| Deep-learning accelerated calculation of real-fluid properties in numerical simulation of complex flowfields PJ Milan, JP Hickey, X Wang, V Yang Journal of Computational Physics, 1-39, 2021 | 26 | 2021 |
| Data-driven model reduction of multiphase flow in a single-hole automotive injector PJ Milan, R Torelli, B Lusch, GM Magnotti Atomization and Sprays, 2020 | 18 | 2020 |
| Accelerating the generation of static coupling injection maps using a data-driven emulator S Mondal, R Torelli, B Lusch, PJ Milan, GM Magnotti SAE International Journal of Advances and Current Practices in Mobility 3 …, 2021 | 13 | 2021 |
| Low‐Cost Rotating Experimentation in Compressor Aerodynamics Using Rapid Prototyping M Michaud, PJ Milan, HD Vo International Journal of Rotating Machinery 2016 (1), 8518904, 2016 | 13 | 2016 |
| Accelerating numerical simulations of supercritical fluid flows using deep neural networks PJ Milan, X Wang, JP Hickey, Y Li, V Yang AIAA Scitech 2020 Forum, 1157, 2020 | 7 | 2020 |
| Time-efficient methods for real fluid property evaluation in numerical simulation of chemically reacting flows PJ Milan, Y Li, X Wang, S Yang, W Sun, V Yang US National Combustion Meeting 11, 71TF-0396, 2019 | 7 | 2019 |
| Data-Driven Modeling of Large-Eddy Simulations for Fuel Injector Design PJ Milan, S Mondal, R Torelli, B Lusch, R Maulik, GM Magnotti AIAA SciTech 2021, 1-15, 2021 | 4 | 2021 |
| Flame dynamics sensitivity to turbulent combustion models in a swirl spray combustor PJ Milan, R Ranjan, A Panchal, S Menon 53rd AIAA/SAE/ASEE Joint Propulsion Conference, 5079, 2017 | 4 | 2017 |
| Enabling real-time adaptation of machine learning models at x-ray Free Electron Laser facilities with high-speed training optimized computational hardware PJ Milan, H Rong, C Michaud, N Layad, Z Liu, R Coffee Frontiers in Physics 10, 958120, 2022 | 2 | 2022 |
| A novel surrogate model for emulation of bi-fluid swirl injector flow dynamics Y Li, X Wang, YH Chang, PJ Milan, V Yang AIAA Scitech 2020 Forum, 1070, 2020 | 2 | 2020 |
| Modeling of saw-tooth DBD plasma actuators for flow control simulations PJ Milan, F Demers, HD Vo 45th AIAA Fluid Dynamics Conference, 2467, 2015 | 2 | 2015 |
| Build enterprise generative AI apps using Llama-3 at 1,000 tokens/s on the SambaNova AI platform PJ Milan, VB Krishna https://www.ai.engineer/worldsfair/2024/schedule/build-enterprise-generative …, 2024 | | 2024 |
| Programming Novel AI Accelerators for Scientific Computing with Hands-On GPT Models M Emani, PJ Milan, Z Claire, A Tsyplikhin, L Tran, S Shanmugavelu, ... https://sc23.conference-program.com/presentation/?id=tut139&sess=sess212, 2023 | | 2023 |
| Data-Driven Surrogate Modeling Approaches for Parametric Prediction and Uncertainty Quantification of Fluid Flows W Ding, PJ Milan, V Yang AIAA SCITECH 2023 Forum, 2043, 2023 | | 2023 |
| Programming Novel AI Accelerators for Scientific Computing with Hands-On BERT Models M Emani, PJ Milan, C Orozco Bohorquez, A Tsyplikhin, V Godsoe, J Chen, ... https://sc22.supercomputing.org/presentation/?id=tut151&sess=sess221, 2022 | | 2022 |
| Deep-Learning-Enhanced Multiphysics Flow Computations for Propulsion Applications PJ Milan Georgia Institute of Technology, 2021 | | 2021 |
| Three-dimensional investigation of fluid dynamics in a rocket engine injector at supercritical pressure PJ Milan, X Wang, V Yang ILASS-Americas 2021, 1-10, 2021 | | 2021 |
| Data-driven deep learning surrogates for parametric prediction of reacting flows PJ Milan, GM Magnotti, V Yang ILASS-Americas 2021, 1-13, 2021 | | 2021 |
| Deep-Learning Enhanced Multiphysics Flow Computations for Propulsion Applications PJ Milan Georgia Institute of Technology, 2021 | | 2021 |
| Machine Learning Approaches for Computational Fluid Dynamics of Supercritical Fluid Flows PJ Milan, X Wang, Y Li, V Yang ILASS-ASIA 2020, 1-9, 2020 | | 2020 |
Vigor YangGeorgia Institute of Technology在 gatech.edu 的电子邮件经过验证
