Argo Saakyan
About Argo Saakyan
Argo Saakyan is a Computer Vision Engineer with extensive experience in machine learning and deep learning. He has worked at various organizations, including Rosgosstrakh, Diagnocat, and Veryfi, where he has contributed to significant projects in fraud detection and image analysis.
Current Role as Computer Vision Engineer
Argo Saakyan currently works as a Computer Vision Engineer in the San Francisco Bay Area. He has been in this role since 2023, focusing on developing advanced solutions in the field of computer vision. His responsibilities include designing custom training pipelines and evaluating various neural network architectures. He has contributed to a fraud detection project, where he significantly improved model accuracy and performance.
Previous Experience in Data Analysis and Machine Learning
Before his current position, Argo Saakyan held several roles in data analysis and machine learning. He worked as a Data Analyst at Rosgosstrakh in Moscow for six months in 2020. In 2021, he served as a Data Scientist at DOCCLUB for seven months. Most recently, he was an ML/CV Researcher at Diagnocat in Yerevan from 2022 to 2023, where he focused on machine learning applications in computer vision.
Educational Background in Law
Argo Saakyan studied at Kutafin Moscow State Law University, where he earned a Bachelor's degree in Law. His studies spanned from 2013 to 2017, providing him with a foundational understanding of legal principles, which may complement his analytical skills in technology and data.
Contributions to Hackathons and Conferences
Argo Saakyan actively participates in the tech community by judging international hackathons, where he shares his expertise in computer vision and deep learning. He also speaks at conferences, providing insights into the latest developments and applications in these fields, thereby contributing to knowledge sharing and community engagement.
Publications and Technical Contributions
In addition to his engineering work, Argo Saakyan writes articles on platforms such as Dev Genius and Hackernoon, focusing on topics related to computer vision and deep learning. His technical contributions include engineering a neural network service for document verification and exporting models for mobile deployment, showcasing his skills in practical applications of machine learning.