[Homepage] [Google Scholar] [ResearchGate]

I am currently a Researcher in Computational Science and Machine Learning at the National Renewable Energy Laboratory (NREL)

I work on scientific machine learning projects using mostly Tensorflow and sometimes Pytorch. I have developed generative modeling techniques for data augmentation, data reduction and rare event probability estimation.

I develop surrogate models using physics-informed neural nets to accelerate parameter identification for Li-ion battery models.

I also develop code for high-performance computing on CPU/GPU architectures. Lately, I have been developing HPC code for analytically reduced chemistry using symbolic mathematics.

I am also working on scaling up the generative modeling regularization techniques I developed to handle large atmospheric datasets

I develop tools generate OpenFOAM meshes that adapt to geometrical parameter variations. This is particularly useful for geometry optimization.

A tool box for journal quality plotting, for input parsing and progress bar display

Currently working on uncertainty quantification for Large eddy simulations. (Coming soon!)

I also develop fun projects to organize Secret Santa 🎅 remotely or settling intense Poker games ♠️.

I'm always happy to hear about new oppportunities!

malik[dot]hassanaly[at]nrel!dot!gov