Data Science & Health
Data Science & Health lecture
This lecture is held by the PIs and Postdocs of the school and invited speakers who cover additional themes. The course consists of lecture-style elements and an interactive discussion. It covers data science methods (e.g., clustering, image analysis, visualization, deep learning), domain-oriented methods (e.g., medical imaging, surgery, robotics) as well as ethical, legal and social implications.
Organization: The lecture Data Science & Health is offered online via zoom and held in the winter semester. The lecture takes place weekly and only attendance is documented. Currently, no further examinations are planned.
Lectures winter semester 2025/2026:
- 06.11.2025 (Thursday, 2:00 – 3:30 pm)
Emilia Grass – Cybergeddon in Healthcare - 13.11.2025 (Thursday, 2:00 – 3:30 pm)
Ralf Mikut – Time Series Analysis in Healthcare - 27.11.2025 (Thursday, 2:00 – 3:30 pm)
Katja Mombaur – Robotics in Healthcare - 11.12.2025 (Thursday, 2:00 – 3:30 pm)
tba - 18.12.2025 (Thursday, 2:00 – 3:30 pm)
Kris Dreher – Decoding Light: Applications of Machine Learning in Advanced Biophotonic Imaging - 08.01.2026 (Thursday, 2:00 – 3:30 pm)
Johannes Bracher – Evaluation of Probabilistic Forecasts in Epidemiology - 15.01.2026 (Thursday, 2:00 – 3:30 pm)
Nadja Klein – Bayesian Deep Learning: An Introduction and Application to Disease Progression - 22.01.2026 (Thursday, 2:00 – 3:30 pm)
Andreas Ott – Topological and Geometric Methods in Omics Data Analysis - 29.01.2026 (Thursday, 2:00 – 3:30 pm)
Junyan Lu – From Data to Discovery: Multi-Omics Integration in Precision Oncology
The Data Science & Health Lecture Series
The aim of this course is to introduce the doctoral researchers to the field and to give a basic understanding of all research areas of the school. In addition, it will train them to consider the different views and needs of data science and health-related sciences, and the opportunities for interdisciplinary cooperation.
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"I am very curious and, therefore, love that the school is so interdisciplinary. I work with colleagues from medicine who never get tired of answering all my questions."
Elaine Zaunseder
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