Summary
Andrew Port is a machine learning and Python engineer with a decade of experience building computer vision and deep learning systems, currently developing evaluation software at Motional. His background blends rigorous applied math (MS in Applied Mathematics) and computer engineering research, with projects ranging from Mask-RCNN-based indoor localization to novel GAN-based sonification that led to an issued patent. He has built production-focused vision pipelines for conservation and fisheries monitoring, designed GPU servers for research workloads, and contributed user-facing improvements to open-source tooling for SVG path and Bezier curve manipulation. A math lover and amateur musician, he brings a strong habit of quantitative thinking and creative signal intuition to problems in perception and evaluation. Based in Natick, MA, he combines academic depth with practical engineering delivered across industry and research settings.
10 years of coding experience
13 years of employment as a software developer
Master of Science - MS, Applied Mathematics, Master of Science - MS, Applied Mathematics at University of California, Davis
University of California Santa Cruz