The SmallData Symposium 2024 has concluded, and we are excited to reflect on the event’s many scientific highlights. From specialized talks delivered by our esteemed speakers to the lively discussions between panelists and participants, this symposium offered a wealth of knowledge for all attendees. The opening addresses by Stefan Rensing, Lutz Hein, and Frederik Wenz […]
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 […]
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, […]
We’re thrilled to announce that our associated researcher, Dr. Pascal Schlosser, has been awarded the prestigious Helmut Holzer Research Prize for his innovative research in statistical genomics and molecular epidemiology. This recognition, awarded by the Wissenschaftliche Gesellschaft Freiburg, celebrates his substantial contributions to advancing our understanding of genetic data analysis and its applications to public […]
On October 24th, our team of doctoral researchers arrived at Europapark to kick off the first day of Science Days, a science fair designed to spark curiosity and bring science closer to the next generation. It was a great chance to share our research and engage kids of all ages. Throughout the event, students enjoyed […]
This year, SmallData had the privilege of sponsoring the STRATOS Accelerated Guidance for Real-World Data Analysis Workshop, held from September 16 to 20, 2024. The workshop provided an invaluable platform for researchers grappling with real-world data challenges to engage with cutting-edge statistical methods and machine learning techniques. Representing SmallData, our speaker Harald Binder introduced our […]
The International Conference on Machine Learning (ICML) held its 41st event from July 21st to the 27th in Vienna, Austria. This renowned conference gathered professionals from a wide range of backgrounds, from academic and industrial researchers to entrepreneurs and engineers, who dedicate themselves to the advancement of the branch of AI known as machine learning. It was […]
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
