Joshua Ho L&S Math & Physical Sciences
Prototyping a Foundational Model for High Energy Physics Data Analyses
Particle physicists seek to understand particles and the physical laws governing their interactions by building particle colliders. These colliders provide a large amount of data, and due to the probabilistic nature of particle physics, researches are turning towards ML to model complex physical processes. With the rise of foundational models like ChatGPT, particle physicists have been inspired to create a large scale, general purpose model that has been trained on a vast amount of data to serve as a strong starting point for various specific tasks, that can be fine-tuned or adapted to perform specialized tasks, improving performance and efficiency. My project will utilize the idea of transferred learning, which is an ML technique where knowledge gained from solving one task is applied to a different but related task to increase performance and runtime. I will be prototyping a foundational model trained on a large and diverse dataset such that it learns general features about the event, and utilizes transferred learning to boost the performance of subsequent analysis tasks.
Message To Sponsor
I am very thankful for the funding that is allowing me to pursue my research. This project is very important to me, as it has enabled me to combine two of my academic interests (computer science and physics), and I would not have been able to explore my interests if not for the funding. Thank you!