Summary
Aydin Ayanzadeh is a PhD student and Graduate Teaching Assistant in Computer Science at UMBC with nine years of research and development experience in computer vision, machine learning, and image processing. He has contributed to applied deep-learning projects across academia and industry, including phase-contrast microscopy analysis at TÜBİTAK and model compression for edge video processing with Arçelik Global and Vodafone. His background spans signal processing research at Istanbul Technical University and practical R&D roles that bridge algorithm development and deployment on constrained devices. Known for improving low-level image analysis methods (e.g., enhanced edge detection heuristics), he brings both theoretical rigor and hands-on experience tuning models for real-world imaging pipelines. Based in the Washington DC–Baltimore area, he combines strong academic credentials with a track record of collaborative, interdisciplinary projects.
9 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer science, 14.58/20, Bachelor's degree, Computer science, 14.58/20 at University of Tabriz
Diploma of high school, Mathematics, 18.96 of 20, Diploma of high school, Mathematics, 18.96 of 20 at Ferdowsi Highschool
UMBC
Master of Science - MS, Informatics, 3.75, Master of Science - MS, Informatics, 3.75 at Istanbul Technical University
English, Persian, Turkish, Azerbaijani, Arabic