About me

I am an incoming M.S. student in Computer Science at NYU's Courant Institute, starting Fall 2026. I received my B.S. in Computer Science with a minor in Mathematics from Cal Poly San Luis Obispo.

My research interests center on inductive biases for efficient multimodal learning, world models and learned representations for planning and control, and semantic-space prediction (JEPA-family architectures) as an alternative to text-centric scaling. I'm broadly interested in how hierarchical structure emerges in learned representations and how it can be leveraged for sample-efficient reasoning.

Previously, I was a Senior Research Assistant at Argonne National Laboratory (UChicago/DOE), where I studied Kolmogorov-Arnold Networks as architectural priors for implicit neural representations of scientific volumes. I also worked on action segmentation from monocular video in the Ventura Lab (funded by the National Cancer Institute) and built multimodal location predictors for missing person cases in the AI for Search & Rescue Lab. In industry, I interned at LandingAI (founded by Andrew Ng), where I worked on VLM fine-tuning, attention diagnostics, and large-scale data distillation pipelines.