Matthew J. Hoffman


Matthew J. Hoffman

Senior Member of Technical Staff

Contact Information

Matthew J. Hoffman / 505-844-4195


Matthew Hoffman has over 15 years of experience in project leadership and in simulation, optimization and data analytics of complex systems for national security. He received his MS in applied mathematics from the New Mexico Institute of Mining and Technology, where his work on hybrid (continuous-discrete) dynamical systems involved extensive improvements to a power systems dynamics research code. At Sandia he has focused on applied optimization research, and in 2015 he was named an INFORMS Franz Edelman Laureate for leading work “representative of the best applications of analytical decision making in the world” optimizing multi-billion-dollar strategic investment decisions for the US Army. For Sandia’s EMP Grand Challenge he leads work (1) characterizing cascading failure modes of the power grid in response to high-altitude electromagnetic pulse and (2) optimizing the post-cascade stability and operating state of the grid prior to restoration from severe emergencies. He is also the PI of a new R&D project on stochastic resilience planning optimization for the grid and other hybrid dynamical systems.


  • Masters of Science, Applied Mathematics, New Mexico Institute of Mining and Technology, 2007
  • Bachelors of Science, Applied Mathematics

U.S. Patents

“Seeding and Healing a Genetic Algorithm to Mitigate Irreducible Complexity,” US16596866, patent pending

“Systems and Methods for Integrating Fleet Composition and Component System Design,” US16900575, patent pending

“Methods, Systems and Computer Program Products for Determining the Sensitivity of Systems of Systems,” Provisional patent SD14162/S147240

Google Scholar:

Matthew J. Hoffman

Key Publications

  • Pierre, B. J., Guttromson, R. T., Eddy, J. P., et al. (2020) A Framework to Evaluate Grid Consequences from High Altitude EMP Events. HEART 2020 (accepted).
  • Waddell, L. A., Gauthier, J. H., Hoffman, M. J. et al. (2020) Estimating the Quality of an Optimization as the Fraction of the Surpassed Solution Space: the SMORS Method. Operations Research Letters (submitted).
  • Hoffman, M. J., Nelson, A. M., Arguello, B., Pierre, B. J., Guttromson, R. T. (2020) Stability Margin Optimization for Wide-Area Power System Emergencies. IEEE Transactions on Power Systems (in preparation).
  • Hoffman, M. J., Bussell, S., Brown, N. J. (2020) A minimally supervised event detection method. Statistical Analysis and Data Mining (in preparation).