Researched and helped developed convolution neural network models to classify detector events and remove background events in raw generated XENONnT data.Oversaw image processing and developed methods to turn physical tabular data into images.Gained a theoretical background in the search for dark matter and a better understanding of the underlying physics. Additionally, gained experience in applying computational physics to astroparticle physics.Gave a research talk on weakly interacting massive particles (WIMPs) and their potential candidacy for dark matter

Researched and developed a sequential triple-class neural network to discriminate detector events in real processed XENONnT data.Gained a background in direct detection experiments for dark matter and learned about the inner workings of XENONnT detector. Additionally gained an understanding of how experimental physics is conducted in the real world.Helped write a white paper on the results of our group.Gave a research talk on the controversial DAMA-LIBRA experiment