Anthony Mein

Led development of a healthcare-focused augmented reality cross platform application that provides real-time visual guidance for biological protocols and procedures, using spatial computing to improve technician accuracy and efficiency. Led research, development, deployment and evaluation of innovative agentic solutions to provide assistance and automation to laboratory scientists.

Developed Unity-based AR visualization tools and computer vision models (YOLACT, Detectron), including dataset preparation, grooming, and model training for medical procedure guidance, improving operator accuracy and efficiency Supported cross-functional collaboration between C++ and Python teams to implement AR solutions, bridging technical development with biological requirements Created technical documentation and stakeholder demonstrations to align AR capabilities with research objectives

Led a senior capstone project in collaboration with Amazon to develop a cloud infrastructure assessment tool that automatically compares developers' current AWS configurations against architectural best practices. Built an MVP using AWS Well-Architected Framework, CodeDeploy, DynamoDB, and Lambda, with a Java 11 backend and React frontend, helping developers efficiently identify and implement infrastructure improvements.

IT assistance for Seattle University including but not limited to monitoring phone queues, troubleshooting customer tickets via Jira and upholding security standards for the university

Developed CNN model (Keras/TensorFlow) achieving 94% accuracy in multiclass classification of Diabetic Retinopathy from fundus images, leveraging data augmentation to expand training dataset from 89 to 12,000+ samples