The general research question we would like to address is whether we can adopt learning-based approaches for the evaluation of tumor growth models. Particularly, we aim to test the methodological advances in parametric inference, relying on deep learning techniques. Besides, we will explore a parallel research line of expressing the whole modeling approach - the tumor simulation and inference tasks - in neural network language. The methods will be validated under models of various biophysical complexity on several retrospective brain tumor studies.

Gained expertise. Computational physiology, deep learning, statistical inference.

Prerequisites. A few self-written lines of code (Python or C++), moderate ability to understand math.