Research Stories

How I trained neural networks to help telescopes automatically correct for atmospheric disturbances and mechanical imperfections, and why bridging the gap between simulation and reality turned out to be the hardest part.

How I use high-resolution simulations and neural networks to model what happened when the first stars lit up the universe, and why getting the small-scale physics right matters.

Building Julia code to find planetary configurations that repeat perfectly over time, using automatic differentiation and some clever optimization tricks.

The story of baryonic streaming velocity—a subtle effect from the early universe that turns out to have big consequences for how cosmic structure forms.

How I used wavelets (math tools from signal processing) to extract new cosmological information from Lyman-α forest data that traditional methods were missing.

Using the cosmic microwave background to test whether fundamental constants have evolved since the early universe. Spoiler: probably not, but the constraints are interesting.