Previously, as a postdoctoral scholar at the Kavli Institute for Theoretical Physics, Jessica’s research explored how the renormalization group can be used to understand the training dynamics of neural networks.  Before that, she obtained her Ph.D. in Physics from UC Irvine in 2022. As an NSF Graduate Research Fellow and Machine Learning and the Physical Sciences (MAPS) Honorary Fellow, her research focused on using advanced computational methods, such as generative machine learning, in collider physics and early universe cosmology applications. Prior to that, she graduated with her B.S. in Physics from UC Davis with Highest Honors.

Additionally, Jessica is passionate about evidence-based mentorship and physics education research with an emphasis on strategies to foster physics identity; this has been shown to help improve retention rates of underrepresented physicists. In addition to her scholarship, Jessica is committed to helping early-career physicists with underrepresented gender identities, especially those with disabilities, navigate the traditionally male-dominated field of theoretical physics.