This research group parked under Centre for Telecommunication, Research & Innovation (CeTRI), along with the wireless communication technology. The aim of this research group is to cater the growing demand of research and development in hardware and software of electronic and computer engineering, in particular for machine learning and signal processing. This research group focuses on several related areas that can be classified into hardware related entity (nano-computing) and software related entity (information engineering).
In Nano-Computing, there will be Programmable Device and System, Device Modelling and Device and System Realization. Meanwhile, in Information Engineering includes, Digital Signal & Image Processing, Algorithm Design and Development and Biomedical Engineering. The two entities are correlated and complement to each other to build a particular system, such as an embedded system design. For example, the novel algorithms can be designed through the information engineering group, which can produce high impact publications. Meanwhile, the implementation can be done through nano-computing group to produce commercial products. Therefore, the MLSP group will support the CeTRI through the Nano Computing and Information Engineering cluster.
Our research theme as follows:
1. Computer Vision & Image Processing
Image and video processing (including stereo and multi-view images)
Intelligent surveillance and security system (including object detection)
Biometric recognition system
Image and video processing (Quantification, Segmentation and Classification, Enhancement)
Image and video compression
2. Signal Processing & Artificial Intelligent
Bio-signal processing and modeling
Brain-computer (machine) interface
Human attention level detection
Speech & audio processing for hearing aids and fault detection in machine
Neuro-feedback/bio-feedback
Real-time and predictive diagnostics in neurology & psychiatric disorders
Modeling and approximation in stochastic modeling
3. Algorithm Design & Development
Developing novel theoretically-inspired methodologies targeting both longstanding and emergent signal processing applications.
Encompasses new theoretical frameworks for statistical signal processing
(e.g. machine learning-based and information-theoretic signal processing),
New and emerging paradigms in statistical signal processing
(e.g. Independent Component Analysis (ICA), kernel-based methods, cognitive signal processing)
MLSP 