about

I am a freelance applied scientist and machine learning engineer based in the San Francisco Bay Area, operating under the name Bayfront Applied AI. I specialize in vision-language models, multimodal representation learning, and foundation model development, with a growing focus on geospatial intelligence and Earth observation AI.

Today I work with clients at the intersection of computer vision and Earth intelligence: evaluating Earth Foundation Models, building multimodal embedding pipelines, and prototyping systems that extract meaning from satellite imagery.

I spent 3.5 years as an Applied Scientist at Amazon working on large-scale visual search systems, and hold a Ph.D. in Computer Science from UC Irvine (2022), where I worked on model-based reinforcement learning and generative world models.

I am drawn to problems where AI connects to something larger: climate, environment, and how we understand the planet from above.

Open to project collaborations, research discussions, and conversations in the Earth observation AI space.

Words in this site are my own, not represent or endorsed by any org.