| Highly-scalable GPU-accelerated compressible reacting flow solver for modeling high-speed flows R Bielawski, S Barwey, S Prakash, V Raman Computers & Fluids 265, 105972, 2023 | 64 | 2023 |
| Using machine learning to construct velocity fields from OH-PLIF images S Barwey, M Hassanaly, V Raman, A Steinberg Combustion Science and Technology 194 (1), 93-116, 2022 | 55 | 2022 |
| Multiscale Graph Neural Network Autoencoders for Interpretable Scientific Machine Learning S Barwey, V Shankar, V Viswanathan, R Maulik Journal of Computational Physics, 112537, 2023 | 49 | 2023 |
| Data-driven classification and modeling of combustion regimes in detonation waves S Barwey, S Prakash, M Hassanaly, V Raman Flow, Turbulence and Combustion 106 (4), 1065-1089, 2021 | 49 | 2021 |
| A neural network-inspired matrix formulation of chemical kinetics for acceleration on GPUs S Barwey, V Raman Energies 14 (9), 2710, 2021 | 48 | 2021 |
| A data-driven reduced-order model for stiff chemical kinetics using dynamics-informed training V Vijayarangan, HA Uranakara, S Barwey, RM Galassi, MR Malik, ... Energy and AI 15, 100325, 2024 | 37 | 2024 |
| An amrex-based compressible reacting flow solver for high-speed reacting flows relevant to hypersonic propulsion S Sharma, R Bielawski, O Gibson, S Zhang, V Sharma, AH Rauch, ... arXiv preprint arXiv:2412.00900, 2024 | 31 | 2024 |
| A generative adversarial network (GAN) approach to creating synthetic flame images from experimental data A Carreon, S Barwey, V Raman Energy and AI 13, 100238, 2023 | 29 | 2023 |
| Extracting information overlap in simultaneous OH-PLIF and PIV fields with neural networks S Barwey, V Raman, AM Steinberg Proceedings of the Combustion Institute 38 (4), 6241-6249, 2021 | 27 | 2021 |
| Experimental data-based reduced-order model for analysis and prediction of flame transition in gas turbine combustors S Barwey, M Hassanaly, Q An, V Raman, A Steinberg Combustion Theory and Modelling 23 (6), 994-1020, 2019 | 26 | 2019 |
| Data-based analysis of multimodal partial cavity shedding dynamics S Barwey, H Ganesh, M Hassanaly, V Raman, S Ceccio Experiments in Fluids 61 (4), 98, 2020 | 21 | 2020 |
| Detonation structure in the presence of mixture stratification using reaction-resolved simulations M Ullman, S Prakash, S Barwey, V Raman Combustion and Flame 264, 113427, 2024 | 17 | 2024 |
| Data-driven analysis of relight variability of jet fuels induced by turbulence M Hassanaly, Y Tang, S Barwey, V Raman Combustion and Flame 225, 453-467, 2021 | 15 | 2021 |
| Mesh-based super-resolution of fluid flows with multiscale graph neural networks S Barwey, P Pal, S Patel, R Balin, B Lusch, V Vishwanath, R Maulik, ... Computer Methods in Applied Mechanics and Engineering 443, 118072, 2025 | 12 | 2025 |
| Interpretable A-posteriori error indication for graph neural network surrogate models S Barwey, H Kim, R Maulik Computer Methods in Applied Mechanics and Engineering 433, 117509, 2025 | 12* | 2025 |
| Segmentation of high-speed flow fields using physics-informed clustering M Ullman, S Barwey, GS Lee, V Raman Applications in Energy and Combustion Science 15, 100181, 2023 | 12 | 2023 |
| Data-driven reduction and decomposition with time-axis clustering S Barwey, V Raman Proceedings of the Royal Society A 479 (2274), 20220776, 2023 | 11* | 2023 |
| Understanding latent timescales in neural ordinary differential equation models of advection-dominated dynamical systems AS Nair, S Barwey, P Pal, JF MacArt, T Arcomano, R Maulik Physica D: Nonlinear Phenomena 476, 134650, 2025 | 9 | 2025 |
| Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling S Barwey, R Balin, B Lusch, S Patel, R Balakrishnan, P Pal, R Maulik, ... SC24-W: Workshops of the International Conference for High Performance …, 2024 | 8 | 2024 |
| Importance of equivariant and invariant symmetries for fluid flow modeling V Shankar, S Barwey, Z Kolter, R Maulik, V Viswanathan arXiv preprint arXiv:2307.05486, 2023 | 8 | 2023 |
Venkat RamanJames Arthur Nicholls Collegiate Professor, University of MichiganVerified email at umich.edu
