The Los Alamos National Laboratory’s Advanced Network Science Initiative (ANSI) is an interdisciplinary initiative that enables fundamental and applied research to address long-term challenges in critical infrastructure design, operation, and security. The primary philosophy of ANSI is that combining insights from Theoretical Physics, Applied Mathematics, Computer Science, and Applied Engineering can result in novel computational methods that address a variety of emerging challenges in infrastructure networks.
ANSI is always looking to motivated and enthusiastic persons to contribute to this research through postdoc and student appointments. Interested parties are encouraged to inquire at email@example.com. Current open apointments include,
To help motivate and inspire novel computational methods, ANSI studies a variety of challenging problems in critical infrastructure networks, such as Analysis of Extreme Events, Network-base Machine Learning and Data Analytics, Control and Optimization Under Uncertainty, Interdependencies Across Multiple Networks, and The Design of Resilient Networks. ANSI has strong expertise in power systems and natural gas systems and is currently building an expertise in potable water and cyber-physical systems.
To address these challenging application areas, ANSI contributes to basic research in a variety of areas including, Statistical Physics / Complex Networks, Machine Learning / Graphical Models, Control Theory, Discrete and Nonconvex Optimization, and Graph Theory. ANSI always strives for research excellence and targets competitive publication venues, such as Science Advances, Proceedings of the National Academy of Sciences, Proceedings of the IEEE, Operations Research, Transactions on Power Systems, Proceedings of Neural Information Processing Systems (NIPS), Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI), and Proceedings of the IEEE Conference on Decision and Control (CDC), to name a few. A complete profile of ANSI’s publications is available here.
ARPA-e Grid Optimization Competition: Los Alamos scientists take top prizes in national competition to help improve electrical grid
Quantum Annealing Hardware Evaluation: Software evaluates qubits, characterizes noise in quantum annealers (technical report)
D-Wave Optimization Verification: a LANL STE Highlights article on how LANL-ANSI scientists leveraged state-of-the-art optimization algoirhtms to verify the solution quality of a D-Wave quantum annealer. (technical report)