albert6Albert Boulanger leads the Smart-X {Cities, Buildings, Grids} Group at the Center for Computational Learning Systems (CCLS) at Columbia University.

Albert Boulanger (M.S. CS Univ. of Illinois 1983) has been at Columbia University since 1994 and is Senior Staff Associate with CCLS. Prior to that, Albert was a scientist at Bolt, Beranek, and Newman. Albert has played multiple technical and oversight roles in several Con Edison projects using machine learning. 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 in 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. Other Smart-X projects include using machine learning for optimizing charging of electric delivery trucks and efficient intelligent energy management of large NYC buildings. He is currently doing a cost vs. benefit analysis using causal inference of Con Edison programs concerning their secondary distribution networks and developing image analysis tools for thermal imaging inspections of underground structures for Con Edison.