
Timothy Klett
- Department Manager, Infrastructure Resilience Analysis
- Idaho National Laboratory
Tim Klett is the Manager of the Infrastructure Resilience Analysis department within Critical Infrastructure Security & Resilience division in the National & Homeland Security directorate. Mr. Klett oversees a multi-disciplinary team delivering holistic, cyber-physical critical infrastructure (CI) analysis to strengthen security, resilience, and mission preparedness across all sixteen critical infrastructure sectors. He guides the development and implementation of novel analytical capabilities that bridge theory and practice to provide innovative, accurate, and timely decision-support to partners addressing national infrastructure challenges. Areas of focus for his department include infrastructure studies, emergency management support, CI data visualization, cyber applications, intelligence-informed approaches, modeling, and large-scale CI research facilities. Mr. Klett has 24 years of experience working within the National Laboratory complex, with a focus on critical infrastructure protection and technology solutions for the Department of Energy (DOE), the Department of Homeland Security (DHS), and the Department of Defense (DOD). Mr. Klett’s experience includes the development of methodologies and technologies that facilitate the collection, analysis, and dissemination of data on CI risk to all hazards; research in CI dependencies and interdependencies; and associating Software Bills of Material (SBOMs) with CI and understanding their impacts.
Tim holds an M.S. degree in Computer Science from the Illinois Institute of Technology in 2004 and is a Certified Information Systems Security Professional (CISSP). He is currently pursuing a Ph.D. in Computer Science from the University of Idaho.
Sessions
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Modeling and Methodology Around Incident Mitigation & Emergency Management
Predicting how threats can impact business continuity of critical assets can be of major benefit for planning resiliency or emergency response. This affects both financial and resource planning. So what are the latest roles and assessments in modeling and methodology? What role can machine learning and AI play in building more accurate predictions and what measures can be put in place to mitigate risk?