Translational Impact

The methods I build for research—analytical and numerical modeling, scientific computing, and turning open-ended problems into tractable ones—translate directly into real-world R&D. I enjoy partnering with teams beyond academia to interpret data, accelerate development, and put physics to work on practical problems.

Example: a bifacial solar plant

In 2020–21, my good friend Osven Ledezma and I worked with Atlas Renewable Energy to model the energy output of a solar plant using ray-tracing techniques.

Why ray tracing? Bifacial solar modules, unlike traditional ones, generate electricity from both sides, so they benefit from both direct sunlight and sunlight reflected from the ground. This makes the estimation of the output energy much more complicated! By following all the light bounces, we estimated the power output for a typical year—with modules that also move following the sun.

Why does it matter? A solar plant is more efficient if everything is adjusted to match the power output of the solar modules. Many of the power losses are associated with energy conversion, which we also dealt with a bit. Moreover, bifacial modules are more expensive, so knowing if they are worth it for a given plant is essential.

The result. It worked pretty well! Here is a simulation of one day.

It was a lot of Python coding, renting HPC computers, and iterations with the Atlas team.