On April 17, 2025, we marked the culmination of a brilliant journey for the SMART Master Lab Cohort 1.0 students. After 10 weeks of in-depth research, collaboration with doctoral researchers and principal investigators, the students presented their exceptional work during the final presentation event. CRC members joined us in celebrating the achievements of the first […]
SmallData joined Girls’ Day on the mission to promote female representation in scientific fields such as mathematics, computer science, biomedicine and statistics / systems modeling. On April 3, 2025, 8 girls aged 12 to 15 from the Freiburg city area schools arrived in our headquarters to take part on a day of scientific activities, led by […]
The CRC SmallData got together for its yearly scientific retreat last week at Schloss Reinach. The aim of the event was to share what has been done over the past year, to present and discuss future plans for the CRC, and to encourage further collaboration between old and new members. Day 1 Highlights: The event kicked off […]
On February 13, we held the inaugural SmallData Data Engineering Forum, bringing together method researchers and biomedical scientists to tackle data engineering challenges in SmallData tandem projects. Entirely organized by our postdoctoral early career researchers, the event strengthened their group identity and provided valuable experience in leading academic activities. Erika Graf, Head of the Statistical Consulting […]
On February 10-11, we launched the first cohort of the SMART Master Lab program, equipping master’s students with SmallData research skills through hands-on training and expert mentorship. The event opened with CRC Speaker Harald Binder introducing the fundamentals of SmallData, followed by SMART PI Nadine Binder and SMART Coordinator Iván Acevedo, who outlined the SMART Master Lab goals and its […]
Last night, we were excited to participate in the Digital Health Research Night at the Technical Faculty in Freiburg, where researchers and students came together to explore opportunities for graduate research and collaboration at the intersection of medicine, data science, and technology. Our team presented a poster showcasing SmallData, the SMART group, and our new SMART Master Lab Program, sparking engaging discussions […]
On April 23, our early career researcher Simon Ging (B05) will talk about his current research on building datasets for Vision-Language models at the Stuttgart AI, Machine Learning and Computer Vision Meetup organized by Antonio Rueda-Toicen. The goal of this event is to bring together a community of data scientists, machine learning engineers, and open source enthusiasts who want […]
We are thrilled to announce the addition of eight distinguished Associated Researchers to SmallData. Their experience and expertise span various fields, promising to enrich our Collaborative Research Centre. Joining us are: Nadja Klein, Heinz Wiendl, Diyora Salimova, Jana Naue, Janis Nolde, Maria Elena Maccari, Martin Wolkewitz, and Maria Kalweit. We are excited to embark on […]
An important aspect of research is having access to as much information as you can in order to reach the most accurate results. Unfortunately, that is not always a possibility. In some studies, due to the nature of the researched subject or the low availability of resources such as time, money or technology, only limited […]
On February 13, we held the inaugural SmallData Data Engineering Forum, bringing together method researchers and biomedical scientists to tackle data engineering challenges in SmallData tandem projects. Entirely organized by our postdoctoral early career researchers, the event strengthened their group identity and provided valuable experience in leading academic activities. Erika Graf, Head of the Statistical Consulting […]
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
