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Profile
| Academic position | Full Professor |
|---|---|
| Research fields | Mathematical and Applied Statistics,Bioinformatics and Theoretical Biology,Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing |
| Keywords | probability metrics and distributions, genome-wide data set analysis, statistical learning theory, signaling networks in cancer genes, machine learning |
Current contact address
| Country | Germany |
|---|---|
| City | Leipzig |
| Institution | Universität Leipzig |
Host during sponsorship
| Prof. Dr. Eva Ines Obergfell | Universität Leipzig, Leipzig |
|---|---|
| Prof. Dr. Bernd Sturmfels | Max-Planck-Institut für Mathematik in den Naturwissenschaften, Leipzig |
| Start of initial sponsorship | 01/05/2022 |
Programme(s)
| 2021 | Alexander von Humboldt Professorship (Artificial Intelligence) |
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Nominator's project description
| Human DNA is composed of three billions of base pairs which, in some cases in groups and combinations, can play a role in the development of various diseases. At the same time, gender, age, heart rate, blood pressure and weight can be linked to a person’s physical condition. In order to be able to record, evaluate and, for example, make and check hypotheses about causal connections in multidimensional data like these, innovative statistical computational methods are required. Sayan Mukherjee has made outstanding contributions to the continued mathematical development of statistical evaluation methods involving high-dimensional data which are being used in computer science, imaging and particularly on an interdisciplinary basis in computational biology with the aim of advancing medicine. Mukherjee was, for instance, involved in developing Gene Set Enrichment Analysis (GSEA), a statistical evaluation method for the human genome through which the biological function of entire groups of genes and their possible role in the formation of cancers is determined – work for which he gained an international reputation. His special field is topological data analysis which visualises high-dimensional data, making it possible to infer individual datasets from the geometric representation. Further developments in this field have led to improvements in medical imaging, allowing predictions to be made about the development of certain diseases. He has also managed to improve statistical error control in the field of AI. In Leipzig, Sayan Mukherjee will continue his fundamental research in mathematical statistics at the Center for Scalable Data Analytics at the University of Leipzig and the Max Planck Institute for Mathematics in the Sciences. He will also be appointed as director of the Interdisciplinary Centre for Bioinformatics (IZBI). His fundamental research on data analysis and its representation seeks to generate new knowledge in the fight against certain diseases in precision medicine. |