In our group we conduct research on various aspects of Machine Learning, mainly based on neural network with an aim of improving the accuracy of our simulations. One our latest research in collaboration with Dr Yasser Mahmoudi-Larimi is in developing tensor-basis neural network (TBNN) in training low-cost models by using reliable high-fidelity computational methods. In addition, we are using some of the latest machine learning algorithms such as Physics-informed neural networks (PINNs) and SciANN. The latter is a high-level artificial neural networks API, written in Python and it is developed with a focus on enabling fast experimentation with different networks architectures and with emphasis on scientific computations, physics informed deep learning, and inversion.