Research

My major contribution are in the area of process control, lies in the process modeling and development of control tools using artificial neural networks (ANN). This covers from the fundamental aspects of system modeling using the emerging ANN technology focusing on the linear chemical system to a more advanced process modeling and control.

My research has evolved from modeling system through single ANN to multiple neural networks (MNN) which has become one of the latest tools in process modeling, that has been recently moving towards modeling nonlinear system, multiple input and multiple output (MIMO) system and also model based control (MBC) utilising both ANN and MNN.

  1. Research grant in progress.

  • Direct Biodiesel Synthesis from Microalgae Through in Situ Transesterification using Homogeneous Catalyst ( 2022)

  • Multivariate data analysis in solving highly dynamic environmental quality data ( 2023)

  • Elicitation Of Autoencoder Artificial Intelligence (AI) Capability In Elucidating The Dynamics Complexities Of Time-Varying Process( 2022-2025).