The transmission of optical information through random scattering media is a major challenge in optics, biomedical imaging, ...
Reasoning and simulation aren't enough if the system doesn't truly understand the physical state of its environment.
Last semester, I assigned students in my energy storage systems class a problem set comparing the electrical designs of supercapacitors, lithium-ion batteries and flywheel systems. One submission ...
Microbial communities drive essential biological processes across ecosystems, yet predicting their dynamics and functions remains challenging due to context-dependent interactions. We develop a ...
ReservoirFlow is a modern open-source Python library developed by Zakariya Abugrin at Hiesab; a startup company specialized in advanced analytics, computing, and automation founded in 2024 with a ...
Inertial microfluidics allows for passive, label-free manipulation of particles suspended in a fluid. Physical experiments can understand the underlying mechanisms to an extent whereby inertial ...
This work develops a physics-informed transfer learning framework for modeling and control of a nonlinear process network with limited training data. Unlike the conventional transfer learning method ...
A curated list of machine learning papers, codes, libraries, and databases applied to fluid mechanics. This list is not comprehensive; if something is missing, please feel free to add it while ...
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