Machine Learning for Bioimage Analysis Group ☰

Our group aims to develop novel machine learning approaches for the automated analysis of biological and medical images as well as for behavior analysis for e.g. neural degenerative diseases. Topics of interest include, but not limited to, cellular and tissue image analysis such as segmentation, tracking, and phenotype recognition, as well as behavioral analysis of articulated object such as human, lab mice, fish and flies.

Our research efforts are toward two complementing directions. One is by close collaboration with clinicians and biologists, to design dedicated machine learning and computer vision algorithms that help to create better healthcare and advance biological understanding. Meanwhile, we devise more robust and effective learning and vision algorithms that address the fundamental and mathematical aspects of biomedical informatics.