Taisija Kozarina
Graduated from Transport and Telecommunication Institute (Riga, Latvia) in 2024. Focused on research in Machine Learning and Medical Computer Vision. While studying participated in biomedical start-up developing diagnostical equipment, and led business communication, frontend development and AI module development. After defending Latvian patent left patent for a corporate career in Data Engineering in Accenture Baltics - developing complex ETL data pipelines and leading Cloud-Native migration for a large Banking company.
Continuing research in Computer Vision - segmentation and recognition, and planning to continue research in Uppsala University (Sweden)
Session
How can machine learning enhance biomedical image analysis? This talk explores the potential of Python and PyTorch in automating artifact and damage segmentation. From data preprocessing to clustering-based label classification and deep learning-driven segmentation, key techniques will be discussed, including the use of Convolutional Neural Network architectures. The session will also cover performance evaluation and insights into advancing biomedical imaging with AI-driven solutions.