I’m a Machine Learning Engineer at the Caltech Vision Lab, working under Pietro Perona, where I develop computer vision systems for detecting, tracking, and counting Pacific salmon populations in low signal-to-noise sonar data.

I lead development of FishEye, an edge-deployed ML system for automated salmon monitoring that operates under real-world constraints – noisy sonar inputs, limited connectivity, and non-technical field users. Most recently, I led the deployment of FishEye following the Klamath River dam removals, contributing to one of the largest ecological restoration efforts in the United States and enabling salmon migration monitoring in the region for the first time in over a century. I also built and maintain the infrastructure for large-scale data collection and annotation across 11 field sites, covering dataset iteration, model training, evaluation, and deployment.

Beyond my current work in ecological monitoring, I’m interested in building large-scale machine learning systems that translate research into products with broad real-world impact. My interests span computer vision and natural language processing, particularly visual recognition, detection and tracking in challenging real-world environments, fine-grained visual classification, multimodal AI, document understanding, and retrieval-augmented generation (RAG). I’m excited to bring my experience deploying reliable ML systems in challenging environments to products operating at global scale.

Previously, I completed a master’s degree in artificial intelligence at the University of Edinburgh in 2021. My dissertation, under the supervision of Ajitha Rajan and Javier Alfaro, focused on the interpretability of biological sequences using natural language processing techniques. I graduated with a bachelor’s degree in computer science at San Diego State University in 2019.