Any fool can know. The point is to understand.
Albert EinsteinAdvancing our understanding of the universe through the synergy of physics and computational innovation. My research focuses on leveraging machine learning techniques to tackle complex problems in cosmology and particle physics, aiming to uncover new insights about the fundamental nature of reality.
Research
Machine Learning in Physics
Teaching computers to find patterns in the universe that humans can't see. By training neural networks on massive physics datasets, we uncover hidden signals in everything from the oldest light in the cosmos to the tiniest particles inside a proton.
The Early Universe
The Cosmic Microwave Background is the oldest light in the universe—a baby picture from 380,000 years after the Big Bang. Using neural networks, I search for faint whispers of primordial non-Gaussianity that could reveal what powered cosmic inflation.
Putting the Proton Under a Microscope
What's inside a proton? By firing electrons at protons and watching what bounces back, we map the sea of quarks and gluons within. At high energies, gluons crowd together until they saturate—a phenomenon I study using machine learning to analyze scattering data.