The symposium provided the opportunity for early career STEM researchers to present their research, receive feedback, and explore the possibilities of turning research to enterprise.
At the symposium, Bamidele presented his research on Volumetric Reconstruction of Burner Flames through Deep Learning, which is supervised by Dr Md Moinul Hossain, Lecturer in Electronic Engineering, and Dr Gang Lu, Reader in Electronic Instrumentation.
Bamidele says: ‘Volumetric tomography is a powerful technique for combustion diagnostics due to its capacity to visualize flame structures in three-dimension (3-D). In this research, we are working on implementing a deep learning-based algorithm for the 3-D reconstruction of burner flames. The main purpose is to improve the 3D reconstruction speed and performance of a deep learning-based 3D rapid ﬂame monitoring solution’.
‘The relevance of this research is that the results from the work could help in providing a combustion diagnostics solution for improving combustion efficiency and reducing pollutant emissions using deep learning’.