The organizing theme of this project is to use AI to enable all the players in a particular academic institituion better to leverage available institutional resources - effectively to allow effect ivetracking by the institutions administrators track progress by indibidul students and match to local market needs - thereby enabling a better match by the local universities to area needs: eg energy, food, disease and transportation - empowering students, faculty and administrators to maximize the outcomes from the large investments by universities in PhD programs. The effort of the project is to develop semi-automated methods for data curation in higher education - and, in turn, using the data to build novel algorithms using neural network architectures and techniques to predict career outcomes of PhD graduates.
