Ekaterina Sedykh completed her Bachelor’s degree in Bioengineering and Robotics and her Master’s degrees in Computer Science at the University of Tartu in 2022 and 2024, and in Life Science Engineering with a Data Science minor at EPFL in 2024. Throughout her training, she developed a strong interdisciplinary background at the intersection of computer vision, machine learning, and biomedical imaging. 

Prior to joining the Institute of Tissue Medicine and Pathology, Ekaterina (Kate) gained research and industry experience across multiple research laboratories in institutions, including the University of Tartu, EPFL, the University of Pennsylvania, and several applied machine-learning roles in industry. Her work has spanned digital pathology, 3D medical image segmentation, generative models for medical image synthesis, and large-scale deployment of deep learning systems. She has contributed to projects involving histopathological image analysis, synthetic CT generation, and 3D reconstruction. 

As a PhD candidate at ITMP, Ekaterina’s research focuses on advancing 3D imaging approaches for colorectal cancer. Her project leverages light-sheet microscopy to move beyond traditional 2D histology, aiming to capture the three-dimensional organization of tumor tissue and its microenvironment. By combining 3D imaging with computational analysis and machine learning, her work seeks to uncover spatial and morphological patterns in CRC that are not accessible in conventional 2D workflows, with the goal of providing deeper biological insight into disease progression and heterogeneity.