Senior Technical Advisor
Senior Technical Advisor


Aaron Luttman is an advisor in Physical Detection Systems and Deployment Division at PNNL, where he operates at the nexus of bringing the latest developments in mathematics and data science to concrete national security applications, establishing and leading diverse and collaborative research teams, and engaging government sponsors to grow our mission.

Luttman has worked in industry, academia, and the Department of Energy (DOE) enterprise, with research spanning machine learning, computer vision, multisensor networks, landscape ecology, ocean flow dynamics, nuclear fusion, mathematical models for novel measurement systems, and commutative Banach algebras. He is also active in the broader scientific community. He was a featured mathematician in the book 101 Careers in Mathematics3rd Ed., having delivered more than 100 invited and conference research presentations. Luttman has served as a distinguished lecturer for the Mathematical Association of America (MAA) and visiting lecturer for the Society of Industrial and Applied Mathematics. He has published more than 40 peer-reviewed journal articles and is an industrial partner to the Preparations for Industrial Careers in Mathematics program. Luttman serves as an officer of the MAA’s Special Interest Group on the mathematics of business, industry, and government. He also serves on the industrial advisory board to the graduate program in computational mathematics at Embry-Riddle Aeronautical University.

Research Interest

  • Assured artificial intelligence and machine learning
  • Data science
  • Inverse problems
  • Imaging science

Disciplines and Skills

  • Image processing
  • Image segmentation
  • Mathematical modeling
  • Mathematical optimization
  • Nuclear nonproliferation


  • PhD in mathematics, University of Montana
  • MS in math science, University of Minnesota-Twin Cities
  • BS in math science, Purdue University

Affiliations and Professional Service

  • Applied Mathematics Education Committee, Society of Industrial and Applied Mathematics (SIAM)
  • Special Interest Group on the Mathematics of Business, Industry, and Government, Mathematical Association of America
  • SIAM Pacific Northwest Section Meeting Organizing Committee
  • Industrial Advisory Board, Computational Mathematics Program, Embry-Riddle Aeronautical University

Awards and Recognitions

  • Society of Industrial and Applied Mathematics Visiting Lecturer, 2018-present
  • Featured Mathematician in the book 101 Careers in Mathematics, 3rd Ed., 2019
  • Mathematical Association of America Distinguished Lecturer, 2018
  • President’s Distinguished Performance Award for Excellence in Scientific Leadership, Nevada National Security Site, 2018
  • 4 Defense Programs Awards of Excellence for contributions to the National Nuclear Security Administration, 2018, 2016
  • Outstanding New Teacher Award, Clarkson University, 2010


Adams, J., M. Morzfeld, K. Joyce, M. Howard, and A. Luttman, A Blocking Scheme for Dimension Robust Gibbs Sampling in Large-scale Image Deblurring, Inverse Prob. Sci Engineering, 2021, doi:10.1080/17415977.2021.1880398.

Catenacci, J., D. Constantino, B. Gall, and A. Luttman, Tomographic Reconstruction of the Neutron Time-Energy Spectrum from a Dense Plasma Focus, IEEE Trans. Plasma Sci., 48 (2020), no. 9, 3135-3143.

Gehring, A., J. Zier, P. Flores, T. Haines, K. Joyce, A. Luttman, A. S. Richardson, and J. Smith, Reduction of radiographic spot size with dual diameter sub-mm rods, Bulletin of the American Physical Society, 64 (2019), no. 8.

Gastleum, Z., B. Goldblum, T. Shead, C. Stewart, K. Miller, and A. Luttman, Integrating Physical and Informational Sensing to Support Nonproliferation Assessments of Nuclear-Related Facilities, Proceedings of the INMM Annual Meeting, 2019.

K. Joyce, Bardsley, J. M., and A. Luttman, Point Spread Function Estimation in X-ray Imaging with Partially Collapsed Gibbs Sampling, SIAM J. Sci. Comput., 40 (2018), no. 3, B766-B787.

Udagedara, I. G., B. Helenbrook, A. Luttman, and J. Catenacci, Probabilistic Reduced Order Modeling using a Bayesian Approach, Amer. J. Math. Comput. Sci., 3 (2018), no. 2, 50-61.

Bennett, N., et al, and A. Luttman, Development of the Dense Plasma Focus for Short-Pulse Applications, Physics of Plasmas, 24, 012720 (2017).

Bennett, N., et al, and A. Luttman, Kinetic Simulations of Gas Breakdown in Dense Plasma Focus, Physics of Plasmas, 24, 062705 (2017).

Blair, J., A. Luttman, and E. Machorro, A Generalized Peano Kernel Theorem for Distributions of Exponential Decay, J. Math. Anal. Appl., 433 (2016), 622-641.

Fowler, M., M. Howard, A. Luttman, S. E. Mitchell, and T. J. Webb, A Stochastic Approach to Quantifying the Blur with Uncertainty for High-energy X-ray Imaging Systems, Inverse Probl. Sci. Engineering, 24 (2016), 353-371.

Howard, M., M. Fowler, A. Luttman, S. Mitchell, and M. Hock, Bayesian Abel Inversion in Quantitative X-Ray Radiography, SIAM. J. Sci. Comput., 38 (2016), B396-B413. (This article was featured as the June 2016, SIAM Nugget Bytes article.)