Dr. Carleton Coffrin is a staff scientist at Los Alamos National Laboratory in the Advanced Network Science Initiative, an interdisciplinary team that investigates the application of emerging optimization and machine learning methods to problems in critical infrastructure systems. Dr. Coffrin’s work focuses on developing novel optimization methods for network design, operation, and restoration for power networks. His work on power system optimization has been recognized by the IEEE PES 2014 Optimal Power Flow Competition, the ARPA-e 2020 Grid Optimization Competition and Los Alamos National Laboratory's Early Career Researcher award. Dr. Coffrin is also exploring how novel computing devices, such as quantum computers and memristor networks, can improve the next generation of optimization algorithms. Dr. Coffrin received his Ph.D. in Computer Science from Brown University in 2012, under the supervision of Pascal Van Hentenryck.
The design, operation and resilience of critical infrastructure networks plays a foundational role in modern society. One open question is how artificial intelligence can provide decision support to maintain and adapt critical infrastructures to a changing world. This talk provides an overview of InfrastructureModels, a software foundation developed at Los Alamos National Laboratory for critical infrastructures analysis and optimization to help explore this question.