■ 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

• A presentation at Rice University - MECH Seminar Series, Nov 2020

1. 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

2. Stabilization of time-varying reduced order models:

• Print: IJNME
• Repository: Contact me
• Presentation: My YouTube Channel, presented at MMLDT 2021

3. Lagrangian dimensionality reduction:

• Preprint: arXiv
• Repository: Contact me