We are primarily focused on mechanics and physics of micro-structurally heterogeneous materials. Micro-mechanical and coupled multi-scale models are developed to predict complex behavior of multi-phase materials, with an emphasis on (bio-)composites. To increase the predictive capability and to enhance the computational efficiency of the models, machine learning techniques, particularly artificial neural networks, are used. As an additional line of research activities, we also work, in collaboration with other research groups, on bio-mechanics problems. Physics-based models are employed together with machine learning techniques to develop computationally enhanced bio-mechanical models.