I am a member of the Applied Statistics Group at Lawrence Livermore National Laboratory (LLNL), where I have worked since completing a PhD in statistics at Penn State University in 2016. My work spans a wide range of applications, including stockpile stewardship, nonproliferation, space domain awareness, materials science, reliability, and software testing. Recent projects include multiple space object tracking, satellite collision probability estimation, equation of state prediction, and Bayesian calibration of material strength models.
I am also the Director of the Data Science Institute Consulting Service and the Open Data Initiative at LLNL, and have managed projects and collaborations with industry, academia, and government partners.
John Tukey said that "The best thing about being a statistician is that you get to play in everyone’s sandbox", and I have found this to be very true at LLNL.
Ph.D., Statistics, Pennsylvania State University, 2016
M.Sc., Statistics, Pennsylvania State University, 2014
B.Sc., Mathematics, Michigan State University, 2010
Hallas, K. L., De Jesus, M., Wu, C. J., Li, J., Bernstein, J., & Myint, P. C. (2026). Toward Mapping Multiphase Multicomponent Mixtures with Neural Networks. Data Science in Science, 5(1), 2631836.
Foster, M., Steirer, K., Bernstein, J., Herynk, M., & Lamberson, L. (2025). Influence of pore geometry and distribution on buckling under micro computed tomography. Polymer, 128434.
Muyskens, A. L., Goumiri, I. R., Priest, B. W., Schneider, M. D., Armstrong, R. E., Bernstein, J., & Dana, R. (2022). Star–galaxy image separation with computationally efficient Gaussian process classification. The Astronomical Journal, 163(4), 148.
Rivera, D., Bernstein, J., Schmidt, K., Muyskens, A., Nelms, M., Barton, N., ... & Florando, J. (2022). Bayesian calibration of strength model parameters from Taylor impact data. Computational Materials Science, 210, 110999.
Bernstein, J. (2021). Probabilistic data association for orbital-element estimation using multistage expectation–maximization. Journal of Aerospace Information Systems, 18(5), 250-268.
Bernstein, J., Filippov, A., Schneider, M., & Miller, C. (2021). Quantifying Uncertainty in All-to-All Estimates of Space Object Conjunction Probabilities using U-Statistics (No. LLNL-TR-827439). Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States).
Schunck, N., Quinlan, K. R., & Bernstein, J. (2020). A Bayesian analysis of nuclear deformation properties with Skyrme energy functionals. Journal of Physics G: Nuclear and Particle Physics, 47(10), 104002.
Bernstein, J., & Fricks, J. (2016). Analysis of single particle diffusion with transient binding using particle filtering. Journal of theoretical biology, 401, 109-121.
