■ computational sciences ■ data-driven modeling ■ machine learning in physical systems ■ model reduction
Project | Description | Repository | Language | |
---|---|---|---|---|
🖥️ | RL SGS on Korali | Theory-driven reinforcement learning for sub-grid scale LES models of 2D turbulent | GitHub | Python (JAX) |
🌊 | Py2D | Python-Jax solver for 2D turbulence | GitHub | Python (JAX) |
🖥️ | LPINNs | Lagrangian physics-informed neural network | GitHub | Python (Pytorch) |
🖥️ | MEDIDA | Model Error Discovery with Interpretability and Data Assimilation | GitHub | Python |
🖥️ | MEDIDA_QG | Model Error Discovery with Interpretability and Data Assimilation for quasi-geostrophic turbulence | GitHub | Python (PyTorch) |
🖥️ | Physics Aware Auto-encoder | Manifold learning for large Kolmogorov n-width PDEs | GitHub | Matlab & Python (Keras) |
🦾 | LTV ROM Stabilization | An optimal feedback controller for linear time-varying reduced order models | Contact me | Matlab |
🌊 | Incompressible flow in a Lid-driven cavity | A control-volume-based finite element method | GitHub | Fortran 90 |
🌊 | Compressible flow on an airfoil | Roe's Riemann solver for Euler equations on unstructured grids | GitHub | Fortran 90 |
Summary of my resume
My PhD Thesis on ``Reduced order modeling of convection-dominated flows, dimensionality reduction and stabilization''
- A presentation at Rice University - MECH Seminar Series, Nov 2020
- Fully data-driven dimensionality reduction (Autoencoder approach):
- Print: AAAI-2021
- Repository: PhysicsAwareAE
- Poster: MLTP-2020
- Presentation: My YouTube Channel, presented at AAAI 2021, AAAI-2021
- Stabilization of time-varying reduced order models:
- Print: IJNME
- Repository: Contact me
- Presentation: My YouTube Channel, presented at MMLDT 2021
- Lagrangian dimensionality reduction:
- Preprint: arXiv
- Repository: Contact me