Matthew G. Medina

About Matthew G. Medina

Currently pursuing a Master of Science in Electrical Engineering at the University of Washington, I am actively engaged as a Machine Learning Engineering Intern at AIWaysion. Here, my core competencies lie in developing cutting-edge computer vision solutions and object tracking systems that enhance real-time traffic surveillance technologies.My recent work includes deploying a high-accuracy detection system across multiple locations, contributing to AIWaysion\'s commitment to innovation and safety. I am proud to be part of a team that values precision, efficiency, and the integration of advanced machine learning in practical applications. Bringing my background in electrical and computer engineering, I am enthusiastic about further aligning our technological solutions with the evolving needs of smart city infrastructure.

Experience

1. Machine Learning Engineering Intern

   Aiwaysion

   Sep 2024 — Present · Seattle, WA, US

   Developed and deployed an advanced computer vision solution for real-time traffic surveillance across five camera locations in Bellevue, WA, Tucson, AZ, and Spokane, WA, leveraging the YOLOv8 deep learning model to achieve over 90% detection accuracy for vehicle and pedestrian tracking. Engineered a Python and OpenCV pipeline, processing video feeds at 32 FPS, to map object trajectories onto geospatially accurate top-down images using homography and perspective transformations with sub-pixel precision. Monitored over 12 ROI entry zones for automated activity detection, achieving 95% zone-activation accuracy, and integrated CSV logging for structured data output. This robust framework significantly improved traffic monitoring by facilitating precise detection of movement patterns and supporting real-time responses to traffic conditions.

Education

• University of Washington

  Master of Science - MS, Electrical Engineering

• University of Washington

  Bachelor of Science - BS, Electrical & Computer Engineering