The registration deadline, September 10, 2024, for the SmallData Symposium in Freiburg, Germany is fast approaching! At this year’s symposium, October 7th and 8th, 2024, you can discover the forefront of small data innovation. The event will begin with welcome addresses from Stefan Rensing, the Vice Rector for Research and Innovation at the University of […]
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, […]
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 Bioinformatics Group at the Department of Computer Science, University of Freiburg, invitesapplications for a highly motivated doctoral researcher to join our team. The successful candidatewill conduct research starting as soon as possible in AI for Medicine under the A04 project, Aneffective similarity integration multi-modal graph neural network method to facilitate disease geneprioritization, which is […]
The International Society for Clinical Biostatistics (ISCB) held their 45th Annual Conference from the 21st to the 25th of July in the city of Thessaloniki, Greece. This event gathered renowned experts as well as researchers from diverse backgrounds working in the field of clinical biostatistics. We were delighted to note that many members from SmallData participated […]
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 […]
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
