headshot of Hessam Babaee

Hessam Babaee

Associate Professor
Research Homepage Mechanical Engineering & Materials Science

overview

The research areas of interest to our lab are at the interface of scientific computing and machine learning. In particular, we develop data-driven and model-driven reduced order modeling techniques to reduce the computational cost of solving a variety of problems. This includes uncertainty quantification, high-dimensional sensitivity analysis, passive and reactive species transport and high-dimensional probability density function transport equations that arise in a number of scientific and engineering problems.We focus on a diverse set of applications from fluid dynamics and bioengineering to ocean engineering.

about

Co-PI of Wireless Underwater Power Transfer for AUVs: Optimization via Metamaterials funded by NOAA.

PI of XSEDE supercomputer allocation of 4.6 million SU’s for Developing Stochastic Reduced-Order Models for Thermal Components, funded by NSF.

PI of XSEDE supercomputer allocation of 1.1 million SU’s for Developing Stochastic Reduced-Order Models for Thermal Components, funded by NSF.

First place poster presentation 2010-Mechanical Engineering graduate student conference, Louisiana State University.

Ph.D. in Mechanical Engineering, Louisiana State University, 2013

M.Sc. in Applied Mathematics, Louisiana State University, 2013

M.Sc. in Mechanical Engineering, University of Tehran, 2006

B.Sc. in Mechanical Engineering, University of Tehran, 2003

Donello, M., Palkar, G., Naderi, M.H., Del Rey Fernandez, D.C., & Babaee, H. (2023). Oblique projection for scalable rank-adaptive reduced-order modelling of nonlinear stochastic partial differential equations with time-dependent bases. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 479(2278).The Royal Society. doi: 10.1098/rspa.2023.0320.

Naderi, M.H., & Babaee, H. (2023). Adaptive sparse interpolation for accelerating nonlinear stochastic reduced-order modeling with time-dependent bases. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 405, 115813.Elsevier BV. doi: 10.1016/j.cma.2022.115813.

Patil, P., & Babaee, H. (2023). Reduced-Order Modeling with Time-Dependent Bases for PDEs with Stochastic Boundary Conditions. SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 11(3), 727-756.Society for Industrial & Applied Mathematics (SIAM). doi: 10.1137/21M1468097.

Ashtiani, S.Z., Malik, M.R., & Babaee, H. (2022). Scalable in situ compression of transient simulation data using time-dependent bases. JOURNAL OF COMPUTATIONAL PHYSICS, 468, 111457.Elsevier BV. doi: 10.1016/j.jcp.2022.111457.

Donello, M., Carpenter, M.H., & Babaee, H. (2022). COMPUTING SENSITIVITIES IN EVOLUTIONARY SYSTEMS: A REAL-TIME REDUCED ORDER MODELING STRATEGY. SIAM JOURNAL ON SCIENTIFIC COMPUTING, 44(1), A128-A149.Society for Industrial & Applied Mathematics (SIAM). doi: 10.1137/20M1388565.

Gourianov, N., Lubasch, M., Dolgov, S., van den Berg, Q.Y., Babaee, H., Givi, P., Kiffner, M., & Jaksch, D. (2022). A quantum-inspired approach to exploit turbulence structures. Nat Comput Sci, 2(1), 30-37.Springer Science and Business Media LLC. doi: 10.1038/s43588-021-00181-1.

Sarabian, M., Babaee, H., & Laksari, K. (2022). Physics-Informed Neural Networks for Brain Hemodynamic Predictions Using Medical Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING, 41(9), 2285-2303.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TMI.2022.3161653.

Meng, X., Babaee, H., & Karniadakis, G.E. (2021). Multi-fidelity Bayesian neural networks: Algorithms and applications. JOURNAL OF COMPUTATIONAL PHYSICS, 438, 110361.Elsevier BV. doi: 10.1016/j.jcp.2021.110361.

Ramezanian, D., Nouri, A.G., & Babaee, H. (2021). On-the-fly reduced order modeling of passive and reactive species via time-dependent manifolds. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 382, 113882.Elsevier BV. doi: 10.1016/j.cma.2021.113882.

Arrue, P., Toosizadeh, N., Babaee, H., & Laksari, K. (2020). Low-Rank Representation of Head Impact Kinematics: A Data-Driven Emulator. FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 8, 555493.Frontiers Media SA. doi: 10.3389/fbioe.2020.555493.

Babaee, H., Bastidas, C., DeFilippo, M., Chryssostomidis, C., & Karniadakis, G.E. (2020). AMultifidelity Framework and Uncertainty Quantification for Sea Surface Temperature in the Massachusetts and Cape Cod Bays. EARTH AND SPACE SCIENCE, 7(2).American Geophysical Union (AGU). doi: 10.1029/2019EA000954.

Patil, P., & Babaee, H. (2020). Real-time reduced-order modeling of stochastic partial differential equations via time-dependent subspaces. JOURNAL OF COMPUTATIONAL PHYSICS, 415, 109511.Elsevier BV. doi: 10.1016/j.jcp.2020.109511.

Babaee, H. (2019). An observation-driven time-dependent basis for a reduced description of transient stochastic systems. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 475(2231), 20190506.The Royal Society. doi: 10.1098/rspa.2019.0506.

Raissi, M., Babaee, H., & Givi, P. (2019). Deep learning of turbulent scalar mixing. PHYSICAL REVIEW FLUIDS, 4(12).American Physical Society (APS). doi: 10.1103/PhysRevFluids.4.124501.

Raissi, M., Babaee, H., & Karniadakis, G.E. (2019). Parametric Gaussian process regression for big data. COMPUTATIONAL MECHANICS, 64(2), 409-416.Springer Science and Business Media LLC. doi: 10.1007/s00466-019-01711-5.

Laksari, K., Kurt, M., Babaee, H., Kleiven, S., & Camarillo, D. (2018). Mechanistic Insights into Human Brain Impact Dynamics through Modal Analysis. PHYSICAL REVIEW LETTERS, 120(13), 138101.American Physical Society (APS). doi: 10.1103/PhysRevLett.120.138101.

Zhang, D., Babaee, H., & Karniadakis, G.E. (2018). STOCHASTIC DOMAIN DECOMPOSITION VIA MOMENT MINIMIZATION. SIAM JOURNAL ON SCIENTIFIC COMPUTING, 40(4), A2152-A2173.Society for Industrial & Applied Mathematics (SIAM). doi: 10.1137/17M1160756.

Babaee, H., Choi, M., Sapsis, T.P., & Karniadakis, G.E. (2017). A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems. JOURNAL OF COMPUTATIONAL PHYSICS, 344, 303-319.Elsevier BV. doi: 10.1016/j.jcp.2017.04.057.

Babaee, H., Farazmand, M., Haller, G., & Sapsis, T.P. (2017). Reduced-order description of transient instabilities and computation of finite-time Lyapunov exponents. CHAOS, 27(6), 063103.AIP Publishing. doi: 10.1063/1.4984627.

Babaee, H., & Sapsis, T.P. (2016). A minimization principle for the description of modes associated with finite-time instabilities. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 472(2186), 20150779.The Royal Society. doi: 10.1098/rspa.2015.0779.

Babaee, H., Perdikaris, P., Chryssostomidis, C., & Karniadakis, G.E. (2016). Multi-fidelity modelling of mixed convection based on experimental correlations and numerical simulations. JOURNAL OF FLUID MECHANICS, 809, 895-917.Cambridge University Press (CUP). doi: 10.1017/jfm.2016.718.

Alvergue, L., Babaee, H., Gu, G., & Acharya, S. (2015). Feedback Stabilization of a Reduced-Order Model of a Jet in Crossflow. AIAA JOURNAL, 53(9), 2472-2481.American Institute of Aeronautics and Astronautics (AIAA). doi: 10.2514/1.J053295.

Zheng, X., Babaee, H., Dong, S., Chryssostomidis, C., & Karniadakis, G.E. (2015). A phase-field method for 3D simulation of two-phase heat transfer. INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 82, 282-298.Elsevier BV. doi: 10.1016/j.ijheatmasstransfer.2014.11.052.

Babaee, H., & Acharya, S. (2014). A HYBRID STAGGERED/SEMISTAGGERED FINITE-DIFFERENCE ALGORITHM FOR SOLVING TIME-DEPENDENT INCOMPRESSIBLE NAVIER-STOKES EQUATIONS ON CURVILINEAR GRIDS. NUMERICAL HEAT TRANSFER PART B-FUNDAMENTALS, 65(1), 1-26.Informa UK Limited. doi: 10.1080/10407790.2013.827012.

Babaee, H., Acharya, S., & Wan, X. (2014). Optimization of Forcing Parameters of Film Cooling Effectiveness. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 136(6).ASME International. doi: 10.1115/1.4025732.

Babaee, H., Wan, X., & Acharya, S. (2014). Effect of Uncertainty in Blowing Ratio on Film Cooling Effectiveness. JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME, 136(3).ASME International. doi: 10.1115/1.4025562.

Nouri, A.G., Babaee, H., Givi, P., Chelliah, H.K., & Livescu, D. (2022). Skeletal model reduction with forced optimally time dependent modes. In COMBUSTION AND FLAME, 235, (p. 111684).Elsevier BV.College Station, TX. doi: 10.1016/j.combustflame.2021.111684.

Wang, Z., Chalfant, G.E.K.J., Chryssostomidis, C., & Babaee, H. (2017). High-fidelity modeling and optimization of conjugate heat transfer in arrays of heated cables. In 2017 IEEE Electric Ship Technologies Symposium (ESTS), (pp. 557-563).IEEE. doi: 10.1109/ests.2017.8069337.

Babaee, H., Chalfant, J., Chryssostomidis, C., & Sanfiorenzo, A.B. (2015). System-level analysis of chilled water systems aboard naval ships. In 2015 IEEE Electric Ship Technologies Symposium (ESTS), (pp. 370-375).IEEE. doi: 10.1109/ests.2015.7157921.

Yang, S., Ordonez, J.C., Vargas, J.V.C., Babaee, H., Chalfant, J., & Chryssostomidis, C. (2015). Comprehensive system-level thermal modeling of all-electric ships: Integration of SMCS and vemESRDC. In 2015 IEEE Electric Ship Technologies Symposium (ESTS), (pp. 251-255).IEEE. doi: 10.1109/ests.2015.7157898.

Babaee, H., Acharya, S., & Wan, X. (2013). Optimization of Forcing Parameters of Film Cooling Effectiveness. In Volume 3B: Heat Transfer, 3.American Society of Mechanical Engineers. doi: 10.1115/gt2013-95636.

Babaee, H., Wan, X., & Acharya, S. (2013). Effect of Uncertainty in Blowing Ratio on Film Cooling Effectiveness. In Volume 3: Gas Turbine Heat Transfer; Transport Phenomena in Materials Processing and Manufacturing; Heat Transfer in Electronic Equipment; Symposium in Honor of Professor Richard Goldstein; Symposium in Honor of Prof. Spalding; Symposium in Honor of Prof. Arthur E. Bergles, 3.American Society of Mechanical Engineers. doi: 10.1115/ht2013-17159.

Babaee, H., & Acharya, S. (2012). A symmetric finite difference discretization of pressure-poisson equation on curvilinear grids. In 42nd AIAA Fluid Dynamics Conference and Exhibit 2012.

Babaee, H., & Acharya, S. (2012). A Symmetric Finite Difference Discretization of Pressure-Poisson Equation on Curvilinear Grids. In 42nd AIAA Fluid Dynamics Conference and Exhibit.American Institute of Aeronautics and Astronautics. doi: 10.2514/6.2012-3068.

Babaee, H., & Acharya, S. (2011). A Semi-Staggered Numerical Procedure for the Incompressible Navier-Stokes Equations on Curvilinear Grids. In Volume 6: Fluids and Thermal Systems; Advances for Process Industries, Parts A and B, 6(PARTS A AND B), (pp. 927-936).ASMEDC. doi: 10.1115/imece2011-64224.

Research interests

Computational fluid dynamics and...
Flow instability
High performance computing
Multi-fidelity modeling
Multi-physics modelin
Stochastic modeling
Uncertainty quantification