Cryogentic station for the measurement of the specific heat
and superfluid density of confined helium

Professional Background

Kevin Mooney, Ph.D., is a computational physicist and engineer with deep experience in experimental research, numerical modeling, and scientific software development.

He earned his Ph.D. in Physics studying quantum fluids and phase transitions at low temperatures. His graduate research focused on the behavior of liquid helium in confined geometries near the superfluid transition. Alongside experimental work using SQUID magnetometry to investigate the magnetic properties of diverse materials, he developed numerical methods for solving complex differential equations and contributed to the operation and maintenance of his department’s Linux computing cluster.

As a postdoctoral researcher at NASA’s Jet Propulsion Laboratory, Kevin designed and built a custom thermosiphon system to study pool boiling in magnetically mediated water. He also created the supporting instrumentation, merging experimental design with precision measurement and control.

Following JPL, Kevin joined Quallion (later acquired by EnerSys), where he developed advanced mathematical models of lithium-ion batteries. His work bridged research and engineering practice, building software tools to make these models directly useful for design and analysis. He also pioneered proof-of-concept techniques, including applying particle filters to estimate and track the internal states of lithium-ion cells in real time.

Beyond his professional research and engineering work, Kevin runs a YouTube channel where he shares his passion for numerical methods and quantitative finance, producing educational content on scientific computing, options trading, and applied mathematics.

Selected Projects

Monte Carlo simulation chart
Monte Carlo

Simulation techniques for probabilistic modeling and quantitative finance.

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BEAST battery modeling framework
BEAST

Battery modeling framework supporting component- and system-level analysis.

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Particle filter visualization
Particle Filters

State estimation methods for tracking latent dynamics in real time.

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