Albert Boulanger (M.S. CS Univ. of Illinois 1983) has been at CU since 1994 and is Senior Staff Associate with the Center for Computational Learning Systems (CCLS) of Columbia University. Prior to that, Albert was a research scientist at Bolt, Beranek and Newman. Albert has played multiple technical and oversight roles in several Con Edison projects while at Columbia. He is valued for his ability to maintain a systems view of all the facets of large projects. His expertise includes systems integration, expert and knowledge-based systems, machine learning and pattern recognition -- including the interface between numerical and symbolic algorithms, parallel computing, pattern recognition applied to time-lapse seismic data, computer representations of complex scientific and engineering objects, visualization, distributed systems and interoperability. Since 2005, Albert has applied machine learning to studying failure patterns of electric power distribution feeders and their components for Con Edison. More recently Albert was involved a Dept. of Energy funded Con Edison-led Smart Grid project to apply Dynamic Treatment Regimes to formulate optimized repair policies of power distribution components and another Smart Grid project to use Approximate Dynamic Programming for optimizing load curtailment decisions in distribution networks. He currently is involved in using machine learning for optimizing charging of electric delivery trucks and efficient intelligent energy management of large NYC buildings.