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My research interests cover a broad range of topics in theoretical soft condensed matter, statistical physics, and biological physics. Quite generally the common theme between these different topics is geometry. For example, I have been studying morphological transitions, shape fluctuations and instabilities, and the emergence of order in biological and soft matter. Recent projects focus on the geometrical formulations of classical and quantum mechanics and the properties of fields in metrices with singularities.
Additionally, I am using physical methods to study cancer. Recently, we have developed a novel machine learning method to detect correlations in (large) 2-dimensional data. This method allows the detection of signatures of cancer subtypes. We are currently extending the scope of this approach by applying it to other biological and non-biological data.