Due to unforeseeable reasons the seminar has to be postponed on short notice. The new date will be published soon. Thank you for your understanding.
CASUS Institute Seminar, Haralampos Hatzikirou, PhD, Associate Professor Khalifa University Abu Dhabi, Research group leader TU Dresden
Haralampos received his PhD from TU Dresden as a Marie Curie fellow. He then worked as a postdoc in Biomedical Informatics at the University of Texas at Houston and in the Pathology department of New Mexico University in Albuquerque. He later returned to Germany where he became a group leader at TU Dresden and at Helmholtz Center for Infection Research. In 2020, he joined the faculty of Mathematics at Khalifa University as an Associate Professor.
Abstract of the talk// In clinical practice, a plethora of examinations is conducted to assess the state of a certain pathology. These span from blood sample analysis, clinical imaging (e.g. CT, MRI) and biopsy sampling are among the most important diagnostic and prognostic tools. Such medical data correspond to snapshots in time of the patient’s state. Moreover, clinical data refer to different biological scales, since imaging, such as MRI, typically provides an organ level picture of a disease (macroscopic), biopsies represent cellular patterns at a tissue (mesoscopic) level and -omics, FACS or molecular markers allow for sub-cellular insights. Finally, the biophysical mechanisms that regulate phenomena in all these scales are not completely known. Therefore, current clinical care faces the following challenges: First data collection is sparse in time since it relies on patient’s clinical presentation. Second, we lack the knowledge/uncertainty of the mechanisms involved in regulating these data variables across different scales (structural uncertainty), and third medical data are multiscale.
In this talk, Haralampos will propose methodologies, which combine multiscale modelling and machine learning, that allows us to address the aforementioned challenges.
Haralampos will be talking live in Görlitz. However, as the event is organized in a hybrid format that includes a videoconferencing tool by Zoom Inc., people interested in the topic have the chance to also join the talk remotely. Please ask for the login details via contact@casus.science.