Kazeem Alli
Optimising batch/semi-batch processes using data-driven concepts.
Email: k.alli2@ncl.ac.uk
Project title
Modelling and optimisation of batch/semi-batch processes with extreme learning machine and recursive learning technique
Supervisors
Project description
This project explores using data-driven concepts to model and optimise nonlinear systems.
The data-driven concept uses statistical theories and machine learning to establish process performances. It monitors the progress of preset operating conditions for optimisation purposes. It also provides generalisation in predicting unforeseen circumstances.
We don't need detailed knowledge of the process operation. But we do need past historical data. If there is enough historical data, we can establish a data-driven model of the process with optimisation. This model will use machine learning and statistical theories conceptualisation.
Interests
Process control, data science, process intensification, bioinformatics and bio-renewable/renewable energy.
Qualifications
BSc, MSc in Chemical Engineering