Pragyan Yadav (he/him) is a junior double-majoring in Physics and Computer Science with a minor in Astrophysics. He is passionate about combining computational methods and machine learning to analyze complex physical systems and better understand the fundamental workings of the universe.

Since his freshman year at UConn, Pragyan has conducted research with Dr. Daniel Anglés-Alcázar in the Computational Galaxy Formation Group, exploring how the universe builds itself on the largest scales. His SURF project models the cosmic web as an interconnected network, applying graph theory to measure the structural connectivity and hidden topology of dark matter filaments. To push the research further, he works on machine learning interpretability techniques to “see” inside AI models, decoding the underlying physical rules AI uncovers about dark matter and cosmology.

In addition to his astrophysics research, Pragyan is also interested in particle physics. He spent a summer as an R&D physics intern at Mirion Technologies, where he developed machine learning tools for gamma-ray spectroscopy to analyze the complex spectral signatures of various radionuclides.

Outside of the lab, Pragyan is actively involved in scientific communication as the Director of Journalism for the Undergraduate Science Journal (USJ) at UConn, helping highlight student research and make science accessible across campus.

Following graduation, Pragyan plans to pursue a PhD in astrophysics. He aims to continue leveraging advanced computational, machine learning, and data-driven methods to study complex physical systems and explore fundamental questions in physics and cosmology.