Bio
I am currently a researcher in AI & physics-based modeling at the National Laboratory of the Rockies (NLR). I earned my Ph.D. from the University of Michigan in Aerospace Engineering.
My work revolves around making physics-based simulations able to inform decision-making. I contribute primarily to research in simulation-based inference, inverse methods, uncertainty propagation and scientific machine learning.
Occasionally, I also develop physics-based models using computational fluid dynamics (CFD) for reacting and multiphase flows.
I work on different applications: Li-ion batteries, atmospheric flows, power-system security, bioreactors, gas turbines and engines.
Most of my methods are available as open-source software — and I try to make sure all my publications are freely accessible. If any paper of mine is not accessible to you, please shoot me an email!
Start here
- Research — what I work on, with cool figures
- Software — tools you can install and run today
- Publications — 40+ papers, open access wherever possible
- CV — résumé (2 pages) · full academic CV
Get in touch
I’m always glad to talk about uncertainty quantification, CFD, scientific machine learning or an interesting research challenge — including about open roles. Reach me a malik.hassanaly@gmail.com.
In the news
- Making the Uncertain (More) Certain, NLR, 2023.
- AI improves efficiency of battery diagnostics, NLR, 2025
- Podcast discussing my work on battery health diagnostics, Peaks to power podcast (skip to 6:20!), 2025