Publications

R. Jones, C. Safta, A. Frankel (2023). Deep learning and multi-level featurization of graph representations of microstructural data. Computational Mechanics.

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R. Wonnacott, D. Ching, J. Chilleri, C. afta, L. Rashkin, T. Reichardt (2023). Industrial PLC Network Modeling and Parameter Identification Using Sensitivity Analysis and Mean Field Variational Inference. Sensors.

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K. Kim, O. Diaz-Ibarra, H. Najm, J. Zador, C. Safta (2022). TChem: A performance portable parallel software toolkit for complex kinetic mechanisms. Computer Physics Communications.

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C. Safta, R. Ghanem, M. Grant, M. Sparapany, H. Najm (2022). Trajectory design via unsupervised probabilistic learning on optimal manifolds. Data-Centric Engineering.

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A. Hegde, E. Weiss, W. Windl, H. Najm, C. Safta (2022). Bayesian calibration of interatomic potentials for binary alloys. Computational Materials Science.

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O. Diaz-Ibarra, K. Kim, C. Safta, J. Zador, H.N. Najm (2021). Using computational singular perturbation as a diagnostic tool in ODE and DAE systems: a case study in heterogeneous catalysis. Combustion Theory and Modelling.

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P. Blonigan, J. Ray, C. Safta (2021). Forecasting Multi-Wave Epidemics Through Bayesian Inference. Archives of Computational Methods in Engineering.

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A.L. Frankel, C. Safta, C. Alleman, R. Jones (2021). Mesh-based Graph Convolutional Neural Networks For Modeling Materials with Microstructure. Journal of Machine Learning for Modeling and Computing.

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K. Lee, J. Ray, C. Safta (2021). The predictive skill of convolutional neural networks models for disease forecasting. PLOS ONE.

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A.A. Gorodetsky, C. Safta, J.D. Jakeman (2021). Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning. Journal of Machine Learning Research.

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Y.T. Lin, J. Neumann, E.F. Miller, R.G. Posner, A. Mallela, C. Safta, J. Ray, G. Thakur, S. Chinthavali, W.S. Hlavacek (2021). Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification, United States. Emerging Infectious Diseases.

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L.P. Swiler, M. Gulian, A.L. Frankel, C. Safta, J.D. Jakeman (2020). A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges. Journal of Machine Learning for Modeling and Computing.

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C. Safta, J. Ray, K. Sargsyan (2020). Characterization of partially observed epidemics through Bayesian inference: Application to COVID-19. Computational Mechanics.

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H. Lu, Q. Shen, J. Che, X Wu, X. Fu, M. Khalil, C. Safta, Y. Huang (2020). Bifidelity Gradient-Based Approach for Nonlinear Well-Logging Inverse Problems. IEEE Journal on Multiscale and Multiphysics Computational Techniques.

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Z.J. Buras, C. Safta, J. Zador, L. Sheps (2019). Simulated production of OH, HO2, CH2O, and CO2 during dilute fuel oxidation can predict 1st-stage ignition delays. Combustion and Flame.

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R.G. Ghanem, C. Soize, C. Safta, X. Huan, G. Lacaze, J.C. Oefelein, H.N. Najm (2019). Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds. Journal of Computational Physics.

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C. Soize, R. Ghanem, C. Safta, X. Huan, Z.P. Vane, J. Oefelein, G. Lacaze, H.N. Najm, Q. Tang, X. Chen (2019). Entropy-based closure for probabilistic learning on manifolds. Journal of Computational Physics.

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C. Soize, R. Ghanem, C. Safta, X. Huan, Z.P. Vane, J.C. Oefelein, G Lacaze, H.N. Najm (2018). Enhancing Model Predictability for a Scramjet Using Probabilistic Learning on Manifolds. AIAA Journal.

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K. Chowdhary, C. Safta, H.N. Najm (2018). Enhancing statistical moment calculations for stochastic Galerkin solutions with Monte Carlo techniques. Journal of Computational Physics.

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M. Vohra, A. Alexanderian, C. Safta, S. Mahadevan (2018). Sensitivity-Driven Adaptive Construction of Reduced-space Surrogates. Journal of Scientific Computing.

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P. Tsilifis, X. Huan, C. Safta, K. Sargsyan, G. Lacaze, J.C. Oefelein, H.N. Najm, R.G. Ghanem (2018). Compressive Sensing Adaptation for Polynomial Chaos Expansions. Journal of Computational Physics.

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M. Lucchesi, H.H. Alzahrani, C. Safta, O.M. Knio (2018). A hybrid, non-split, stiff/RKC, solver for advection–diffusion–reaction equations and its application to low-Mach number combustion. Combustion Theory and Modelling.

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J. Cheng, R.L.-Y. Chen, H.N. Najm, A. Pinar, C. Safta, J.-P. Watson (2018). Chance-Constrained Economic Dispatch with Renewable Energy and Storage. Computational Optimization and Applications.

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F. Rizzi, K. Morris, K. Sargsyan, P. Mycek, C. Safta, O. Le Matre, O.M. Knio, B.J. Debuschere (2018). Exploring the Interplay of Resilience and Energy Consumption for a Task-Based Partial Differential Equations Preconditioner. Parallel Computing.

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X. Huan, C. Safta, K. Sargsyan, Z.P. Vane, G. Lacaze, J.C. Oefelein, H.N. Najm (2018). Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions. SIAM/ASA Journal on Uncertainty Quantification.

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J. Cheng, R.L.-Y. Chen, H.N. Najm, A. Pinar, C. Safta, J.-P. Watson (2018). Distributionally Robust Optimization with Principal Component Analysis. SIAM Journal on Optimization.

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X. Huan, C. Safta, K. Sargsyan, G. Geraci, M.S. Eldred, Z.P. Vane, G. Lacaze, J.C. Oefelein, H.N. Najm (2018). Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations. AIAA Journal.

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P. Mycek, A. Contreras, O. Le Maitre, K. Sargsyan, F. Rizzi, K. Morris, C. Safta, B.J. Debuschere, O.M. Knio (2017). A resilient domain decomposition polynomial chaos solver for uncertain elliptic PDEs. Computer Physics Communications.

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D. Lu, D. Ricciuto, A. Walker, C. Safta, W. Munger (2017). Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods. Biogeosciences.

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F. Rizzi, K. Morris, K. Sargsyan, P. Mycek, C. Safta, O. Le Matre, O. Knio, B.J. Debuschere (2017). Partial differential equations preconditioner resilient to soft and hard faults. The International Journal of High Performance Computing Applications.

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P. Mycek, F. Rizzi, O. Le Maitre, K. Sargsyan, K. Morris, C. Safta, B.J. Debuschere, O.M. Knio (2016). Discrete A Priori Bounds for the Detection of Corrupted PDE Solutions in Exascale Computations. SIAM Journal on Scientific Computing.

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R. Malpica Galassi, M. Valorani, H.N. Najm, C. Safta, M. Khalil, P.P. Ciottoli (2016). Chemical model reduction under uncertainty. Combustion and Flame.

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C. Safta, R.L.-Y. Chen, H.N. Najm, A. Pinar, J.-P. Watson (2016). Efficient Uncertainty Quantification in Stochastic Economic Dispatch. IEEE Transactions on Power Systems.

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M. Khalil, K. Chowdhary, C. Safta, K. Sargsyan, H.N. Najm (2016). Inference of reaction rate parameters based on summary statistics from experiments. Proceedings of the Combustion Institute.

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C. Safta, M. Blaylock, J. Templeton, S. Domino, K. Sargsyan, H.N. Najm (2016). Uncertainty quantification in LES of channel flow. International Journal for Numerical Methods in Fluids.

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K. Sargsyan, F. Rizzi, P. Mycek, C. Safta, K. Morris, H.N. Najm, O. Le Maitre, O. Knio, B. Debusschere (2015). Fault Resilient Domain Decomposition Preconditioner for PDEs. SIAM Journal on Scientific Computing.

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C. Safta, D. Ricciuto, K. Sargsyan, D. Debusschere, H.N. Najm, M. Williams, P.E. Thornton (2015). Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model. Geoscientific Model Development.

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C. Safta, K. Sargsyan, D. Debusschere, H.N. Najm (2014). Hybrid discrete/continuum algorithms for stochastic reaction networks. Journal of Computational Physics.

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C. Safta, K. Sargsyan, H.N. Najm, K. Chowdhary, B. Debusschere, L.P. Swiler, M.S. Eldred (2014). Probabilistic Methods for Sensitivity Analysis and Calibration in the NASA Challenge Problem. Journal of Aerospace Information Systems.

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K.S. Kedia, C. Safta, J. Ray, H.N. Najm, A.F. Ghoniem (2014). A second-order coupled immersed boundary-SAMR construction for chemically reacting flow over a heat-conducting Cartesian grid-conforming solid. Journal of Computational Physics.

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K. Sargsyan, C. Safta, H.N. Najm, B.J. Debusschere, D. Ricciuto, P. Thornton (2013). Dimensionality Reduction for Complex Models via Bayesian Compressive Sensing. International Journal for Uncertainty Quantification.

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H.N. Najm, R.D. Berry, C. Safta, K. Sargsyan, B.J. Debusschere (2013). Data-free Inference of Uncertain Parameters in Chemical Models. International Journal for Uncertainty Quantification.

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