deep learning for multi domain engineering systems

Develop machine learning techniques and models to fuse knowledge (mathematical model or expert beliefs) and data from different engineering domains (vibration, thermal, engine performance, etc.)
· Train these models on real data to produce predictions of complex systems, such as gas turbines and hybrid electric propulsion systems.
· Using machine learning techniques to incorporate new sources of maintenance data, such as 3D component scans and visual imaging, to better understand system condition.