2023
- R. Jones, C. Safta, A. Frankel, Deep learning and multi-level featurization of graph representations of microstructural data, Computational Mechanics (2023).
- K. Kim, O. Díaz-Ibarra, H. Najm, J. Zádor, C. Safta, TChem: A performance portable parallel software toolkit for complex kinetic mechanisms, Computer Physics Communications, (2023).
- R. Wonnacott, D. Ching, J. Chilleri, C. Safta, L. Rashkin, T. Reichardt, Industrial PLC Network Modeling and Parameter Identification Using Sensitivity Analysis and Mean Field Variational Inference, Sensors (2023).
2022
- O. Díaz-Ibarra, K. Kim, C. Safta, J. Zádor, H. Najm, Using computational singular perturbation as a diagnostic tool in ODE and DAE systems: a case study in heterogeneous catalysis, Combustion Theory and Modelling (2022).
- A. Frankel, C. Safta, C. Alleman, R. Jones, Mesh-based Graph Convolutional Neural Networks for Modeling Materials with Microstructure, Journal of Machine Learning for Modeling and Computing (2022).
- C. Safta, R. Ghanem, M. Grant, M. Sparapany, H.N. Najm, Trajectory design via unsupervised probabilistic learning on optimal manifolds. Data-Centric Engineering (2022).
- A.A. Gorodetsky, C. Safta, J.D. Jakeman, Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning. Journal of Machine Learning Research (2022).
- A. Hegde, E. Weiss, W. Windl, H. Najm, C. Safta, Bayesian calibration of interatomic potentials for binary alloys. Computational Materials Science (2022).
2021
- O. Diaz-Ibarra, K. Kim, C. Safta, J. Zador, H.N. Najm, Using computational singular perturbation as a diagnostic tool in ODE and DAE systems: a case study in heterogeneous catalysis. Combustion Theory and Modelling (2021).
- P. Blonigan, J. Ray, C. Safta, Forecasting Multi-Wave Epidemics Through Bayesian Inference. Archives of Computational Methods in Engineering (2021).
- A.L. Frankel, C. Safta, C. Alleman, R. Jones, Mesh-based Graph Convolutional Neural Networks For Modeling Materials with Microstructure. Journal of Machine Learning for Modeling and Computing (2021).
- K. Lee, J. Ray, C. Safta, The predictive skill of convolutional neural networks models for disease forecasting. PLOS ONE (2021).
- Y.T. Lin, J. Neumann, E.F. Miller, R.G. Posner, A. Mallela, C. Safta, J. Ray, G. Thakur, S. Chinthavali, W.S. Hlavacek, “Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification”, Emerging Infectious Diseases (2021).
2020
- L.P. Swiler, M. Gulian, A.L. Frankel, C. Safta, J.D. Jakeman, “A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges”, Journal of Machine Learning for Modeling and Computing (2020).
- C. Safta, J. Ray, K. Sargsyan, “Characterization of partially observed epidemics through Bayesian inference: application to COVID-19”, Computational Mechanics (2020).
- H. Lu, Q. Shen, J. Chen, X. Wu, X. Fu, M. Khalil, C. Safta, Y. Huang, “Bifidelity Gradient-Based Approach for Nonlinear Well-Logging Inverse Problems”, IEEE Journal on Multiscale and Multiphysics Computational Techniques (2020).
- Z.J. Buras, C. Safta, J. Zador, L. Sheps, “Simulated Production of OH, HO2, CH2O, and CO2 During Dilute Fuel Oxidation Can Predict 1st-Stage Ignition Delays”, Combustion and Flame (2020).
2019
- R.G. Ghanem, C. Soize, C. Safta, X. Huan, G. Lacaze, J.C. Oefelein, and H.N. Najm, “Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds”, Journal of Computational Physics (2019).
- M. Lucchesi, H.H. Alzahrani, C. Safta, O. M. Knio, “A hybrid, non-split, stiff/RKC, solver for advection-diffusion-reaction equations and its application to low-Mach number combustion”, Combustion Theory and Modelling (2019).
- C. Soize, R.G. Ghanem, C. Safta, X. Huan, Z.P. Vane, J.C. Oefelein, G. Lacaze, and H.N. Najm, Q. Tang, X. Chen, “Entropy-based closure for probabilistic learning on manifolds”, Journal of Computational Physics (2019).
- P. Tsilifis, X. Huan, C. Safta, K. Sargsyan, G. Lacaze, J.C. Oefelein, H.N.Najm, R.G. Ghanem, “Compressive Sensing Adaptation for Polynomial Chaos Expansions”, Journal of Computational Physics (2019).
- M. Vohra, A. Alexanderian, C. Safta, S. Mahadevan, “Sensitivity-Driven Adaptive Construction of Reduced-space Surrogates”, Journal of Scientific Computing (2019).
- C. Soize, R.G. Ghanem, C. Safta, X. Huan, Z.P. Vane, J.C. Oefelein, G. Lacaze, and H.N. Najm, “Enhancing Model Predictability for a Scramjet Using Probabilistic Learning on Manifolds”, AIAA Journal (2019).
2018
- K. Chowdhary, C. Safta, and H.N. Najm, “Enhancing Statistical Moment Calculations for Stochastic Galerkin Solutions with Monte Carlo Techniques”, Journal of Computational Physics (2018).
- X. Huan, C. Safta, K. Sargsyan, Z. Vane, G. Lacaze, J. Oefelein, and H.N. Najm, “Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions”, SIAM/ASA Journal on Uncertainty Quantification (2018).
- J. Cheng, R.L.-Y. Chen, H.N. Najm, A. Pinar, C. Safta, J.-P. Watson, “Distributionally Robust Optimization with Principal Component Analysis”, SIAM Journal on Optimization (2018).
- J. Cheng, R.L.-Y. Chen, H.N. Najm, A. Pinar, C. Safta, J.-P. Watson, “Chance-constrained economic dispatch with renewable energy and storage”, Computational Optimization and Applications (2018).
- X. Huan, C. Safta, K. Sargsyan, G. Geraci, M.S. Eldred, Z. Vane, G. Lacaze, J. Oefelein, and H.N. Najm, “Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scramjet Computations”, AIAA Journal (2018).
2017
- D. Lu, D. Ricciuto, A. Walker, C. Safta, W. Munger, “Bayesian calibration of terrestrial ecosystem models: a study of advanced Markov chain Monte Carlo methods”, Biogeosciences (2017).
- R. Malpica Galassi, M. Valorani, H.N. Najm, C. Safta, M. Khalil, P.P. Ciottoli, “Chemical model reduction under uncertainty”, Combustion and Flame (2017).
- F. Rizzi, K. Morris, K. Sargsyan, P. Mycek, C. Safta, O. Le Maître, O. Knio, B. Debusschere, “Exploring the interplay of resilience and energy consumption for a task-based partial differential equations preconditioner”, Parallel Computing (2017).
- P. Mycek, A. Contreras, O. Le Maître, K. Sargsyan, F. Rizzi, K. Morris, C. Safta, B. Debusschere, O. Knio, “A resilient domain decomposition polynomial chaos solver for uncertain elliptic PDEs”, Computer Physics Communications (2017).
- P. Mycek, F. Rizzi, O. Le Maître, K. Sargsyan, K. Morris, C. Safta, B. Debusschere, O. Knio, “Discrete A Priori Bounds for the Detection of Corrupted PDE Solutions in Exascale Computations”, SIAM Journal on Scientific Computing (2017).
- F. Rizzi, K. Morris, K. Sargsyan, P. Mycek, C. Safta, O. Le Maître, O. Knio, B. Debusschere, “Partial differential equations preconditioner resilient to soft and hard faults”, The International Journal of High Performance Computing Applications (2017).
2016
- M. Khalil, K. Chowdhary, C. Safta, K. Sargsyan, H.N. Najm, “Inference of reaction rate parameters based on summary statistics from experiments”, Proceedings of the Combustion Institute (2016).
- C. Safta, R.L.-Y. Chen, H.N. Najm, A. Pinar, J.-P. Watson, “Efficient Uncertainty Quantification in Stochastic Economic Dispatch”, IEEE Transactions on Power Systems (2016).
- C. Safta, M. Blaylock, J.A. Templeton, S.P. Domino, K. Sargsyan, H.N. Najm, “Uncertainty Quantification in LES of Channel Flow”, International Journal for Numerical Methods in Fluids (2016).
2015
- K. Sargsyan, F. Rizzi, P. Mycek, C. Safta, K. Morris, H.N. Najm, O. Le Maître, O. Knio, B. Debusschere, “Fault Resilient Domain Decomposition Preconditioner for PDEs”, SIAM Journal on Scientific Computing (2015).
- C. Safta, D.M. Ricciuto, K. Sargsyan, B. Debusschere, H.N. Najm, M. Williams, and P.E. Thornton, “Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model”, Geoscientific Model Development (2015).
- C. Safta, K. Sargsyan, B.J. Debusschere, H.N. Najm, “Hybrid discrete/continuum algorithms for stochastic reaction networks”, Journal of Computational Physics (2015).
2014
- C. Safta, K. Sargsyan, H.N. Najm, K. Chowdhary, B.J. Debusschere, L. P. Swiler, and M. S. Eldred, “Probabilistic Methods for Sensitivity Analysis and Calibration of Computer Models in the NASA Challenge Problem”, AIAA Journal of Aerospace Information Systems (2014).
- H.N. Najm, R. D. Berry, C. Safta, K. Sargsyan, B.J. Debusschere, “Data-Free Inference of Uncertain Parameters in Chemical Models”, International Journal for Uncertainty Quantification (2014).
- K. Kedia, C. Safta, J. Ray, H.N. Najm, A. F. Ghoniem, “A second-order coupled immersed boundary-SAMR construction for chemically reacting flow over a heat-conducting Cartesian grid-conforming solid”, Journal of Computational Physics (2014).
- K. Sargsyan, C. Safta, H.N. Najm, B.J. Debusschere, D. Ricciuto, and P. Thornton, “Dimensionality Reduction for Complex Models via Bayesian Compressive Sensing”, International Journal for Uncertainty Quantification (2014).
2013
- J. Prager, H.N. Najm, C. Safta, K. Sargsyan and W. J. Pitz, “Uncertainty quantification of reaction mechanisms accounting for correlations introduced by rate rules and fitted Arrhenius parameters”, Combustion and Flame (2013).
2012
- K. E. Cheng, D. J. Crary, J. Ray and C. Safta, “Structural models used in real-time biosurveillance outbreak detection and outbreak curve isolation from noisy background morbidity levels”, Journal of the American Medical Informatics Association (2012).
- K. Sargsyan, C. Safta, B.J. Debusschere and H.N. Najm, “Multiparameter Spectral Representation of Noise-induced Competence in Bacillus Subtilis”, IEEE/ACM Transactions on Computational Biology and Bioinformatics (2012).
2011
- K. Sargsyan, C. Safta, B.J. Debusschere and H.N. Najm, “Uncertainty Quantification given Discontinuous Model Response and a Limited Number of Model Runs”, SIAM Journal on Scientific Computing (2011).
2010 and earlier
- C. Safta, J. Ray and H.N. Najm, “A high-order low-Mach AMR construction for chemically reacting flows”, Journal of Computational Physics (2010).
- N. Bharadwaj, C. Safta, and C.K. Madnia, “Flame-wall interaction for a non-premixed flame propelled by a vortex ring”, Combustion Theory and Modelling (2007).
- C. Safta and C.K. Madnia, “Autoignition and Structure of Non-Premixed Methane Flames: Detailed and Reduced Kinetic Models”, Combustion and Flame (2006).
- C. Safta and C.K. Madnia, “Characteristics of methane diffusion flame in a reacting vortex ring”, Combustion Theory and Modelling (2004).
- C. Safta, S. Enachescu, and C.K. Madnia, “Interaction of a vortex ring with a diffusion flame”, Physics of Fluids (2002).