Research

Research

Researcher Profile

Research Centre: 

Centre for Multimodal Signal Processing

Principal Investigator: Assoc. Prof. Eur Ing Dr Lai Weng Kin
Faculty: Faculty of Engineering and Technology (FOET)

Types of Grant: MyGrants- FRGS Cycle 01/2014
Project Title : Research into a Machine Vision Framework to Characterise the Mechanical Stability of Colloidal Liquids in the Processing of cis-1,4 Polyisoprene
Approval Date : 09.06.14
Duration : 01.07.14 - 30.06.16 (2 years) (extended to 31.12.16) 
Approved Budget : RM 123,000.00

Major of Study/Specialization: Computer vision, Soft computing
Area of Interest: Artificial Neural Networks, Swarm Intelligence (ABC, ACO, PSO), Image Processing, Intelligent Systems

Research Centre: 

Centre for Multimodal Signal Processing

Principal Investigator : Dr Goh Kam Meng 
Faculty : Faculty of Engineering and Technology (FOET)
Types of Grant : MyGrants- FRGS Cycle 01/2016
Project Title : A High-level Head Pose Invariant Spatio-Temporal Representation for Subtle Expression Extraction and Analysis Framework
Approval Date : 08.07.16
Duration : 01.08.16 - 31.07.18 (2 years)
Approved Budget : RM 53,600.00

Major of Study/Specialization: Electrical and Electronic Engineering
Area of Interest: Image Processing, Computer Vision, and Machine Learning (AI)

Research Centre: 

Centre for Advanced Materials

Principal Investigator : Dr. Ho Mui Yen

Faculty : Faculty of Engineering and technology (FOET)

Types of Grant : TAR UC Internal Research Grant (UC/I/G2018-00025)

Project Title : Graphene-based ternary composite electrodes for non-enzymatic glucose sensing applications

Approval Date : 29th March 2018

Duration : 01.04.18 - 31.03.20 (2 years)

Approved Budget : RM 73,600.00

Major of Study/Specialization: Corrosion Control; Advanced Materials
Area of Interest: Corrosion inhibitor; Nanostructured coating; Nanomaterials in Energy Storage Devices

Research Centre: 

Centre for Multimodal Signal Processing

Principal investigator: Dr. Raymond Wong Jee Keen

Faculty: faculty of Engineering and Technology (FOET)

Types of grant: TARUC Internal Research Grant

Project Title: Noise-resilient incipient Fault Prognostication of High Voltage Insulation Using Combined Partial Discharge Analysis and Optimized Artificial Intelligence Framework

Approval date:1 Apr 2018

Duration: 2 Years

Approved Budget:RM 61,400

Major of Study/Specialization: Partial Discharge, Pattern Recognition
Area of Interest: Artificial Intelligence, Machine Learning, Dielectrics and Electrical Insulation

    

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