Professor Jiamei Deng

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About

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.

Selected Publications

Journal articles (29)

Chapters (2)

  • 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.
    https://doi.org/10.1007/978-3-319-60137-3_17
  • 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.
    https://doi.org/10.1007/978-3-319-76472-6_3

Conference proceedings (20)

  • 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, pp. .
    https://doi.org/10.4271/2012-01-0893
  • 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 06/11/2020 00:00:00. : , pp. 100-104.
    https://doi.org/10.1109/ICCMA51325.2020.9301483
    View Repository Record
  • 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 06/11/2020 00:00:00. : , pp. .
    https://doi.org/10.1109/ICCMA51325.2020.9301579
    View Repository Record
  • 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) Prague, Czech Republic 29/06/2020 00:00:00. : IEEE, pp. 1012-1017.
    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) Prague, Czech Republic 29/06/2020 00:00:00. : IEEE, pp. 7-12.
    https://doi.org/10.1109/CoDIT49905.2020.9263955
    View Repository Record
  • 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) Saint-Raphaël, France 16/09/2020 00:00:00. : IEEE, pp. 91-96.
    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 Netherlands 06/11/2019 00:00:00. : IEEE, pp. .
    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 Bologona, Italy 21/11/2019 00:00:00. : Springer Verlag, pp. .
    View Repository Record
  • 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. In: . : , pp. 237-243.
    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) 22/09/2018 00:00:00. : IEEE, pp. .
    https://doi.org/10.1109/dsa.2018.00017
  • 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. In: . : , pp. 278-284.
  • 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) 14/12/2017 00:00:00. : IEEE, pp. .
    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. In: . : , pp. .
    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) Lougborough 09/07/2014 00:00:00. : IEEE, pp. 296-300.
    https://doi.org/10.1109/CONTROL.2014.6915156
    View Repository Record
  • 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. In: . : , pp. 174-179.
    https://doi.org/10.1109/CONTROL.2014.6915135
  • Deng J; Ordys A (2014) Modelling and control of hybrid systems - A forward look. In: . : , pp. .
    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. In: . : , pp. 5213-5218.
  • 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. In: . : , pp. 897-903.
  • 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) 23/05/2012 00:00:00. : IEEE, pp. .
    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. In: . : , pp. .