Fully Funded PhD Position in Data-Driven Computational Sensing and Imaging
Summary of PhD Program:
This project will consider a range of algorithmic and machine learning technologies including: low rank models and/or auto-encoder type architectures to identify low dimensional data representations; physics-informed and physics aware neural networks that ensure the machine learning solutions adhere to necessary physics within the sensing problem; machine learning solutions targeted reducing computation or processing time; robustness to noise, outliers and adversarial attacks; and Bayesian and variational architectures that can provide uncertainty quantification.
