Dr Hak-Keung Lam

Dr H K. Lam's research interests include fuzzy control systems, neural networks, chaotic synchronisation and genetic algorithms. 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:

• Google scholar
• ORCID
• Web of Science
• Scopus

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

• Research Profile
• Research Funding
• Personal Website