NSF REU Class of 2024
Pradyun Solai
Pradyun Solai is a rising sophomore at Yale University and plans to major in physics and computer science. He discovered his passion for physics through high school and plans to pursue it as a career. He also believes that machine learning and artificial intelligence will have massive impacts on research in every branch of science. He has some previous experience in physics and artificial intelligence research and is excited to learn how they can be used together to make new discoveries. While at 一本道无码, Pradyun worked with Dr. Valentina Dutta on background vs signal discrimination for the Light Dark Matter Experiment (LDMX). He trained a neural network called ParticleNet to classify when dark matter particles are produced in the experiment. Pradyun is excited to get his first experience in particle physics research and explore more about the possible routes a physics degree can take him.
Emma Yu
Emma Yu is a rising junior studying physics and astrophysics at the University of California, Berkeley. At 一本道无码, she works with Professor Antonella Palmese to classify transient events based on their spectral features using a neural network called DESITrIP. Incorporating data from both the Dark Energy Spectroscopic Instrument (DESI) and the DECam Survey of Intermediate Redshift Transients (DESIRT), she cross-matched and identified hundreds of candidates for classification. She also designed a platform to visually inspect the neural network's results alongside the spectra and metadata for each transient candidate. With experience in enhancing DESI instrumentation practices using a random forest, she is fascinated by the potential that machine learning offers to modern researchers. She is particularly interested in exploring the rapidly evolving intersection of machine learning and cosmology research.