New York University is a major private research university with global campuses and strengths in computer science, medicine, and public policy. It fosters boundary-pushing research in a vibrant urban setting. We have worked with New York University on deep learning and multimodal AI research. Our joint efforts include developing generative adversarial networks and robust pretraining techniques to improve performance on complex visual and language tasks. Please read about our latest news and collaborative publications with New York University.

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Resilient DFOS Placement Strategy for Power Grid Monitoring: Integrating Fiber and Power Network Dependencies

We propose a novel Distributed Fiber Optic Sensing (DFOS) placement strategy tailored to the evolving needs of modern power grids, where fiber cables serve dual purposes: communication and real-time sensing. Our approach integrates a heuristic algorithm, PURE (Power Source-aware Route Exploration), with Integer Linear Programming (ILP) to optimize DFOS placement while addressing power supply constraints. The strategy ensures resilient monitoring across diverse grid scenarios by prioritizing observability during outages and leveraging advancements in fiber infrastructure deployment. Case studies demonstrate the effectiveness of our methodology in maintaining power grid resilience while minimizing deployment costs.