Unsupervised data exploration plays an important role in many areas of science and becomes increasingly crucial as collected datasets grow in size and complexity.
Dr. Dmitry Kobak
Dmitry Kobak is a group leader in the Department of Data Science at the Hertie Institute for AI in Brain Health at the University of Tübingen. He is interested in unsupervised and self-supervised learning, in particular contrastive learning, manifold learning, and dimensionality reduction for two-dimensional visualization of high-dimensional biological datasets such as single-cell transcriptomic datasets. He has also worked on statistical forensics and has been involved in the analysis of Russian electoral falsifications and Covid-19 excess mortality. He is a member of the ELLIS society and an IMPRS-IS associated scientist.
Unsupervised data exploration plays an important role in many areas of science and becomes increasingly crucial as collected datasets grow in size and complexity.