Nathan Danneman

Nathan serves as a technical lead and innovator at LMI. His academic background in quantitative political science, where he studied international conflict processes, trained him to think rigorously about measurement of strategic interactions. Nathan spent the first part of his career focused on uncovering bad cyber actors in big cyber datasets at the Defense Advanced Research Projects Agency, and then at a cybersecurity startup. He served as the chief data scientist at a small contracting firm that tackled complex data science topics in the federal space, such as detecting manipulated images at scale, writing metamodels over cybersecurity tools, and using graph-based methods to increase the precision of cyber detection suites.

At LMI, Nathan uses his broad AI and machine learning background to weigh in across multiple subject matter areas, including predictive maintenance for fleet management, graph-based methods for spatial overdose network descriptions, supply chain risk, portfolio optimization, logistics operations, and human capital measurement and optimization.