The Science Days take place every autumn – they are Germany’s largest science and STEM festival.

Together with institutions from the fields of science, education and business, a fascinating and very diverse programme is put together. STEM topics are presented from different directions and perspectives, and visitors get insights into highly topical issues and their research. Hands-on activities play a very important role here. Visitors are encouraged to try things out, experiment and tinker! In exchange with the actors and under their expert guidance, visitors can gain new insights and expand their knowledge. Another highlight of the programme are our spectacular science shows, which guarantee aha and wow experiences.

SmallData will be participating this year! Please come and visit our stand!

We aim to bring together all female career advanced and early career researchers for fostering connections across career levels. In a still rather male-dominated leadership world, this retreat will provide a space to exchange experiences, discuss challenges, and explore opportunities for female leadership.

Keynote Lecture by Harald Binder, Speaker for the CRC 1597 Small Data

Recent advances in AI have been largely driven by big data and data-driven approaches like deep learning. However, many applications, particularly in biomedicine, face challenges with theseapproaches due to limited data availability. Addressing these “small data” scenarios requires innovative methods that integrate data-driven techniques, such as pre-training and meta-learning, with knowledge-driven approaches, like regression models and differential equations, and also foundation models. Our Collaborative Research Center, SmallData, focuses on three core areas: similarity, transfer, and uncertainty, aiming to create a unified interdisciplinary framework toaddress this problem. By combining contributions from computer science, mathematics, andstatistics with input from biomedical experts, we develop novel methods tailored to applications ingene therapy, nephrology, psychiatry, radiology, and more. These efforts aim to advance small data solutions, foster interdisciplinary collaboration, and drive biomedical discoveries.

More information will be found here closer to the date.

Girls’ Day is an annual event in Germany designed to inspire and empower girls and young women to explore career opportunities in fields where women are traditionally underrepresented. These include areas such as science, technology, engineering, mathematics (STEM), and skilled trades. The initiative aims to spark curiosity, challenge gender stereotypes, and open up a world of professional possibilities for the next generation.

At SmallData, we’re offering a unique experience to see a day in the life of an “AI data scientist in medicine”. Participants will have the opportunity to gain an understanding of the work of various researchers and take their first steps in data modelling using artificial intelligence. In doing so, they will learn how data is prepared to gain valuable insights for research. This event will run from 10:00 – 15:00 and be in german.

If you know any girls aged older than 12 who would love to explore this opportunity, please encourage them to sign up using this link. Here, they can also find more information about the event and what to expect!

From March 13th to 14th, 2025, SmallData will draw together all members of our CRC to share insights, collaborate, and delve into addressing the challenges of small data for meaningful discoveries!

This is the continuation seminar from the “Overview Paper Seminar on Model-based similarity and its quantification with small data”. Here, we will explore concrete examples which could be used to further the development of this paper!

Moderators: Nadine Binder (A02) & Johannes Hertel (B06)

This forum will bring together our CRC tandems of biomedical scientists and methods researchers with ongoing collaborations to tackle real-world challenges. Together, we’ll focus on:

• Highlighting the critical role of data engineering in collaborative research.
• Identifying and addressing gaps in data engineering.
• Exchanging ideas, insights, and practical solutions.

Whether you’re navigating interdisciplinary teamwork or aiming to optimize your data strategies, this forum is your chance to learn from peers, share your experiences, and strengthen your collaborative edge.

From February 10–11, 2025, participants of the SMART Master Lab will gather at the University of Freiburg for the kick-off event. This two-day event offers an opportunity to meet, network, and build connections with fellow SmallData researchers from diverse fields, including biomedical sciences, computer sciences, mathematics, and systems modeling. It’s a chance to lay the foundation for future collaborations, foster interdisciplinary relationships, and kick-start the exciting work ahead in the SMART Master Lab!

This is the continuation seminar from the “Overview Paper Seminar on Model-based similarity and its quantification with small data”. Here, we will explore concrete examples which could be used to further the development of this paper!

Moderators: Nadine Binder (A02) & Johannes Hertel (B06)

In this seminar, projects handling similar data structures or methodologies can come together and briefly present their research projects (or other topic related to their research) in oral presentations, offering a snapshot of their work or aspects related to their work to attract potential collaborators. After this, each speaker will head to their own table, allowing interested parties to join the table of the project or topic they’re most drawn to. Here, they can discuss this in greater detail and explore potential collaborations.

Merging explicit and implicit knowledge through synthetic data
Moritz Hess
Institute of Medical Biometry and Statistics (IMBI), Faculty of Medicine and Medical Center, University of Freiburg

Learning from prior distributions: Synthetic data for prior-data fitted networks
Johannes Hog
Department of Computer Science, Faculty of Engineering, University of Freiburg

On the statistic structure of synthetic fluxome data from constraint-based modelling paradigms
Johannes Hertel
Department of Psychiatry and Psychotherapy, Medical Center, University of Greifswald