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Systems and Intelligence Analysis

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Systems and Intelligence Analysis consists of 70 professionals with a wide range of industry experience and academic backgrounds including operations research, statistics, mathematics, and economics as well as engineering, computer science and the physical sciences. Due to the multidisciplinary nature of the field, we frequently collaborate with specialists and integrate models and results to characterize overall performance of a system.

 

Current Research
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Applying MESA Epidemiological Model to Human Diseases Read more...

Automatic Learning of Probabilistic Causal Models Read more...

Decomposition of Large-Scale Semantic Graphs via an Efficient Communities Algorithm Read more...

Dynamic Data-Driven Event Reconstruction for Atmospheric Releases Read more...

Enhanced Event Extraction from Text via Error-Driven Aggregation Methodologies Read more...

Entity Extractor Aggregation System Read more...

Evaluating Deterrence Measures in Adversary Modeling Read more...

Image Content Engine for Finding Rings of Defects on Optics Read more...

Insider Threat Scenarios and Signatures Read more...

Probabilistic Characterization of Adversary Behavior in Cyber Security Read more...

Proliferation Resistance and Physical Protection of Current Nuclear Fuel Cycles Read more...

Robust Ensemble Classifier Methods for Detection Problems with Unequal and Evolving Error Costs Read more...

Semantic Graph Hierarchical Clustering and Analysis Testbed Read more...

Software Module for Statistical Analysis in Climate-Related Impact Read more...

Statistical Approach to Complex Systems in the Presence of Uncertainty Read more...

Toward Understanding Higher-Adaptive Systems Read more...

Ultra-Scale Tracking in Low-Resolution Image Sequences Read more...



Technical Contact
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  Publications
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Tom Edmunds
(925) 423-8982

 

Maurer, S. M., Ed. (2009) WMD Terrorism: Science and Policy Choices, MIT Press (contributed chapter).

Edwards, W., Miles, R. F., Jr., and von Winterfeldt, D., Eds. (2007) Advances in Decision Analysis, Cambridge University Press (contributed chapter).

Edmunds, T. A. and Bard, J. F. (1991) Algorithms for Nonlinear Bilevel Mathematical Programs, IEEE Transactions on Systems, Man, and Cybernetics, 21: 1, 83–89.

Edmunds, T. A. and Bard, J. F. (1990) Time-Axis Decomposition of Large-Scale Optimal Control Problems, Journal of Optimization Theory and Applications, 67: 2, 259–277.

Edmunds, T. A. and Bard, J. F. (1990) A Decomposition Technique for Discrete Time Optimal Control Problems with an Application to Water Resources Management, Mathematical and Computer Modelling, 13: 1, 61–78.

         
NNSA Department of Energy
Lawrence Livermore National Laboratory
7000 East Avenue • Livermore, CA 94550
Operated by Lawrence Livermore National Security, LLC, for the Department of Energy's National Nuclear Security Administration

 
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