CV and robotics to automate quality inspection in fish farms
Fish farms rely on slow, error-prone manual phenotyping and deformity inspections, leading to wasted labor, feed, and lower-quality stock selection.
An AI computer-vision robotics system that automates hatchery quality inspection (broodstock phenotyping and juvenile deformity detection) in seconds with high accuracy.
Aquaculture fish farms and hatcheries that need to perform quality assurance and quality control on broodstock and juvenile fish.
Co-founder and CEO of OctaPulse, deploying computer vision, edge computing, and robotics to make fish farms autonomous. CMU Robotics Institute Pathways Fellow, and prior to CMU sold enterprise portfolio risk and attribution products to Tier 1 asset managers while at Bloomberg LP. Named as a Future Leader in two national aquaculture organizations.
Co-founder and CTO of OctaPulse, deploying computer vision, edge computing, and robotics to make fish farms autonomous. Former D1 tennis player at Texas A&M, CMU AI Engineering MS, with production robotics and software experience across Tesla, Nvidia, ASML, and Toyota.




