A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems. - Hessam Babaee; Minseok Choi; Themistoklis P. Sapsis; George E. Karniadakis (J. Comput. Phys., 2017)

Deep Learning of Turbulent Scalar Mixing. - Maziar Raissi; Hessam Babaee; Peyman Givi (CoRR, 2018)

Stochastic Domain Decomposition via Moment Minimization. - Dongkun Zhang; Hessam Babaee; George E. Karniadakis (SIAM J. Sci. Comput., 2018)

Real-time reduced-order modeling of stochastic partial differential equations via time-dependent subspaces. - Prerna Patil; Hessam Babaee (J. Comput. Phys., 2020)

On-the-fly Reduced Order Modeling of Passive and Reactive Species via Time-Dependent Manifolds. - Donya Ramezanian; Arash G. Nouri; Hessam Babaee (CoRR, 2021)

Physics-informed neural networks for improving cerebral hemodynamics predictions. - Mohammad Sarabian; Hessam Babaee; Kaveh Laksari (CoRR, 2021)

Multi-fidelity Bayesian neural networks: Algorithms and applications. - Xuhui Meng; Hessam Babaee; George Em Karniadakis (J. Comput. Phys., 2021)

Scalable In Situ Compression of Transient Simulation Data Using Time-Dependent Bases. - Shaghayegh Zamani Ashtiani; Mujeeb R. Malik; Hessam Babaee (CoRR, 2022)

Adaptive sparse interpolation for accelerating nonlinear stochastic reduced-order modeling with time-dependent bases. - Mohammad Hossein Naderi; Hessam Babaee (CoRR, 2022)

Scalable in situ compression of transient simulation data using time-dependent bases. - Shaghayegh Zamani Ashtiani; Mujeeb R. Malik; Hessam Babaee (J. Comput. Phys., 2022)

A quantum-inspired approach to exploit turbulence structures. - Nikita Gourianov; Michael Lubasch; Sergey Dolgov; Quincy Y. van den Berg; Hessam Babaee; Peyman Givi; Martin Kiffner; Dieter Jaksch (Nat. Comput. Sci., 2022)

Computing Sensitivities in Evolutionary Systems: A Real-Time Reduced Order Modeling Strategy. - Michael Donello; Mark H. Carpenter; Hessam Babaee (SIAM J. Sci. Comput., 2022)

Physics-Informed Neural Networks for Brain Hemodynamic Predictions Using Medical Imaging. - Mohammad Sarabian; Hessam Babaee; Kaveh Laksari (IEEE Trans. Medical Imaging, 2022)

Learning stiff chemical kinetics using extended deep neural operators. - Somdatta Goswami; Ameya D. Jagtap; Hessam Babaee; Bryan T. Susi; George Em Karniadakis (CoRR, 2023)

CUR Decomposition for Scalable Rank-Adaptive Reduced-Order Modeling of Nonlinear Stochastic PDEs with Time-Dependent Bases. - Michael Donello; G. Palkar; Mohammad Hossein Naderi; David C. Del Rey Fernández; Hessam Babaee (CoRR, 2023)

Low-Rank Solution Operator for Forced Linearized Dynamics with Unsteady Base Flows. - Alireza Amiri-Margavi; Hessam Babaee (CoRR, 2023)

Reduced-Order Modeling with Time-Dependent Bases for PDEs with Stochastic Boundary Conditions. - Prerna Patil; Hessam Babaee (SIAM/ASA J. Uncertain. Quantification, 2023)

A DEIM Tucker Tensor Cross Algorithm and its Application to Dynamical Low-Rank Approximation. - Behzad Ghahremani; Hessam Babaee (CoRR, 2024)

Reconstructing Blood Flow in Data-Poor Regimes: A Vasculature Network Kernel for Gaussian Process Regression. - Shaghayegh Zamani Ashtiani; Mohammad Sarabian; Kaveh Laksari; Hessam Babaee (CoRR, 2024)

Cross Algorithms for Cost-Effective Time Integration of Nonlinear Tensor Differential Equations on Low-Rank Tucker Tensor and Tensor Train Manifolds. - Behzad Ghahremani; Hessam Babaee (CoRR, 2024)

CUR for Implicit Time Integration of Random Partial Differential Equations on Low-Rank Matrix Manifolds. - Mohammad Hossein Naderi; Sara Akhavan; Hessam Babaee (CoRR, 2024)

Reduced order modeling of turbulent reacting flows on low-rank matrix manifolds. - Aidyn Aitzhan; Arash G. Nouri; Peyman Givi; Hessam Babaee (J. Comput. Phys., 2025)

Skeletal Reaction Models for Gasoline Surrogate Combustion. - Yinmin Liu; Hessam Babaee; Peyman Givi; Daniel Livescu; Arash G. Nouri (CoRR, 2025)