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Dr Hak-Keung Lam
Dr Hak-Keung Lam

Dr Hak-Keung Lam

  • Academics
  • Supervisors


Associate Editor of IEEE Transactions on Fuzzy Systems, International Journal of Fuzzy Systems, Journal of Intelligent Learning Systems and Applications.

Research subject areas

  • Engineering

Contact details


H K Lam’s research interests include control theory, intelligent systems, computational intelligence, machine learning and their applications. He has authored/co-authored over 480 publications (as of 2023) on these topics.

His citation information can be found in the links below:

He serves as an area editor/guest editor/editorial board member for a number of journals, a program committee member, an international advisory board member, an invited session chair, publication chair and programme chair for various international conferences, and a reviewer for various books, international journals and international conferences. He has organised a number of special sessions for international conferences.

He was an associate editor for IEEE Transactions on Circuits and Systems II: Express Briefs and is an associate editor for IEEE Transactions on Fuzzy Systems, IET Control Theory and Applications, International Journal of Fuzzy Systems, Neurocomputing and Nonlinear Dynamics.

He is a co-editor for two edited volumes: Control of Chaotic Nonlinear Circuits (World Scientific, 2009) and Computational Intelligence and Its Applications (World Scientific, 2012), and the author/co-author of the books Stability Analysis of Fuzzy-Model-Based Control Systems (Springer, 2011), Polynomial Fuzzy Model Based Control Systems (Springer 2016), Interval Type-2 Fuzzy-Model-Based Systems (Springer, 2016).

He is an IEEE Fellow for contributions to analysis and design of fuzzy model-based control systems. He has been named a Highly Cited Researcher (Clarivate Web of Science) since 2018.

Research interests

Control Theory and Intelligent Systems

  • Fuzzy modelling
  • Fuzzy-model-based control
  • Neural network-based control
  • Control methods: PID control, state-feedback control, fuzzy logic control, time-delayed control, sampled-data control, networked control, fault-tolerant control, sliding-mode control, switching control
  • Stability/performance/robustness analysis
  • Lyapunov stability

Computational Intelligence

  • Fuzzy logic, type-1 fuzzy sets, type-2 fuzzy sets, interval type-2 fuzzy sets
  • Neural networks (NN)
  • Neural-fuzzy network (NFN)
  • Support vector machine (SVM)
  • Meta-heuristic optimization algorithm, evolutionary algorithms, genetic algorithm, swarm intelligence, particle swarm optimisation algorithm


Machine Learning

  • Deep learning
  • Deep structured network: feedback forward neural network, variable-weight neural network, variable-structure neural network, graph neural network (GNN), convolutional neural network (CNN), recurrent neural network (RNN), Long-short term memory (LSTM), generative adversarial network (GAN)
  • Reinforcement learning
  • Data-driving modelling/control
  • Explainable artificial intelligence (XAI), machine explainability


Biomedical Applications

  • Classification of EMG/ECG/EEG signal
  • Catheter classification and detection
  • Seizure phases and types, hand gestures, brain signals
  • Classification of COVID-19
  • Detection of non-erosive reflux disease
  • Depth estimation of hard inclusions in soft tissue


Engineering Applications

  • Control of autonomous vehicles, bolt tightening, continuum manipulators, inverted pendulum, mobile robots, motors, power converters, robot arms, vehicle suspension systems
  • Ball bonding inspections
  • Hand-written/voice command recognition
  • Classification of material textures
  • Path planning for robot navigation

More information