Digital Twin Lab

Journal Articles

  1. A knowledge-informed machine learning framework for multifidelity modeling
    Shafi Al Salman Romeo, Kursat Kara and Omer San
    Machine Learning for Computational Science and Engineering, Springer Nature, Vol. 2, pp. 26, 2026
  2. Localized PCA-Net neural operators for scalable solution reconstruction of elliptic PDEs
    Mrigank Dhingra, Romit Maulik, Adil Rasheed and Omer San
    Machine Learning for Computational Science and Engineering, Springer Nature, Vol. 2, pp. 22, 2026
  3. Discovery of governing equations for reduced-order aerodynamic modes of atmospheric entry capsules
    Ashraf Kassem, Shafi Al Salman Romeo, Bipin Tiwari, Lamisa Musharrat, Omer San and Kursat Kara
    Aerospace Science and Technology, Elsevier, Vol. 178, pp. 112454, 2026
  4. FEDONet: Fourier-embedded DeepONet for spectrally accurate operator learning
    Arth Sojitra, Mrigank Dhingra and Omer San
    Journal of Computational Physics, Elsevier, Vol. 559, pp. 114931, 2026
  5. Data-efficient neural operator surrogates for nonlinear pitch dynamics of blunt-body re-entry vehicles
    Bipin Tiwari, Ashraf Kassem, Shafi Al Salman Romeo, Dirk Ekelschot, Cole Kazemba, Kursat Kara and Omer San
    Aerospace Science and Technology, Elsevier, Vol. 177, pp. 112360, 2026
  6. The evolution of digital twins from reactive to agentic systems
    Omer San, Adil Rasheed, Eda Bozdemir and Jun Deng
    Nature Computational Science, Nature Publishing Group, Vol. 6, pp. 6—10, 2026
  7. Adaptive Bayesian learning for stability characterization of re-entry vehicles
    Bipin Tiwari, Lamisa Musharrat, Shafi Al Salman Romeo, Ashraf Kassem, Kursat Kara and Omer San
    Scientific Reports, Nature Publishing Group UK London, Vol. 16, pp. 10267, 2026
  8. Accelerating Bayesian inverse design in computational fluid dynamics using neural operators
    Bipin Tiwari and Omer San
    Machine Learning for Computational Science and Engineering, Springer Nature, Vol. 2, pp. 14, 2026
  9. Emulator-accelerated Bayesian framework for nonlinear parameter estimation of entry capsule dynamic stability
    Shafi Al Salman Romeo, Ashraf Kassem, Bipin Tiwari, Lamisa Musharrat, Omer San and Kursat Kara
    Aerospace Science and Technology, Elsevier, Vol. 177, pp. 112342, 2026
  10. Data-driven reduced-order modeling framework for blunt-body aerodynamic characterization
    Ashraf Kassem, Shafi Al Salman Romeo, Bipin Tiwari, Omer San and Kursat Kara
    Aerospace Science and Technology, Elsevier, Vol. 171, pp. 111615, 2026
  11. Multifidelity data fusion for analyzing dynamic stability of atmospheric entry vehicles
    Shafi Al Salman Romeo, Ashraf Kassem, Bipin Tiwari, Omer San and Kursat Kara
    Aerospace Science and Technology, Elsevier, Vol. 168, pp. 111049, 2026
  12. Nonlinear parameter estimation for entry capsule dynamic stability analysis and uncertainty quantification
    Furkan Oz, Shafi Al Salman Romeo, Ashraf Kassem, Dirk Ekelschot, Joseph C Schulz, Cole Kazemba, Omer San and Kursat Kara
    Journal of Spacecraft and Rockets, American Institute of Aeronautics and Astronautics, Vol. 63, pp. 407—420, 2026
  13. Bayesian framework for estimating dynamic stability derivatives in 6-DoF blunt-body entry vehicles
    Ashraf Kassem, Shafi Al Salman Romeo, Bipin Tiwari, Omer San and Kursat Kara
    Aerospace Science and Technology, Elsevier, Vol. 167, pp. 110646, 2025
  14. Superbench: A super-resolution benchmark dataset for scientific machine learning
    Pu Ren, N Benjamin Erichson, Shashank Subramanian, Omer San, Zarija Lukic and Michael W Mahoney
    The Journal of Data-centric Machine Learning Research (DMLR), Vol. 2, No. 8, pp. 1—45, 2025
  15. Development and performance evaluation of empirical models compatible with building energy modeling engines for unitary equipment
    Shahzad Yousaf, Craig R Bradshaw, Rushikesh Kamalapurkar and Omer San
    Science and Technology for the Built Environment, Taylor & Francis, Vol. 31, No. 5, pp. 533—550, 2025
  16. Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approach
    Jacob Wulff Wold, Florian Stadtmann, Adil Rasheed, Mandar Tabib, Omer San and Jan-Tore Horn
    Engineering Applications of Artificial Intelligence, Elsevier, Vol. 137, pp. 109167, 2024
  17. Enhancing elasticity models with deep learning: A novel corrective source term approach for accurate predictions
    Sondre Sørbø, Sindre Stenen Blakseth, Adil Rasheed, Trond Kvamsdal and Omer San
    Applied Soft Computing, Elsevier, Vol. 153, pp. 111312, 2024
  18. Bridging large eddy simulation and reduced order modeling of convection-dominated flows through spatial filtering: Review and perspectives
    Annalisa Quaini, Omer San, Alessandro Veneziani and Traian Iliescu
    Fluids, MDPI, Vol. 9, pp. 178, 2024
  19. A gray-box model for unitary air conditioners developed with symbolic regression
    Shahzad Yousaf, Craig R Bradshaw, Rushikesh Kamalapurkar and Omer San
    International Journal of Refrigeration, Elsevier, Vol. 168, pp. 696—707, 2024
  20. Accelerated evolution of Burgers' turbulence with coarse projective integration and deep learning
    Mrigank Dhingra, Omer San and Anne E Staples
    Physics of Fluids, AIP Publishing, Vol. 36, No. 3, 2024
  21. An augmented physics informed neural network approach for blunt-body dynamics
    Shafi Al Salman Romeo, Furkan Oz, Ashraf Kassem, Kursat Kara and Omer San
    Physics of Fluids, AIP Publishing, Vol. 36, No. 1, 2024
  22. Decentralized digital twins of complex dynamical systems
    Omer San, Suraj Pawar and Adil Rasheed
    Scientific Reports, Nature Publishing Group UK London, Vol. 13, No. 1, pp. 20087, 2023
  23. Digital twins in wind energy: Emerging technologies and industry-informed future directions
    Florian Stadtmann, Adil Rasheed, Trond Kvamsdal, Kjetil André Johannessen, Omer San, Konstanze Kölle, John Olav Tande, Idar Barstad, Alexis Benhamou and Thomas Brathaug
    IEEE Access, IEEE, Vol. 11, pp. 110762—110795, 2023
  24. Physics guided machine learning for variational multiscale reduced order modeling
    Shady E Ahmed, Omer San, Adil Rasheed, Traian Iliescu and Alessandro Veneziani
    SIAM Journal on Scientific Computing, SIAM, Vol. 45, No. 3, pp. B283—B313, 2023
  25. Forward sensitivity analysis and mode dependent control for closure modeling of Galerkin systems
    Shady E Ahmed and Omer San
    Computers and Mathematics with Applications, Vol. 145, pp. 289—302, 2023
  26. On the dual advantage of placing observations through forward sensitivity analysis
    Shady E Ahmed, Omer San, Sivaramakrishnan Lakshmivarahan and John M Lewis
    Proceedings of the Royal Society A, Vol. 479, pp. 20220815, 2023
  27. An energy-based lengthscale for reduced order models of turbulent flows
    Changhong Mou, Elia Merzari, Omer San and Traian Iliescu
    Nuclear Engineering and Design, Elsevier, Vol. 412, pp. 112454, 2023
  28. Investigating critical model input features for unitary air conditioning equipment
    Shahzad Yousaf, Craig R Bradshaw, Rushikesh Kamalapurkar and Omer San
    Energy and Buildings, Elsevier, Vol. 284, pp. 112823, 2023
  29. An efficient quantum partial differential equation solver with Chebyshev points
    Furkan Oz, Omer San and Kursat Kara
    Scientific Reports, Nature Publishing Group UK London, Vol. 13, No. 1, pp. 7767, 2023
  30. Artificial intelligence-driven digital twin of a modern house demonstrated in virtual reality
    Elias Mohammed Elfarri, Adil Rasheed and Omer San
    IEEE Access, IEEE, Vol. 11, pp. 35035—35058, 2023
  31. Blending machine learning and sequential data assimilation over latent spaces for surrogate modeling of Boussinesq systems
    Saeed Akbari, Pedram H Dabaghian and Omer San
    Physica D: Nonlinear Phenomena, Elsevier, Vol. 448, pp. 133711, 2023
  32. Numerical assessment of a nonintrusive surrogate model based on recurrent neural networks and proper orthogonal decomposition: Rayleigh—Bénard convection
    Saeed Akbari, Suraj Pawar and Omer San
    International Journal of Computational Fluid Dynamics, Taylor & Francis, Vol. 36, No. 7, pp. 599—617, 2022
  33. Nonintrusive reduced order modelling of convective Boussinesq flows
    Pedram H Dabaghian, Shady E Ahmed and Omer San
    International Journal of Computational Fluid Dynamics, Taylor & Francis, Vol. 36, No. 7, pp. 578—598, 2022
  34. Prospects of federated machine learning in fluid dynamics
    Omer San, Suraj Pawar and Adil Rasheed
    AIP Advances, Vol. 12, pp. 095212, 2022
  35. Towards multi-fidelity deep learning of wind turbine wakes
    Suraj Pawar, Ashesh Sharma, Ganesh Vijayakumar, Chrstopher J Bay, Shashank Yellapantula and Omer San
    Renewable Energy, Elsevier, Vol. 200, pp. 867—879, 2022
  36. Equation-free surrogate modeling of geophysical flows at the intersection of machine learning and data assimilation
    Suraj Pawar and Omer San
    Journal of Advances in Modeling Earth Systems, Elsevier, Vol. 14, pp. e2022MS003170, 2022
  37. Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems
    Omer San, Suraj Pawar and Adil Rasheed
    Scientific Reports, Elsevier, Vol. 12, pp. 17947, 2022
  38. Combining physics-based and data-driven techniques for reliable hybrid analysis and modeling using the corrective source term approach
    Sindre Stenen Blakseth, Adil Rasheed, Trond Kvamsdal and Omer San
    Applied Soft Computing, Vol. 128, pp. 109533, 2022
  39. Dynamic mode decomposition with core sketch
    Shady E Ahmed, Pedram H Dabaghian, Omer San, Diana A Bistrian and Ionel M Navon
    Physics of Fluids, AIP Publishing LLC, Vol. 34, No. 6, pp. 066603, 2022
  40. The digital twin revolution
    Omer San
    Nature Computational Science, Nature Publishing Group, Vol. 1, No. 5, pp. 307—308, 2021
  41. Physics guided neural networks for modelling of non-linear dynamics
    Haakon Robinson, Suraj Pawar, Adil Rasheed and Omer San
    Neural Networks, Vol. 154, pp. 333—345, 2022
  42. Frame invariant neural network closures for Kraichnan turbulence
    Suraj Pawar, Omer San, Adil Rasheed and Prakash Vedula
    Physica A: Statistical Mechanics and its Applications, Vol. 609, pp. 128327, 2022
  43. Multi-fidelity information fusion with concatenated neural networks
    Suraj Pawar, Omer San, Prakash Vedula, Adil Rasheed and Trond Kvamsdal
    Scientific Reports, Vol. 12, pp. 5900, 2022
  44. Analysis of radial expansion, inversion and cavitation of rubberlike functionally graded material spheres
    S A Mousavi, A Bahrami, O San and R C Batra
    Mathematics and Mechanics of Solids, Vol. 28, pp. 208—228, 2023
  45. Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning
    Amalie Heiberg, Thomas Nakken Larsen, Eivind Meyer, Adil Rasheed, Omer San and Damiano Varagnolo
    Neural Networks, Vol. 152, pp. 17—33, 2022
  46. Deep neural network enabled corrective source term approach to hybrid analysis and modeling
    Sindre Stenen Blakseth, Adil Rasheed, Trond Kvamsdal and Omer San
    Neural Networks, Vol. 146, pp. 181—199, 2022
  47. Nonlinear proper orthogonal decomposition for convection-dominated flows
    Shady E Ahmed, Omer San, Adil Rasheed and Traian Iliescu
    Physics of Fluids, Vol. 33, No. 12, pp. 121702, 2021
  48. On closures for reduced order models—A spectrum of first-principle to machine-learned avenues
    Shady E Ahmed, Suraj Pawar, Omer San, Adil Rasheed, Traian Iliescu and Bernd Noack
    Physics of Fluids, AIP Publishing LLC, Vol. 33, pp. 091301, 2021
  49. A nonintrusive hybrid neural-physics modeling of incomplete dynamical systems: Lorenz equations
    Suraj Pawar, Omer San, Adil Rasheed and Ionel M Navon
    GEM - International Journal on Geomathematics, Vol. 12, pp. 17, 2021
  50. Model fusion with physics-guided machine learning: Projection-based reduced-order modeling
    Suraj Pawar, Omer San, Aditya Nair, Adil Rasheed and Trond Kvamsdal
    Physics of Fluids, AIP Publishing LLC, Vol. 33, No. 6, pp. 067123, 2021
  51. Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution
    Omer San, Adil Rasheed and Trond Kvamsdal
    GAMM-Mitteilungen — Surveys for Applied Mathematics and Mechanics, Wiley Online Library, Vol. 44, pp. e202100007, 2021
  52. Geometric change detection in digital twins
    Tiril Sundby, Julia Maria Graham, Adil Rasheed, Mandar Tabib and Omer San
    Digital, Multidisciplinary Digital Publishing Institute, Vol. 1, No. 2, pp. 111—129, 2021
  53. A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction
    Shady E Ahmed, Suraj Pawar, Omer San, Adil Rasheed and Mandar Tabib
    Computers & Fluids, Elsevier, Vol. 221, pp. 104895, 2021
  54. Applying object detection to marine data and exploring explainability of a fully convolutional neural network using principal component analysis
    Herman Stavelin, Adil Rasheed, Omer San and Arne Johan Hestnes
    Ecological Informatics, Elsevier, Vol. 62, pp. 101269, 2021
  55. Multifidelity computing for coupling full and reduced order models
    Shady E Ahmed, Omer San, Kursat Kara, Rami Younis and Adil Rasheed
    PLOS ONE, Public Library of Science San Francisco, CA USA, Vol. 16, No. 2, pp. e0246092, 2021
  56. Deep reinforcement learning controller for 3D path following and collision avoidance by autonomous underwater vehicles
    Simen Theie Havenstrøm, Adil Rasheed and Omer San
    Frontiers in Robotics and AI, Frontiers, Vol. 7, pp. 211, 2021
  57. Physics guided machine learning using simplified theories
    Suraj Pawar, Omer San, Burak Aksoylu, Adil Rasheed and Trond Kvamsdal
    Physics of Fluids, AIP Publishing LLC, Vol. 33, No. 1, pp. 011701, 2021
  58. Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows
    Suraj Pawar and Omer San
    Physical Review Fluids, APS, Vol. 6, No. 5, pp. 050501, 2021
  59. Data-driven variational multiscale reduced order models
    Changhong Mou, Birgul Koc, Omer San, Leo G Rebholz and Traian Iliescu
    Computer Methods in Applied Mechanics and Engineering, Vol. 373, pp. 113470, 2021
  60. Interface learning of multiphysics and multiscale systems
    Shady E Ahmed, Omer San, Kursat Kara, Rami Younis and Adil Rasheed
    Physical Review E, APS, Vol. 102, No. 5, pp. 053304, 2020
  61. Interface learning in fluid dynamics: Statistical inference of closures within micro—macro-coupling models
    Suraj Pawar, Shady E Ahmed and Omer San
    Physics of Fluids, AIP Publishing LLC, Vol. 32, No. 9, pp. 091704, 2020
  62. COLREG-compliant collision avoidance for unmanned surface vehicle using deep reinforcement learning
    Eivind Meyer, Amalie Heiberg, Adil Rasheed and Omer San
    IEEE Access, IEEE, Vol. 8, pp. 165344—165364, 2020
  63. Forward sensitivity approach for estimating eddy viscosity closures in nonlinear model reduction
    Shady E Ahmed, Kinjal Bhar, Omer San and Adil Rasheed
    Physical Review E, Vol. 102, pp. 043302, 2020
  64. Numerical investigation of air mixer for HVAC testing applications
    M Ahmed, H Park, C Bach and Omer San
    Science and Technology for the Built Environment, Vol. 26, No. 9, pp. 1252—1273, 2020
  65. Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows
    Suraj Pawar, Shady E Ahmed, Omer San, Adil Rasheed and Ionel M Navon
    Physics of Fluids, Vol. 32, pp. 076606, 2020
  66. PyDA: A hands-on introduction to dynamical data assimilation with Python
    Shady E Ahmed, Suraj Pawar and Omer San
    Fluids, Multidisciplinary Digital Publishing Institute, Vol. 5, No. 4, pp. 225, 2020
  67. Recent numerical advances in fluid mechanics
    Omer San
    Fluids, Multidisciplinary Digital Publishing Institute, Vol. 5, No. 2, pp. 73, 2020
  68. An evolve-then-correct reduced order model for hidden fluid dynamics
    Suraj Pawar, Shady E Ahmed, Adil Rasheed and Omer San
    Mathematics, Vol. 8, No. 4, pp. 570, 2020
  69. Data-driven recovery of hidden physics in reduced order modeling of fluid flows
    Suraj Pawar, Shady E Ahmed, Adil Rasheed and Omer San
    Physics of Fluids, Vol. 32, pp. 036602, 2020
  70. A long short-term memory embedding for hybrid uplifted reduced order models
    Shady E Ahmed, Omer San, Adil Rasheed and Traian Iliescu
    Physica D: Nonlinear Phenomena, Vol. 406, pp. 132409, 2020
  71. Numerical assessments of a parametric implicit large eddy simulation model
    Romit Maulik and Omer San
    Journal of Computational and Applied Mathematics, Vol. 376, pp. 112866, 2020
  72. Taming an autonomous surface vehicle for path following and collision avoidance using deep reinforcement learning
    E Meyer, Haakon Robinson, Adil Rasheed and Omer San
    IEEE Access, IEEE, Vol. 8, pp. 41466—41481, 2020
  73. Spatiotemporally dynamic implicit large eddy simulation using machine learning classifiers
    Romit Maulik, Omer San and Jamey D. Jacob
    Physica D: Nonlinear Phenomena, Vol. 406, pp. 132409, 2020
  74. Breaking the Kolmogorov barrier in model reduction of fluid flows
    Shady E Ahmed and Omer San
    Fluids, Multidisciplinary Digital Publishing Institute, Vol. 5, No. 1, pp. 26, 2020
  75. Digital twin: values, challenges and enablers from a modeling perspective
    Adil Rasheed, Omer San and Trond Kvamsdal
    IEEE Access, IEEE, Vol. 8, pp. 21980 — 22012, 2020
  76. Sampling and resolution characteristics in reduced order models of shallow water equations: intrusive vs non-intrusive
    Shady E Ahmed, Omer San, Diane A Bistrian and Michael Navon
    International Journal Numerical Methods in Fluids, Wiley, Vol. 92, No. 8, pp. 992—1036, 2020
  77. A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence
    Suraj Pawar, Omer San, Adil Rasheed and Prakash Vedula
    Theoretical and Computational Fluid Dynamics, Springer, Vol. 34, pp. 429—455, 2020
  78. Feature engineering and symbolic regression methods for detecting hidden physics from sparse sensor observation data
    Harsha Vaddireddy, Adil Rasheed, Anne E Staples and Omer San
    Physics of Fluids, AIP Publishing LLC, Vol. 32, No. 1, pp. 015113, 2020
  79. Memory embedded non-intrusive reduced order modeling of non-ergodic flows
    Shady E Ahmed, Sk Mashfiqur Rahman, Omer San, Adil Rasheed and Ionel M Navon
    Physics of Fluids, AIP Publishing LLC, Vol. 31, No. 12, pp. 126602, 2019
  80. A nonintrusive reduced order modeling framework for quasigeostrophic turbulence
    Sk M Rahman, Suraj Pawar, Omer San, A Rasheed and T Iliescu
    Physical Review E, Vol. 100, pp. 053306, 2019
  81. A deep learning enabler for non-intrusive reduced order modeling of fluid flows
    S Pawar, SM Rahman, H Vaddireddy, O San, A Rasheed and P Vedula
    Physics of Fluids, AIP Publishing, Vol. 31, pp. 085101, 2019
  82. A dynamic closure modeling framework for model order reduction of geophysical flows
    Sk M Rahman, Shady E Ahmed and Omer San
    Physics of Fluids, AIP Publishing, Vol. 31, No. 4, pp. 046602, 2019
  83. Sub-grid scale model classification and blending through deep learning
    Romit Maulik, Omer San, Jamey D Jacob and Christopher Crick
    Journal of Fluid Mechanics, Cambridge University Press, Vol. 870, pp. 784—812, 2019
  84. CFD Julia: A learning module structuring an introductory course on computational fluid dynamics
    Suraj Pawar and Omer San
    Fluids, Multidisciplinary Digital Publishing Institute, Vol. 4, No. 3, pp. 159, 2019
  85. Equation discovery using fast function extraction: a deterministic symbolic regression approach
    Harsha Vaddireddy and Omer San
    Fluids, Multidisciplinary Digital Publishing Institute, Vol. 4, No. 2, pp. 111, 2019
  86. A relaxation filtering approach for two-dimensional Rayleigh—Taylor instability-induced flows
    Sk Rahman and Omer San
    Fluids, Multidisciplinary Digital Publishing Institute, Vol. 4, No. 2, pp. 78, 2019
  87. An artificial neural network framework for reduced order modeling of transient flows
    Omer San, Romit Maulik and Mansoor Ahmed
    Communications in Nonlinear Science and Numerical Simulation, Elsevier, Vol. 77, pp. 271—287, 2019
  88. Subgrid modelling for two-dimensional turbulence using neural networks
    Romit Maulik, Omer San, Adil Rasheed and Prakash Vedula
    Journal of Fluid Mechanics, Cambridge University Press, Vol. 858, pp. 122—144, 2019
  89. A localised dynamic closure model for Euler turbulence
    S M Rahman and Omer San
    International Journal of Computational Fluid Dynamics, Taylor & Francis, Vol. 32, No. 8--9, pp. 326—378, 2019
  90. Data-driven deconvolution for large eddy simulations of Kraichnan turbulence
    Romit Maulik, Omer San, Adil Rasheed and Prakash Vedula
    Physics of Fluids, AIP Publishing, Vol. 30, No. 12, pp. 125109, 2018
  91. A hybrid approach for model order reduction of barotropic quasi-geostrophic turbulence
    Sk M Rahman, Omer San and Adil Rasheed
    Fluids, Multidisciplinary Digital Publishing Institute, Vol. 3, No. 4, pp. 86, 2018
  92. Stabilized principal interval decomposition method for model reduction of nonlinear convective systems with moving shocks
    Mansoor Ahmed and Omer San
    Computational and Applied Mathematics, Springer, Vol. 37, No. 5, pp. 6870—6902, 2018
  93. Improved singlet oxygen generation and antimicrobial activity of sulphur-doped graphene quantum dots coupled with methylene blue for photodynamic therapy applications
    Khomidkhodza Kholikov, Saidjafarzoda Ilhom, Muhammed Sajjad, Michael E Smith, Jerry D Monroe, Omer San and Ali Oguz Er
    Photodiagnosis and Photodynamic Therapy, Elsevier, Vol. 24, pp. 7—14, 2018
  94. A hybrid analytics paradigm combining physics-based modeling and data-driven modeling to accelerate incompressible flow solvers
    Sk M Rahman, Adil Rasheed and Omer San
    Fluids, Multidisciplinary Digital Publishing Institute, Vol. 3, No. 3, pp. 50, 2018
  95. Stratified Kelvin—Helmholtz turbulence of compressible shear flows
    Omer San and Romit Maulik
    Nonlinear Processes in Geophysics, Vol. 25, No. 2, pp. 457—476, 2018
  96. Extreme learning machine for reduced order modeling of turbulent geophysical flows
    Omer San and Romit Maulik
    Physical Review E, APS, Vol. 97, No. 4, pp. 042322, 2018
  97. Neural network closures for nonlinear model order reduction
    Omer San and Romit Maulik
    Advances in Computational Mathematics, Springer, Vol. 44, No. 6, pp. 1717—1750, 2018
  98. An adaptive multilevel wavelet framework for scale-selective WENO reconstruction schemes
    R Maulik, O San and R Behera
    International Journal for Numerical Methods in Fluids, Wiley Online Library, Vol. 87, No. 5, pp. 239—269, 2018
  99. Laser shock wave-assisted patterning on NiTi shape memory alloy surfaces
    Saidjafarzoda Ilhom, Dovletgeldi Seyitliyev, Khomidkohodza Kholikov, Zachary Thomas, Ali Oguz Er, Peizhen Li, Haluk E Karaca and Omer San
    Shape Memory and Superelasticity, Springer, Vol. 4, No. 1, pp. 224—231, 2018
  100. Scalable patterning using laser-induced shock waves
    Saidjafarzoda Ilhom, Khomidkhodza Kholikov, Peizhen Li, Claire Ottman, Dylan Sanford, Zachary Thomas, Omer San, Haluk E Karaca and Ali Oguz Er
    Optical Engineering, International Society for Optics and Photonics, Vol. 57, No. 4, pp. 041413, 2018
  101. Machine learning closures for model order reduction of thermal fluids
    Omer San and Romit Maulik
    Applied Mathematical Modelling, Vol. 60, pp. 681—710, 2018
  102. A dynamic closure modeling framework for large eddy simulation using approximate deconvolution: Burgers equation
    Romit Maulik and Omer San
    Cogent Physics, Taylor & Francis, Vol. 5, No. 1, pp. 1464368, 2018
  103. Generalized deconvolution procedure for structural modeling of turbulence
    Omer San and Prakash Vedula
    Journal of Scientific Computing, Springer, Vol. 75, No. 2, pp. 1187—1206, 2018
  104. Explicit and implicit LES closures for Burgers turbulence
    Romit Maulik and Omer San
    Journal of Computational Applied Mathematics, Vol. 327, pp. 12—40, 2018
  105. A neural network approach for the blind deconvolution of turbulent flows
    Romit Maulik and Omer San
    Journal of Fluid Mechanics, Cambridge University Press, Vol. 831, pp. 151—181, 2017
  106. Laser-induced hydrogen generation from graphite and coal
    Dovletgeldi Seyitliyev, Khomidkhodzha Kholikov, Byron Grant, Omer San and Ali Oguz Er
    International Journal of Hydrogen Energy, Vol. 42, pp. 26277—26288, 2017
  107. A novel dynamic framework for subgrid scale parametrization of mesoscale eddies in quasigeostrophic turbulent flows
    Romit Maulik and Omer San
    Computers & Mathematics with Applications, Vol. 74, No. 3, pp. 420—445, 2017
  108. Learning-based robust stabilization for reduced-order models of 2D and 3D Boussinesq equations
    Mouhacine Benosman, Jeff Borggaard, Omer San and Boris Kramer
    Applied Mathematical Modelling, Vol. 49, pp. 162—181, 2017
  109. Resolution and energy dissipation characteristics of implicit LES and explicit filtering models for compressible turbulence
    Romit Maulik and Omer San
    Fluids, Vol. 2, No. 2, pp. 14, 2017
  110. A dynamic framework for functional parameterisations of the eddy viscosity coefficient in two-dimensional turbulence
    R. Maulik and O. San
    International Journal of Computational Fluid Dynamics, Vol. 31, No. 2, pp. 69—92, 2017
  111. A stable and scale-aware dynamic modeling framework for subgrid-scale parameterizations of two-dimensional turbulence
    Romit Maulik and Omer San
    Computers & Fluids, Vol. 158, pp. 11—38, 2017
  112. A dynamic subgrid-scale modeling framework for Boussinesq turbulence
    Romit Maulik and Omer San
    International Journal of Heat and Mass Transfer, Vol. 108, pp. 1656—1675, 2017
  113. Dynamic modeling of the horizontal eddy viscosity coefficient for quasigeostrophic ocean circulation problems
    Romit Maulik and Omer San
    Journal of Ocean Engineering and Science, Vol. 1, No. 4, pp. 300—324, 2016
  114. Numerical assessments of ocean energy extraction from western boundary currents using a quasi-geostrophic ocean circulation model
    Omer San
    International Journal of Marine Energy, Vol. 16, pp. 12—29, 2016
  115. Analysis of low-pass filters for approximate deconvolution closure modelling in one-dimensional decaying Burgers turbulence
    O. San
    International Journal of Computational Fluid Dynamics, Vol. 30, No. 1, pp. 20—37, 2016
  116. Principal interval decomposition framework for POD reduced-order modeling of convective Boussinesq flows
    O. San and J. Borggaard
    International Journal for Numerical Methods in Fluids, Vol. 78, No. 1, pp. 37—62, 2015
  117. A stabilized proper orthogonal decomposition reduced-order model for large scale quasigeostrophic ocean circulation
    Omer San and Traian Iliescu
    Advances in Computational Mathematics, Vol. 41, No. 5, pp. 1289—1319, 2015
  118. A novel high-order accurate compact stencil Poisson solver: application to cavity flows
    Omer San
    International Journal of Applied Mechanics, Vol. 7, No. 1, pp. 1550006, 2015
  119. A posteriori analysis of low-pass spatial filters for approximate deconvolution large eddy simulations of homogeneous incompressible flows
    Omer San, Anne E. Staples and Traian Iliescu
    International Journal of Computational Fluid Dynamics, Vol. 29, No. 1, pp. 40—66, 2015
  120. Evaluation of Riemann flux solvers for WENO reconstruction schemes: Kelvin—Helmholtz instability
    Omer San and Kursat Kara
    Computers & Fluids, Vol. 117, pp. 24—41, 2015
  121. A dynamic eddy-viscosity closure model for large eddy simulations of two-dimensional decaying turbulence
    O. San
    International Journal of Computational Fluid Dynamics, Vol. 28, No. 6, pp. 363—382, 2014
  122. Numerical assessments of high-order accurate shock capturing schemes: Kelvin—Helmholtz type vortical structures in high-resolutions
    Omer San and Kursat Kara
    Computers & Fluids, Vol. 89, pp. 254—276, 2014
  123. Proper orthogonal decomposition closure models for fluid flows: Burgers equation
    Omer San and Traian Iliescu
    International Journal of Numerical Analysis & Modeling, Series B, Vol. 5, pp. 217—237, 2014
  124. A coarse-grid projection method for accelerating incompressible flow computations
    Omer San and Anne E Staples
    Journal of Computational Physics, Elsevier, Vol. 233, pp. 480—508, 2013
  125. An efficient coarse grid projection method for quasigeostrophic models of large-scale ocean circulation
    Omer San and Anne E. Staples
    International Journal for Multiscale Computational Engineering, Vol. 11, No. 5, pp. 463—495, 2013
  126. Approximate deconvolution large eddy simulation of a stratified two-layer quasigeostrophic ocean model
    Omer San, Anne E. Staples and Traian Iliescu
    Ocean Modelling, Vol. 63, pp. 1—20, 2013
  127. Stationary two-dimensional turbulence statistics using a Markovian forcing scheme
    Omer San and Anne E. Staples
    Computers & Fluids, Vol. 71, pp. 1—18, 2013
  128. An improved model for reduced-order physiological fluid flows
    Omer San and Anne E. Staples
    Journal of Mechanics in Medicine and Biology, Vol. 12, No. 3, pp. 1250052, 2012
  129. Dynamics of pulsatile flows through elastic microtubes
    Omer San and Anne E. Staples
    International Journal of Applied Mechanics, Vol. 4, No. 1, pp. 1250006, 2012
  130. High-order methods for decaying two-dimensional homogeneous isotropic turbulence
    Omer San and Anne E. Staples
    Computers & Fluids, Vol. 63, pp. 105—127, 2012
  131. Approximate deconvolution large eddy simulation of a barotropic ocean circulation model
    Omer San, Anne E Staples, Zhu Wang and Traian Iliescu
    Ocean Modelling, Elsevier, Vol. 40, No. 2, pp. 120—132, 2011
  132. Size and expansion ratio analysis of micro nozzle gas flow
    Omer San, Ilhan Bayraktar and Tuba Bayraktar
    International Communications in Heat and Mass Transfer, Vol. 36, No. 5, pp. 402—411, 2009

Books

  1. Recent numerical advances in fluid mechanics
    Omer San
    ISBN 978-3-03936-402-2, MDPI, 2020

Book Chapters

  1. Digital Twins: Challenges and Enablers
    Omer San
    Machine Learning for Fluid Mechanics: Analysis, Modeling, Control and Closures, VKI Lecture Series, von Karman Institute Lecture Series, pp. 323—332, 2025
  2. Reduced Order Model Closures: A Brief Tutorial
    William Snyder, Changhong Mou, Honghu Liu, Omer San, Raffaella De Vita and Traian Iliescu
    Recent Advances in Mechanics and Fluid-Structure Interaction with Applications, 978-3-031-14323-6, Springer Nature, pp. 167—193, 2022
  3. Forward Sensitivity Analysis of the FitzHugh–Nagumo System: Parameter Estimation
    Shady E. Ahmed, Omer San and S. Lakshmivarahan
    Advances in Nonlinear Dynamics, Springer Nature, pp. 93—103, 2022
  4. Psychrometric Performance Testing for HVAC&R Components and Equipment
    Onur Kurtulus, Charles K. Bach, Omer San, Romit Maulik, Davide Ziviani, Craig R. Bradshaw and Eckhard A. Groll
    The Art of Measuring in Thermal Sciences, CRC Press—Taylor and Francis, pp. 215—238, 2020

Conference Papers

  1. Learning Nonlinear Six-DoF Re-Entry Dynamics With Neural Ordinary Differential Equations
    Bipin Tiwari, Ashraf K Kassem, Shafi Al Salman Romeo, Lamisa Musharrat, Kursat Kara and Omer San
    AIAA Aviation 2026 Forum, Paper ID: AIAA 2026-4393
  2. Epistemic Uncertainty Analysis in GPR-Based Modeling of Pitch Damping Sum for 1 DOF Reentry Vehicle Dynamics
    B. Tiwari, A. K. Kassem, S. A. S. Romeo, K. Kara and Omer San
    AIAA Aviation Forum and ASCEND 2025, Paper ID: AIAA 2025-3770
  3. Nonlinear Parameter Estimation Model for Dynamic Stability Analysis and Uncertainty Quantification of Six-Degree-of-Freedom Atmospheric Entry Capsules
    A. K. Kassem, F. Oz, S. A. S. Romeo, B. Tiwari, Omer San and K. Kara
    AIAA SciTech 2025 Forum, Paper ID: AIAA 2025-0677
  4. Trajectory Reconstruction of Blunt Body Capsules From Ballistic Range Testing Data Using Multi-Fidelity Gaussian Processes
    S. A. S. Romeo, F. Oz, A. K. Kassem, B. Tiwari, Omer San and K. Kara
    AIAA SciTech 2025 Forum, Paper ID: AIAA 2025-0884
  5. Optimizing Markov Chain Initial Conditions for Studying Blunt Body Reentry Dynamics Using Differential Evolution
    B. Tiwari, F. Oz, A. K. Kassem, S. A. S. Romeo, K. Kara and Omer San
    AIAA SciTech 2025 Forum, Paper ID: AIAA 2025-0679
  6. Reconstructing the Equations of Motion of Atmospheric Entry Vehicle Using High-Order Approach
    A. K. Kassem, F. Oz, S. A. S. Romeo, Omer San and K. Kara
    AIAA Aviation Forum and ASCEND 2024, Paper ID: AIAA 2024-4347
  7. Physics Informed Data Fusion Model for Uncertainty Quantification in Atmospheric Entry Vehicle Dynamic Stability
    S. A. S. Romeo, F. Oz, A. K. Kassem, Omer San and K. Kara
    AIAA Aviation Forum and ASCEND 2024, Paper ID: AIAA 2024-4446
  8. Using Data Fusion to Analyze Dynamic Stability of Atmospheric Entry Vehicles
    F. Oz, S. A. S. Romeo, A. K. Kassem, Omer San and K. Kara
    AIAA Aviation Forum and ASCEND 2024, Paper ID: AIAA 2024-4445
  9. Digital Twin for Wind Energy: Latest Updates From the NorthWind Project
    Adil Rasheed, F. Stadtmann, E. Fonn, Mandar Tabib, V. Tsiolakis, B. Panjwani, K. A. Johannessen, Trond Kvamsdal, Omer San, J. O. Tande, I. Barstad, T. Christiansen, E. Rishoff, L. Frøyd and T. Rasmussen
    American Society of Mechanical Engineers (ASME), Vol. 87783, pp. V001T01A045, 2024
  10. Hybrid analysis and modeling as an enabler for digital twins
    Adil Rasheed, Trond Kvamsdal and Omer San
    The 8th European Congress on Computational Methods in Applied Sciences and Engineering, Oslo, Norway, on 5th — 9th of June, 2022, pp. 22—26, 2022
  11. Sketching Methods for Dynamic Mode Decomposition in Spherical Shallow Water Equations
    Shady E. Ahmed, Omer San, Diana A. Bistrian and Ionel M. Navon
    AIAA SciTech 2022, San Diego, CA, 3–-7 January 2022, Paper ID: AIAA 2022-2325
  12. Hyperparameter Search using the Genetic Algorithm for Surrogate Modeling of Geophysical Flows
    Suraj Pawar, Omer San and Gary G Yen
    AIAA SciTech 2022, San Diego, CA, 3-–7 January 2022, Paper ID: AIAA 2022-0459
  13. Hybrid analysis and modeling for next generation of digital twins
    Suraj Pawar, Shady E. Ahmed, Omer San and Adil Rasheed
    IOP Publishing, Vol. 2018, No. 1, pp. 012031, 2021
  14. A non-intrusive parametric reduced order model for urban wind flow using deep learning and Grassmann manifold
    Mandar V Tabib, Suraj Pawar, Shady E. Ahmed, Adil Rasheed and Omer San
    IOP Publishing, Vol. 2018, No. 1, pp. 012038, 2021
  15. Comparative study of sequential data assimilation methods for the Kuramoto-Sivashinsky equation
    Suraj Pawar and Omer San
    AIAA SciTech 2021, Virtual Event, Paper ID: AIAA 2021-1749
  16. Nonlinear filtering for simultaneous state correction and eddy viscosity estimation in computational fluid dynamics
    Shady E. Ahmed, Omer San and Imraan Faruque
    AIAA SciTech 2021, Virtual Event, Paper ID: AIAA 2021-1332
  17. Forward sensitivity analysis of the FitzHugh-Nagumo system
    Shady E. Ahmed, Omer San and Sivaramakrishnan Lakshmivarahan
    International Nonlinear Dynamics Conference, NODYCON 2021, Virtual Event, February 16-19, 2021
  18. Light induced bacterial deactivation using graphene quantum dot
    Ermek Belekov, Lauren Cooper, Khomidkhodza Kholikov, Omer San and Ali O Er
    International Society for Optics and Photonics, Vol. 11220, pp. 112200E, 2020
  19. GANs enabled super-resolution reconstruction of wind field
    Duy Tan Tran, Haakon Robinson, Adil Rasheed, Omer San, Mandar Tabib and Trond Kvamsdal
    IOP Publishing, Vol. 1669, No. 1, pp. 012029, 2020
  20. Reduced order modeling of fluid flows: Machine learning, Kolmogorov barrier, closure modeling, and partitioning (Invited)
    Shady E. Ahmed, Suraj Pawar, Omer San and Adil Rasheed
    2020 AIAA AVIATION Forum and Exposition, Virtual Event, June 15—19, 2020
  21. An Update on the Evaluation of Air Mixer Performance (RP-1733)(VC-20-A006)
    Hyunjin Park, Christian Bach and Omer San
    ASHRAE Virtual Conference, 2020, pp. 20—22
  22. Hybrid modeling as an enabler for big data cybernetics
    Adil Rasheed, Omer San, Haakon Robinson and Trond Kvamsdal
    The 32nd Nordic Seminar on Computational Mechanics, Oulu, Finland, October 24—25, 2019
  23. Improvement of unitary equipment and heat exchanger testing methods
    M. Yeam Hossain, Romit Maulik, H. Park, M. Ahmed, Christian Konrad Bach and Omer San
    ASHRAE Annual Conference, Kansas City, KS, June 22—26, 2019, pp. 214—221
  24. Effect of inlet duct design on fan performance of indoor air handling unit
    M. Yeam Hossain, Christian Konrad Bach, Omer San and Ardiyansyah Yatim
    ASHRAE Annual Conference, Kansas City, KS, June 22—26, 2019, pp. 40—42
  25. Optimal control of heat transfer in unsteady Stokes flows
    Weiwei Hu and Omer San
    57th IEEE Conference on Decision and Control, Miami Beach, FL, December 17—19, 2018, pp. 3752—3757
  26. Formation of two-way shape memory effect in NiTi alloy using pulsed laser irradiation
    Saidjafarzoda Ilhom, Khomidkhodzha Kholikov, Peizhen Li, Dovletgeldi Seyitliyev, Zachary Thomas, Duvall Roberts, Omer San, Haluk E Karaca and Ali Oguz Er
    SPIE LASE, 2018, San Francisco, CA, 27 January — 1 February 2018, Vol. 10520, pp. 105200V
  27. A computational investigation of the effect of ground clearance in vertical ducting systems-ASHRAE RP-1743
    Romit Maulik, Omer San and Christian Konrad Bach
    Paper 3586, International Refrigeration and Air-Conditioning Conference, Purdue 2018, Herrick Conferences, Purdue University, West Lafayette, IN, July 9—12, 2018
  28. Effect of inlet duct and damper design on fan performance and static pressure measurements (ASHRAE RP 1743)
    M. Yeam Hossain, Omer San and Christian Konrad Bach
    Paper 2659, International Refrigeration and Air-Conditioning Conference, Purdue 2018, Herrick Conferences, Purdue University, West Lafayette, IN, July 9—12, 2018
  29. Basis selection and closure for POD models of convection dominated Boussinesq flows
    Omer San and Jeff Borggaard
    21st International Symposium on Mathematical Theory of Networks and Systems, Groningen, Netherlands, July 7—11, 2014
  30. Comparing piezoelectric and electroosmotic micropumps for biomedical applications
    Omer San, S. E. Yalcin and O. Baysal
    2008 ASME International Mechanical Engineering Congress and Exposition, Boston, MA, October 31—November 6, 2008
  31. Numerical modeling of gas flow in converging-diverging micronozzles
    Omer San and I Bayraktar
    Paper ID: AIAA 2007-3986, 37th AIAA Fluid Dynamics Conference and Exhibit, Miami, FL, June 25—28 2007

Invited Talks

  1. Bridging physics-based and data-driven approaches for enhanced modeling
    Omer San
    Statistics and Data Science Seminar Talk, Department of Mathematics, University of Tennessee, Knoxville, April 24, 2025
  2. Digital Twins: Challenges and Enablers
    Omer San
    von Karman Institute / ULB Lecture Series, Machine Learning for Fluid Mechanics: Analysis, Modeling, Control and Closures, January 29—February 2, 2024
  3. Hybrid physics-data analysis and modeling: an inductive bias perspective
    Omer San
    Machine Learning + X seminars, The Crunch Group, Brown University, January 13, 2023
  4. Hybrid physics-data analysis and modeling: an inductive bias perspective
    Omer San
    SIAM SEAS, Virginia Tech, March 25, 2023
  5. Hybrid physics-data analysis and modeling: a key technology for developing digital twins
    Omer San
    Mechanical Engineering Fall Seminar Series, Rice University, November 30, 2022
  6. Hybrid modeling in fluid dynamics
    Omer San
    Harvard Widely Applied Mathematics (WAM) Seminar Talk, The Harvard John A. Paulson School of Engineering and Applied Sciences, November 10, 2022
  7. Hybrid physics-data modeling in fluid dynamics
    Omer San
    e-Seminar on Scientific Machine Learning, https://scientific-ml.org/, October 23, 2022
  8. The prospects of hybrid analysis and modeling in fluid dynamics
    Omer San
    The 1st International Forum for Artificial Intelligence in Mechanical Engineering (IFAIME 2022), July 25—30, 2022
  9. Hybrid analysis and modeling
    Omer San
    Center of Excellence Collaboration Workshop, Trondheim, Norway, May 26, 2021
  10. Data-driven closure modeling of fluid flows
    Omer San
    Department of Scientific Computing, Florida State University, January 31, 2020
  11. Data-driven closure modeling in transport phenomena
    Omer San
    Graduate Seminar Series, The McDougall School of Petroleum Engineering, University of Tulsa, Tulsa, OK, February 14, 2020

Conference Presentations

  1. FNO-GCD-KF: A Fourier Neural Operator with Global-Context Decoder for Flow-Adaptive Covariance Estimation in Geophysical Data Assimilation
    Muhammad Abid, Arth Sojitra and Omer San
    CADRE-EPIC Data Assimilation Training Workshop, University of Oklahoma, Norman, OK, June 1-5, 2026
  2. Superresolving Nonlinear PDE Dynamics with latent-space Ensemble Filtering for Turbulence Modeling and Flow Control
    Mrigank Dhingra and Omer San
    78th Annual Meeting of the APS Division of Fluid Dynamics, Houston, Texas, November 23-25, 2025
  3. Numerical Assessments of Data Assimilation Methods for High-Speed Flows
    Bipin Tiwari, Mrigank Dhingra, Arth Sojitra and Omer San
    78th Annual Meeting of the APS Division of Fluid Dynamics, Houston, Texas, November 23-25, 2025
  4. Fourier-Embedded Deep Operator Networks for High-Fidelity Parametric PDE Surrogates and Inverse Optimization
    Arth Sojitra, Mrigank Dhingra and Omer San
    78th Annual Meeting of the APS Division of Fluid Dynamics, Houston, Texas, November 23-25, 2025
  5. Data-Efficient Neural Operator Surrogates for Nonlinear Pitch Dynamics of Blunt-Body Reentry Vehicles
    B. Tiwari, A. K. Kassem, S. A. S. Romeo, D. Ekelschot, C. Kazemba, K. Kara and O. San
    Data Meets Dynamics: Workshop on Data Assimilation for Complex Systems and Applications, Madison, WI, August 21—22, 2025
  6. A Parametric ROM Framework for Inverse Problems in High-Speed Flows
    B. Tiwari and O. San
    SIAM Conference on Computational Science and Engineering (CSE25), Fort Worth, TX, USA, March 3—7, 2025
  7. A Y-network encoder-decoder model for predicting vorticity fields from kinetic energy spectra in 2D decaying turbulence
    M. Dhingra, O. San and A. Staples
    77th Annual Meeting of the APS Division of Fluid Dynamics, Salt Lake City, Utah, November 24—26, 2024
  8. Meta-Learning for Dynamic Stability Analysis of Atmospheric Entry Vehicles
    S. A. S. Romeo, F. Oz, A. K. Kassem, O. San and K. Kara
    77th Annual Meeting of the APS Division of Fluid Dynamics, Salt Lake City, Utah, November 24—26, 2024
  9. Dynamic Mode Decomposition of Wake Flow Structures for Supersonic Oscillating Genesis Atmospheric Entry Capsule
    A. K. Kassem, S. A. S. Romeo, B. Tiwari, O. San and K. Kara
    77th Annual Meeting of the APS Division of Fluid Dynamics, Salt Lake City, Utah, November 24—26, 2024
  10. Harnessing the power of natural language processing techniques for multiscale turbulence simulation
    M. Dhingra, O. San and A. Staples
    76th Annual Meeting of the APS Division of Fluid Dynamics, Washington, DC, November 19—21, 2023
  11. Markov Chain Monte Carlo-Based Parameter Estimation for Entry Descend and Landing Applications
    F. Oz, S. A. S. Romeo, A. K. Kassem, K. Kara and O. San
    76th Annual Meeting of the APS Division of Fluid Dynamics, Washington, DC, November 19—21, 2023
  12. A deep learning based closure model for the multiscale evolution of Burgers turbulence
    M. Dhingra, A. Staples and O. San
    75th Annual Meeting of the APS Division of Fluid Dynamics, Indianapolis, IN, November 20—22, 2022
  13. Inductive bias and information fusion with concatenated neural networks
    O. San, S. Pawar, P. Vedula, A. Rasheed and T. Kvamsdal
    75th Annual Meeting of the APS Division of Fluid Dynamics, Indianapolis, IN, November 20—22, 2022
  14. Nonintrusive reduced order modeling of convective Boussinesq flows
    P. H. Dabaghian and O. San
    7th Annual Meeting of SIAM Central States Section, October 1—2, 2022, Oklahoma State University, Stillwater, OK (SIAM-CSS 2022)
  15. Nonlinear proper orthogonal decomposition approach for modeling Rayleigh Bénard convection
    S. Akbari and O. San
    7th Annual Meeting of SIAM Central States Section, October 1—2, 2022, Oklahoma State University, Stillwater, OK (SIAM-CSS 2022)
  16. Automatic Mixed-Precision (AMP) Computational Fluid Dynamics (CFD)
    M. Zomorodiyan and O. San
    7th Annual Meeting of SIAM Central States Section, October 1—2, 2022, Oklahoma State University, Stillwater, OK (SIAM-CSS 2022)
  17. Fluid flow modeling in elastic networking tubes
    S. Romeo and O. San
    7th Annual Meeting of SIAM Central States Section, October 1—2, 2022, Oklahoma State University, Stillwater, OK (SIAM-CSS 2022)
  18. Hierarchical learning to reduced order modeling
    S. E. Ahmed, O. San, A. Rasheed, T. Iliescu and A. Veneziani
    AIAA Aviation Forum, Chicago, Illinois, 27 June—1 July 2022
  19. Real-Time Shape Optimization of the Total Cavopulmonary Connection in Fontan Surgical Planning Via Reduced Order Modeling
    I. Shah, L. Dasi, T. Iliescu, O. San and A. Veneziani
    2022 Summer Biomechanics, Bioengineering, and Biotransport Conference, June 20—23, 2022, Eastern Shore, Maryland
  20. Physics-constrained deep learning for subgrid modeling in geophysical flows
    S. Pawar and O. San
    4th MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, March 30, 2022
  21. Hierarchical learning to generate surrogate models in fluid dynamics
    S. E. Ahmed and O. San
    4th MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, March 30, 2022
  22. Nonlinear proper orthogonal decomposition for compressible flows
    M. Zomorodiyan and O. San
    4th MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, March 30, 2022
  23. Modeling networking flows in elastic tubes
    S. Romeo and O. San
    4th MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, March 30, 2022
  24. Towards physics-aware model reduction and data compression
    S. E. Ahmed, S. Pawar, O. San and A. Rasheed
    The NSF AI Planning Institute for Data Driven Physics Workshop on AI Super-Resolution Simulations: from Climate Science to Cosmology, Carnegie Mellon University, Pittsburgh, PA, February 23—25, 2022
  25. Physics-guided machine learning for surrogate modeling in fluid mechanics
    S. Pawar, O. San and A. Rasheed
    74th Annual Meeting of the APS Division of Fluid Dynamics, Phoenix, AZ, November 21—23, 2021
  26. Physics-Guided Machine Learning Variational Multiscale Reduced Order Models
    S. Ahmed, O. San, A. Rasheed, A. Veneziani and T. Iliescu
    74th Annual Meeting of the APS Division of Fluid Dynamics, Phoenix, AZ, November 21—23, 2021
  27. Combining machine learning and data assimilation for hybrid multi-level variational multiscale reduced order models
    S. E. Ahmed, O. San, T. Iliescu and A. Veneziani
    The Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology Conference (MMLDT-CSET 2021), San Diego, CA September 26—29, 2021
  28. A hybrid variational multiscale and machine learning approach for nonlinear model order reduction
    S. Ahmed, O. San, A. Veneziani and T. Iliescu
    44th SIAM Southeastern Atlantic Section Conference (SIAM-SEAS), Auburn, AL, September 18—19, 2021
  29. Interface Learning: Towards Seamless Integration of Multi-scale, Multi-physics and Multi-fidelity (M3) Models
    S. Ahmed, S. Pawar, O. San and A. Rasheed
    16th U.S. National Congress on Computational Mechanics (USNCCM16), Virtual Event, July 25—29, 2021
  30. Physics guided machine learning in fluid dynamics
    S. Pawar, O. San and A. Rasheed
    16th U.S. National Congress on Computational Mechanics (USNCCM16), Virtual Event, July 25—29, 2021
  31. Interface learning for coupling full and reduced order models in multifidelity simulations
    S. E. Ahmed, O. San, K. Kara, R. Younis and A. Rasheed
    40th ASME/AIAA Online Regional Symposium [Virtual], April 3, 2021
  32. Deep learning approaches for subgrid scale parameterization in chaotic dynamical systems
    S. Pawar and O. San
    40th ASME/AIAA Online Regional Symposium [Virtual], April 3, 2021
  33. Data assimilation for dynamic estimate of closure effect in reduced order models
    S. E. Ahmed, O. San and A. Rasheed
    SIAM CSE21 [Virtual], March 1—5, 2021
  34. Interface closure in multi-fidelity computing via deep learning
    S. Pawar, S. Ahmed and O. San
    SIAM CSE21 [Virtual], March 1—5, 2021
  35. Data assimilation assisted neural network parameterizations for subgrid processes in multiscale systems
    S. Pawar and O. San
    73rd Annual Meeting of the APS Division of Fluid Dynamics, Virtual Event, 2020
  36. Interface learning paradigms for multi-scale and multi-physics systems
    S. Ahmed, S. Pawar and O. San
    73rd Annual Meeting of the APS Division of Fluid Dynamics, Virtual Event, 2020
  37. Direct numerical simulation of turbulent flows in Python
    S. Pawar and O. San
    Poster presented at the Coalition for Advancing Digital Research & Education (CADRE) conference, Oklahoma State University, Stillwater, OK, April 17, 2020
  38. Augmentation of nonlinear reduced order models via machine learning
    S. E. Ahmed and O. San
    3rd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, February 28, 2020
  39. Hybrid analysis and modeling paradigm for reduced order modeling of fluid flows with unknown physics
    S. Pawar, S. E. Ahmed and O. San
    Poster presented at the 3rd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, February 28, 2020
  40. Blind deconvolution of turbulent flows using super-resolution reconstruction
    H. Vaddireddy and O. San
    Poster presented at the 3rd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, February 28, 2020
  41. Reduced order modeling of shallow water equations using dynamic mode decomposition
    K. Bhar and O. San
    Poster presented at the 3rd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, February 28, 2020
  42. A nonintrusive reduced order modelling of magnetic skyrmions
    M. Annaorazov, S. Ahmed, O. San and E. Turgut
    APS March Meeting 2020, Denver, Colorado, March 2—6, 2020
  43. Data-driven modeling for fluid dynamics: Turbulence closure, model order reduction, and super-resolution
    S. Pawar, S. Ahmed, H. Vaddireddy, O. San, R. Maulik, D. T. Tran and A. Rasheed
    Poster presented at the NSF Workshop on Exuberance of Machine Learning in Transport Phenomena, Southern Methodist University, Dallas, TX, February 10—11, 2020
  44. Deep learning based sub-grid scale closure for LES of Kraichnan turbulence
    S. Pawar, O. San and A. Rasheed
    72nd Annual Meeting of the APS Division of Fluid Dynamics, Seattle, WA, November 23—26, 2019
  45. LSTM based nonintrusive ROM of convective flows
    S. E. Ahmed, S. M. Rahman, O. San and A. Rasheed
    72nd Annual Meeting of the APS Division of Fluid Dynamics, Seattle, WA, November 23—26, 2019
  46. A symbolic regression approach for the development of high accuracy defect correction schemes
    H. Vaddireddy and O. San
    72nd Annual Meeting of the APS Division of Fluid Dynamics, Seattle, WA, November 23—26, 2019
  47. Deep reinforcement learning for path following and collision avoidance
    C. Sterud, H. Robinson, S. Moe, A. Rasheed and O. San
    5th Norwegian Big Data Symposium (NOBIDS) 2019, Trondheim, Norway, November 13, 2019
  48. Model discovery using deterministic symbolic regression
    H. Vaddireddy and O. San
    39th Oklahoma AIAA/ASME Symposium, University of Tulsa, Tulsa, OK, April 6, 2019
  49. Staggered reduced order model for shallow water equations: POD vs DMD
    S. E. Ahmed and O. San
    39th Oklahoma AIAA/ASME Symposium, University of Tulsa, Tulsa, OK, April 6,2019
  50. Numerical assessment of higher order compact scheme for Poisson equation
    S. Pawar and O. San
    39th Oklahoma AIAA/ASME Symposium, University of Tulsa, Tulsa, OK, April 6, 2019
  51. Improvement of air mixer performance for HVAC testing applications: CFD simulations (RP-1733)
    M. Ahmed, O. San and C. K. Bach
    39th Oklahoma AIAA/ASME Symposium, University of Tulsa, Tulsa, OK, April 6, 2019
  52. On the development of robust reduced order model frameworks for partial differential equation systems: current status and future prospects
    S. M. Rahman and O. San
    39th Oklahoma AIAA/ASME Symposium, University of Tulsa, Tulsa, OK, April 6, 2019
  53. Antimicrobial activity of sulphur-doped graphene quantum dots coupled with methylene blue for photodynamic therapy applications
    A. Er, K. Kholikov, L. Cooper, E. Belekov and O. San
    APS March Meeting 2019, Boston, MA, March 4—8, 2019
  54. Laser-induced shock wave-assisted patterning on NiTi shape memory alloys
    A. O. Er, C. Ottman, D. Sanford, E. Belekov, S. Ilhom, H. Karaca and O. San
    International Society for Optics and Photonics, SPIE LASE, San Francisco, CA, 4 March, 2019
  55. Data-driven filter estimation for the sub-grid modelling of Kraichnan turbulence
    R. Maulik, O. San, A. Rasheed and P. Vedula
    SIAM Conference on Computational Science and Engineering (CSE19), Spokane, WA, February 25—March 1, 2019
  56. A hybrid approach for model order reduction of barotropic quasi-geostrophic turbulence
    S. M. Rahman, O. San and A. Rasheed
    SIAM Conference on Computational Science and Engineering (CSE19), Spokane, WA, February 25—March 1, 2019
  57. Data-driven subgrid scale modeling of turbulence
    O. San, S. M. Rahman and A. Rasheed
    Poster presented at the DOE ASCR Applied Mathematics Principal Investigators’ (PI) Meeting, Rockville, MD January 29—30, 2019
  58. Data-driven deconvolution for the large eddy simulation of Kraichnan turbulence
    R. Maulik, O. San, A. Rasheed and P. Vedula
    71st Annual Meeting of the APS Division of Fluid Dynamics, Atlanta, GA, November 18—20, 2018
  59. A hybrid analytics paradigm combining physics-based modeling and data-driven modeling to accelerate incompressible flow solvers
    O. San, S. M. Rahman and A. Rasheed
    71st Annual Meeting of the APS Division of Fluid Dynamics, Atlanta, GA, November 18—20, 2018
  60. Bacterial deactivation by using graphene quantum dot as an effective photodynamic therapy agent
    E. Belekov, L. Cooper, K. Devarakonda, K. Kholikov, S. Ilhom, M. Smith, J. Monroe, O. San and A. Er
    85th Annual Meeting of the APS Southeastern Section, Knoxville, TN, November 8—10, 2018
  61. Physics-based artificial neural network formulations for LES of Kraichnan turbulence
    R. Maulik, O. San, A. Rasheed and P. Vedula
    2nd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, November 2, 2018
  62. Air mixer design guidelines using CFD analysis (ASHRAE, RP-1733)
    M. Ahmed, O. San and C. Bach
    2nd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, November 2, 2018
  63. Effect of inlet duct configuration on the fan performance of air handling units (ASHRAE RP-1743)
    M. Y. Hossain, C. Bach and O. San
    2nd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, November 2, 2018
  64. A review of designs and test strategies for air mixers (ASHRAE RP-1733)
    H. Park, C. Bach and O. San
    2nd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, November 2, 2018
  65. Hybrid analytics paradigm in fluid dynamics
    S. M. Rahman and O. San
    2nd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, November 2, 2018
  66. A survey of symbolic regression approaches to distill equations/models from big data
    H. Vaddireddy and O. San
    2nd MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, November 2, 2018
  67. An optimized discrete filtering framework for large eddy simulations
    S. M. Rahman and O. San
    38th Oklahoma AIAA/ASME Symposium, Oklahoma Christian University, Oklahoma City, OK, April 14, 2018
  68. Sub-filter scale nonlinear interaction modeling for LES using deep learning networks
    R. Maulik, E. Ozbenli, O. San and P. Vedula
    38th Oklahoma AIAA/ASME Symposium, Oklahoma Christian University, Oklahoma City, OK, April 14, 2018
  69. Reduced order framework for optimal control of nonlinear PDE
    N. Nelsen and O. San
    Poster presented at the Coalition for Advancing Digital Research & Education (CADRE) conference, Oklahoma State University, Stillwater, OK, April 17—18, 2018
  70. Nonlinear physics inference using artificial neural networks
    R. Maulik, E. Ozbenli, O. San and P. Vedula
    Poster presented at the Coalition for Advancing Digital Research & Education (CADRE) conference, Oklahoma State University, Stillwater, OK, April 17—18, 2018
  71. MPI implementation of Navier—Stokes equations
    S. M. Rahman and O. San
    Poster presented at the Coalition for Advancing Digital Research & Education (CADRE) conference, Oklahoma State University, Stillwater, OK, April 17—18, 2018
  72. One-step laser-induced hydrogen generation from graphite and coal in water
    K. Kholikov, D. Seyitliyev, B. Grant, O. San and A. Er
    APS March Meeting 2018, Los Angeles, CA, March 5—9, 2018
  73. A coarse grid projection multiscale method for turbulent geophysical flows
    A. E. Staples and O. San
    International Workshop on Complex Turbulent Flows, Tangier, Morocco, November 27—28, 2017
  74. A neural network approach for the blind deconvolution of turbulent flows
    R. Maulik and O. San
    70th Annual Meeting of the APS Division of Fluid Dynamics, Denver, CO, November 19—21, 2017
  75. Laser-induced hydrogen generation from graphite and coal
    K. Kholikov, D. Seyitliyev, B. Grant, O. San and A. Er
    84th Annual Meeting of the APS Southeastern Section, Milledgeville, GA, November 16—19, 2017
  76. Subfilter recovery for the turbulence modeling of large eddy simulations using sparse regression for blind deconvolution
    R. Maulik and O. San
    Poster presented at the MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, October 28, 2017
  77. CFD analysis of HVAC duct design and fittings
    M. Ahmed, O. San and C. Bach
    MAE Graduate Research Symposium, Oklahoma State University, Stillwater, OK, October 28, 2017
  78. Implicit LES modeling of stratified shear layer turbulence
    R. Maulik and O. San
    Poster presented at the Coalition for Advancing Digital Research & Education (CADRE) conference, Oklahoma State University, Stillwater, OK, April 11—12, 2017
  79. An implicit large eddy simulation framework based on wavelet adaptive mesh refinement
    R. Maulik, O. San and B. R.
    37th Oklahoma AIAA/ASME Symposium, Oral Roberts University, Tulsa, OK, April 15, 2017
  80. Artificial neural network models for model order reduction of nonlinear systems
    M. Ahmed and O. San
    37th Oklahoma AIAA/ASME Symposium, Oral Roberts University, Tulsa, OK, April 15, 2017
  81. Constitutive modeling in reduced order representation of hemodynamic flows
    W. Glenn and O. San
    37th Oklahoma AIAA/ASME Symposium, Oral Roberts University, Tulsa, OK, April 15, 2017
  82. An artificial neural network closure modeling framework for model order reduction of convective flows
    O. San and M. Ahmed
    SIAM Conference on Computational Science and Engineering (CSE17), Atlanta, GA, February 27—March 3, 2017
  83. A dynamic framework for subgrid-scale parametrization of mesoscale eddies in geophysical flows
    O. San and R. Maulik
    69th Annual Meeting of the APS Division of Fluid Dynamics, Portland, OR, November 20—22, 2016
  84. A dynamic hybrid subgrid-scale modeling framework for large eddy simulations
    R. Maulik and O. San
    69th Annual Meeting of the APS Division of Fluid Dynamics, Portland, OR, November 20—22, 2016
  85. An explicit filtering framework based on Perona-Malik anisotropic diffusion for shock capturing and subgrid scale modeling of Burgers’ turbulence
    R. Maulik and O. San
    69th Annual Meeting of the APS Division of Fluid Dynamics, Portland, OR, November 20—22, 2016
  86. Evaluation of explicit and implicit LES closures for Burgers turbulence
    R. Maulik and O. San
    36th Oklahoma AIAA/ASME Symposium, University of Oklahoma, Norman, April 16, 2016
  87. WAMR: An accurate predictive tool
    O. San, R. Behera, T. Grenga, K. Matous and S. Paolucci
    Poster presented at the Center for Shock Wave-processing of Advanced Reactive Materials, University of Notre Dame, Notre Dame, IN, November 5—6, 2014
  88. An efficient coarse grid projection method for quasi-geostrophic models of large-scale ocean circulation
    A. E. Staples and O. San
    66th Annual Meeting of the APS Division of Fluid Dynamics, Pittsburgh, PA, November 24—26, 2013
  89. Large eddy simulation of the quasi-geostrophic equations of oceanic flows
    T. Iliescu, O. San, Z. Wang, E. Foster and A. E. Staples
    American Geophysical Union Fall Meeting, San Francisco, CA, December 3—7, 2012
  90. A posteriori analysis of spatial filters for approximate deconvolution large eddy simulations of homogeneous incompressible flows
    A. E. Staples and O. San
    65th Annual Meeting of the APS Division of Fluid Dynamics, San Diego, CA, November 18—20, 2012
  91. A coarse-grid projection method for accelerating incompressible flow computations
    O. San and A. E. Staples
    64th Annual Meeting of the APS Division of Fluid Dynamics, Baltimore, MD, November 20—22, 2011
  92. Approximate deconvolution large eddy simulation of a barotropic ocean circulation model
    A. E. Staples and O. San
    64th Annual Meeting of the APS Division of Fluid Dynamics, Baltimore, MD, November 20—22, 2011
  93. A coarse-grid projection multiscale method for accelerating incompressible flow computations
    O. San and A. E. Staples
    Fall Fluid Mechanics Symposium, Virginia Tech, Blacksburg, VA, November 3, 2011
  94. Dynamics of pulsatile flows through elastic microtubes
    O. San and A. E. Staples
    63rd Annual Meeting of the APS Division of Fluid Dynamics, Long Beach, CA, November 21—23, 2010
  95. A global reduced-order distributed model for physiological fluid dynamics
    O. San and A. E. Staples
    Biomedical Engineering Society Annual Meeting, Austin, TX, October 6—9, 2010
  96. An algorithm for a reduced-order representation of physiological fluid dynamics
    O. San and A. E. Staples
    VT Symposium on Reduced-Order Modeling and System Identification, Blacksburg, VA, February 15, 2010
  97. A multigrid accelerated high-order compact fractional step method for unsteady incompressible viscous flows
    O. San and A. E. Staples
    62nd Annual Meeting of the APS Division of Fluid Dynamics, Minneapolis, MN, November 22—24, 2009
  98. An efficient algorithm for computing physiological fluid flows
    A. E. Staples and O. San
    62nd Annual Meeting of the APS Division of Fluid Dynamics, Minneapolis, MN, November 22—24, 2009
  99. An efficient model and algorithm for physiological fluid dynamics
    O. San and A. E. Staples
    Joint ASCE-ASME-SES Conference on Mechanics and Materials, Blacksburg, VA, June 24—27, 2009
  100. Multiscale modeling of physiological fluid dynamics
    O. San and A. E. Staples
    25th Annual Research Symposium and Exposition, Virginia Tech, Blacksburg, VA, March 25, 2009
  101. Numerical simulation of a low voltage electrokinetic micropump for microfluidic LOC devices
    O. San, S. E. Yalcin and O. Baysal
    AIAA Region I-MA Student Conference, University of Maryland, College Park, MD, April 11, 2008
  102. Numerical simulations of MEMS-based micropumps
    O. San and O. Baysal
    5th Annual Research Exposition, Old Dominion University, Norfolk, VA, April 9, 2008
  103. Numerical modeling of gas flow in converging-diverging micronozzles
    O. San and I. Bayraktar
    37th AIAA Fluid Dynamics Conference and Exhibit, Miami, FL, June 25—28, 2007
  104. Assessment of slip wall conditioning for gas flow simulation in micronozzles
    O. San and I. Bayraktar
    18th AIAA Computational Fluid Dynamics Conference, Miami, FL, June 25—28, 2007
  105. Numerical analysis of gas flow in micronozzles
    O. San
    AIAA Young Professional, Student and Education Conference, Johns Hopkins University, Baltimore, MD, November 10—11, 2006
  106. 2D unsteady incompressible Navier—Stokes solution of cavity flow
    O. San
    AIAA Region I-MA Student Conference, Penn State, University Park, PA, April 7—8, 2006