We recently hosted an enriching Equity and Diversity Session, in collaboration with the ‘Women in Data Science Worldwide’ (WiDS) initiative*, entitled “Equity and Diversity in the Era of AI and Small Data”. This event brought together members of SmallData and the public to explore vital topics concerning equity and diversity within our CRC. The session […]
On July 5th, a group of our principal investigators, early career scientists, and members of the public gathered for another session on our SmallData Seminar Series. In this Bazaar edition, representatives from projects handling similar data structures presented some of their methodologies, showing insights into how they used some of their data analysis tools. Jacques […]
On June 28, 2024, our IRTG SMART early career scientists gathered for a dynamic session to discuss how their projects align with the broader SmallData Vision. In preparation for the meeting, project pairs were tasked with providing their thoughts on the following five key questions in relation to a draft vision document from SmallData shared with them beforehand: These […]
The first SmallData Seminar titled “Bring Your Cool Tool” successfully showcased innovative methodological tools being utilized in current research projects. Our Doctoral Researcher, Fabian Kabus (Fusion Hub) kicked off the seminar with an insightful introduction to PyTorch, covering essential topics such as tensor operations, dynamic computation graphs, Autograd, evaluation mode, and gradients. His session provided […]
Join our event for shaping the small data community to advance AI and modeling in settings with limited data — hosted by the Collaborative Research Center (CRC) 1597 “Small Data”. Discover the forefront of small data innovation at the SmallData Symposium, October 7th and 8th, 2024. Join us in Freiburg, Germany, where we will feature […]
From April 3rd to April 5th, doctoral researchers of our SmallData Integrated Research Training Group (SMART) took part in a dynamic and enriching Good Scientific Practice course. The workshop, hosted by Dr. Michael Mende, provided an engaging platform for docs to delve into essential topics crucial for maintaining ethical standards in scientific research. The 1.5-day, […]
Our PI Clemens Kreutz recently inspired students at Heimschule St. Landolin with a dynamic presentation on cutting-edge new machine learning techniques. We spoke with Clemens to get more details on the topics discussed: “Starting with regression, which was covered in the class, we gave an insight into mathematical models that we use in our research […]
Our Associated Researcher, Tanja Vogel, will be coordinating one of the newly selected priority programs established by the German Research Foundation, set to commence in 2025. Out of 43 initiatives that applied, only 11 were selected for this prestigious opportunity, each receiving funding for a duration of six years. The program is titled EPIADAPT, short […]
We are thrilled to announce the addition of nine distinguished Associated Researchers to SmallData. Their experience and expertise span various fields, promising to enrich our Collaborative Research Centre. Joining us are: Daiana Stolz, Ilka Diester, Diana Lindner, Pascal Schlosser, Oliver Amft, Tanja Vogel, Susanne Weber, Adam Kortylewski, Jan Hasenauer. We are excited to embark on […]
SmallData had the pleasure of attending the opening ceremony of the University of Freiburg’s new graduate centre (GraCe). Our PI Frank Hutter co-led a thought-provoking talk entitled “Wie wird die KI Promovieren verändern?” (How will AI change graduate education?). Frank Hutter discussed the impact of AI on doctoral research, emphasizing its potential to streamline research […]
The recent progress in artificial intelligence has been facilitated by big data volumes and data-driven modeling approaches. However, there is a much larger number of applications where data analysis has to be performed with a relatively small number of observations. This can be addressed with knowledge-driven approaches, such as differential equations that incorporate biomedical domain knowledge, or by adapting data-driven approaches, e.g., neural networks, or ideally by combining the two types of approaches. When developing such methods for small data settings, three key areas need to be addressed: similarity, transfer, and uncertainty. This enables combination of similar observations, e.g., from different hospitals, and more generally transfer of information, e.g., between genome screening and mechanistic models, while quantifying and reducing uncertainty. For creating comprehensive solutions that fuse such exciting emerging ideas, our Collaborative Research Center (CRC) 1597 'Small Data' (SmallData), which started on October 1st, 2023, integrates contributions from computer science, mathematics, and statistics/systems modeling, with input from biomedicine. Our doctoral program SMART is key for establishing a shared language across those disciplines. We are located in Freiburg, Germany, with external partners in Bochum and Greifswald. For more details see our scientific framework and interdisciplinary approach, or have a look at the individual research projects.
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center –
University of Freiburg
