Ebrahim Rahmani, a Mechanical Engineer with a Master’s in Aerospace Engineering from Iran University of Science and Technology, is focused on developing sparse sensing methodologies within ENCODING. His research aims to minimize sensor count while maximizing information extraction from systems.

He will:

1. Collect experimental data on ULB semi-industrial furnace using various fuel mixtures and atmospheres.
2. Utilize ML techniques like PCA or Sparse Representation for Reconstruction (SRR) to optimize sensor placement.
3. Integrate this technique with numerical data using Data Assimilation and Kalman filter methodologies.

This approach will create a soft sensor for precise combustion control, offering cost-effective solutions for the industry.