A Fuzzy Controller for Fault Tolerant Control of Nuclear Reactor. In: 2017 International Conference on Computational Science and Computational Intelligence (CSCI), 14 December 2017 - 16 December 2017. IEEE.

    https://doi.org/10.1109/csci.2017.64

  • Khanjani K; Deng J; Ordys A (2014) Controlling variable coolant temperature in internal combustion engines and its effects on fuel consumption.

    https://doi.org/10.4271/2014-32-0064

  • Levermore T; Ordys A; Deng J (2014) A review of driver modelling. In: 2014 UKACC International Conference on Control (CONTROL), 9 July 2014 - 11 July 2014, Lougborough. IEEE.

    https://doi.org/10.1109/CONTROL.2014.6915156

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  • Chan KY; Ordys A; Duran O; Volkov K; Deng J (2014) Adaptive neuro-fuzzy method to estimate virtual SI engine fuel composition using residual gas parameters.

    https://doi.org/10.1109/CONTROL.2014.6915135

  • Deng J; Ordys A (2014) Modelling and control of hybrid systems - A forward look.

    https://doi.org/10.1109/CCECE.2014.6900960

  • Zhao D; Liu C; Stobart R; Deng J; Winward E (2013) Explicit model predictive control on the air path of turbocharged diesel engines.

  • Chan KY; Ordys A; Duran O; Volkov K; Deng J (2013) SI engine simulation using residual gas and neural network modeling to virtually estimate the fuel composition.

  • Deng J; Ordys A; Yawei Wang (2012) Input choices of Particulate Matter Models for Diesel Engines. In: 2012 24th Chinese Control and Decision Conference (CCDC), 23 May 2012 - 25 May 2012. IEEE.

    https://doi.org/10.1109/ccdc.2012.6243025

  • Sedyono J; Hadavinia H; Deng J; Marchant DR; Garcia J (2012) Optimization of the stacking sequence of laminated composite plates under buckling loads.

    http://eprints.kingston.ac.uk/23236/