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

During my PhD, 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?

There are special bifacial solar modules, which, unlike traditional ones, can generate electricity from both sides. Thus, bifacial modules can benefit from both direct sunlight and reflected sunlight from the ground. This makes the estimation of the output energy much more complicated! That is where ray tracing came in. By following all the light bounces, we were able to estimate the power output for a typical year.

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.

Yes, the modules also move following the sun. It was a lot of Python coding, renting HPC computers, and iterations with the Atlas team.