Data Science Seminar
The DKFZ Data Science Seminar is a campus-wide effort bringing together thought-leading speakers and researchers in the field of data science to discuss both methodological advances as well as medical applications.
Data Science Seminar Channel
Data Science seminar goes virtual
We will offer a mix of live and recorded online lectures.
The upcoming physical seminars are postponed till further notice.
- 17.06.2020: Christina Heinze-Deml - Towards Active Invariant Causal Prediction: Experiment Selection through Stability
- 20.05.2020: Elisabeth Hoppe - Deep Learning-based Magnetic Resonance Fingerprinting
- 06.05.2020: Max Welling - Learning Equivariant and Hybrid Message Passing on Graphs
- 22.04.2020: Lynton Ardizzone - Safety, Robustness and Explainability in Supervised Tasks using Invertible Neural Networks
- ELLIS against COVID-19
- 08.04.2020: Veronika Cheplygina - Ten Simple Rules for using Twitter as a Scientist
- Deep Learning State of the Art (2020) | MIT Deep Learning Series
Physical Seminars
- 11.03.2020: Emre Kavur - A story of a challenge and how to keep it impartial
- 26.02.2020: Mathias Niepert - Graph Neural Networks for (Bio-)Medical Applications
- 12.02.2020: Titus Brinker - Von der Klinik in die Pathologie: Das Potential künstlicher Intelligenz in der Hautkrebsdiagnostik
- 29.01.2020: Patrick Scholz, Jan Sellner, David Zimmerer - Recent developments in 3 domains of data science
- 06.11.2019: Manuel Wiesenfarth - Unraveling uncertainty in benchmarking: Methods and open-source toolkit for analyzing and visualizing challenge results
- 21.10.2019: Teodor Grantcharov - Using data to enhance teamwork, team performance, and patient safety in the OR
Upcoming Speakers
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The Data Science Seminar series is supported by the Data Science Driven Surgical Oncology program of the NCT Heidelberg and CAMI@DKFZ.