Hello, I'm Adrian Crawford! (they/them)Current WorkMy current project on supernovae (SNe) harnesses the power of machine learning by creating a data-driven classifier to identify rare, doubly-peaked Type IIb supernovae for crucial follow-up observations admit the millions of transient alerts in the forthcoming age of LSST and Big Data astronomy.
It's important that LSST can quickly and reliably identify a multitude of transient events so astronomers know where to focus their time and energy. Currently, most training data sets for LSST on supernovae use simulated data, but theory doesn't always match reality, so it's important to create data-driven training sets that comprise of real observations of supernovae. |
I am currently a 3rd year Ph.D. candidate at the University of Virginia. I am working with Maryam Modjaz as part of the Modjaz Explosions and Transients Astronomy Lab (METAL). I've done work on the very small (white dwarfs), to the very largest (galaxy clusters), and now to the most energetic (supernovae). I have experience using theoretical, analytic, and computational methods in my research.
I graduated from UT Austin in May 2021 with a B.S. in Astronomy and a B.S. in Physics. I earned my M.S. in May 2023 on the way towards my Ph.D. |