I am excited to be planning to attend the 2024 Data Assimilation summer school in Boltenhagen, Germany! Looking forward to learning about new DA methods on the German coast.

I am excited to be an Intern in the Quantitative Systems Pharmacology group at Johnson and Johnson Innovative Medicine. I will spend the summer building ML models to predict the side effects of immuno-oncology therapies.

I am excited to announce that I successfully passed my advancement to candidacy exam and am now a PhD candidate in Mechanical and Aerospace Engineering at UCSD!

I had a great time organizing a minisymposium and presenting my work at SIAM UQ 2024 in Trieste, Italy.

I had an excellent time learning more about optimal transport and normalizing flows at the Uncertainty Quantification Summer School in August 2023!

I presented my work on model averaging to account for model uncertainty when making predictions from blood glucose and insulin measurements in Diabetes at the Society for Mathematical Biology Annual Meeting in July 2023.

Our paper on uncertainty quantification for progression damage simulation of composite materials was accepted in Composite Structures (link). This work is part of an international collaboration, including Jonnahes Reiner at Deakin University, Navid Zobeiry at the University of Washington, Reza Vaziri at the University of British Columbia, and my advisor Boris Kramer at UCSD.

I presented my current work on applications of Bayesian parameter estimation to study intracellular AMP-activated protein kinase signaling at the National Institutes of Health, National Institute of Bioimaging and Bioengineering (NIH NIBIB) Training Grantees Meeting in Bethesda, MD.

I completed my first year of volunteer tutoring at the Preuss School UCSD. Throughout the school year, I had to the opportunity to support students in a 7th grade science classroom! I am looking forward to continuing this work next school year.