Designed and prototyped a Physics-Informed Graph Neural Network to identify particle trajectories for the Tagged Deep Inelastic Scattering Experiment at Jefferson Lab.

Responsible for the development of benchmarking tools to assess the performance of detector designs for the upcoming electron-proton ion collider (ePIC) experiment to be performed at the electron Ion Collider (EIC).

Designed these tools to execute workflow pipelines that operate on HPCs and other distributed systems.

Integrated analytic methods to determine the momentum resolution, track efficiency, and other physical observables for several ePIC configurations/scenarios to assess the ePIC detector's performance.

Undergraduate Computer Science and Physics Student at the University of California, Berkeley.

Academically supporting and teaching Data Science to students in Kuwait to develop their statistical skill sets.