Journal Publications and Selected Technical Reports and Conference Proceedings
For full citations, see the CV tab. For a complete publication record, visit my Google Scholar page.
2025
S. Taverniers, S. Korneev, C. Somarakis, M. Behandish, and A.J. Lew.
2023
A multi-physics compiler for generating numerical solvers from differential equations
J.T. Maxwell III, M. Behandish, and S. Taverniers.
Inverse asymptotic treatment: Capturing discontinuities in fluid flows via equation modification
S. Mirjalili, S. Taverniers, H. Collis, M. Behandish, and A. Mani.
2022
Accelerating part-scale simulation in liquid metal jet additive manufacturing via operator learning
S. Taverniers, S. Korneev, K.M. Pietrzyk, and M. Behandish.
2021
S. Mirjalili, S. Taverniers, H. Collis, M. Behandish, and A. Mani.
Mutual Information for explainable deep learning of multiscale systems
S. Taverniers, E.J. Hall, M.A. Katsoulakis, and D.M. Tartakovsky.
GINNs: Graph-Informed Neural Networks for Multiscale Physics
E.J. Hall, S. Taverniers, M.A. Katsoulakis, and D.M. Tartakovsky.
2020
Accelerated multilevel Monte Carlo with kernelābased smoothing and Latinized stratification
S. Taverniers, S.B.M. Bosma, and D.M. Tartakovsky.
Estimation of distributions via multilevel Monte Carlo with stratified sampling
S. Taverniers and D.M. Tartakovsky.
2019
S. Taverniers, H.S. Udaykumar, and G.B. Jacobs.
Multi-scale Simulation of the Interaction of a Shock Wave and a Cloud of Particles
S. Taverniers, G.B. Jacobs, V. Fountoulakis, O. Sen and H.S. Udaykumar.
2017
S. Taverniers and D.M. Tartakovsky.
A tightly-coupled domain-decomposition approach for highly nonlinear stochastic multiphysics systems
S. Taverniers and D.M. Tartakovsky.
2016
Conservative tightly-coupled simulations of stochastic multiscale systems
S. Taverniers, A.Y. Pigarov, and D.M. Tartakovsky.
2015
Physics-based statistical learning approach to mesoscopic model selection
S. Taverniers, T.S. Haut, K. Barros, F.J. Alexander, and T. Lookman.
2014
Noise propagation in hybrid models of nonlinear systems: The Ginzburg-Landau equation
S. Taverniers, F.J. Alexander, and D.M. Tartakovsky.