The SimTech Status Seminar is an annual event designed to bring together the entire SimTech community, including Principal Investigators (PIs), Principal Researchers (PRs), early career researchers, and everyone involved in the Cluster of Excellence SimTech. The seminar serves as a dynamic platform for participants to present their research, exchange innovative ideas, and facilitate knowledge transfer within the interdisciplinary environment that defines SimTech. It provides a unique opportunity for networking, fostering collaboration, and advancing the frontiers of research in simulation science.
SimTech Status Seminar 2024
This year's SimTech Status Seminar took place from September 30th to October 2nd in Reutlingen, with a special focus on doctoral researchers. The event featured a rich program including parallel sessions on diverse topics, a scientific talk by the 2024 Argyris Visiting Professor Per-Olof Persson, as well as sessions on project networks and cross-network sessions. Poster presentations also played a key role, allowing researchers to showcase their work and engage in in-depth discussions with their peers.
Election of New PhD and PostDoc Representatives
These newly elected representatives are set to play a vital role in shaping the future direction of the SimTech community, ensuring that the voices and perspectives of their peers are well-represented.
Best Paper Award 2024
The nomination highlighted the innovative aspects of the BayModTS workflow, which integrates Bayesian modeling techniques to handle sparse and noisy time series data - a common challenge in systems biology. The approach uniquely incorporates process knowledge, ensuring that uncertainties in the data are consistently transferred to model predictions.
This work stood out due to its interdisciplinary nature, bridging the gap between methods development and biomedical application. BayModTS was applied to analyze three different hepatic datasets using various measurement techniques, including MRI for rat liver perfusion, drug metabolization studies in mice, and CT-based assessments of human liver remnants. Its ability to handle diverse data types and integrate them into a cohesive analysis framework was praised as a significant advancement in simulation modeling.
Moreover, the emphasis on reproducibility and adherence to FAIR principles (Findable, Accessible, Interoperable, and Reusable) played a central role in the project's design. The implementation of BayModTS in Python, along with its compatibility with the SBML standard and data sharing via platforms like GitHub and DaRUS, ensures that other researchers can easily replicate and build upon this work. These qualities made the paper an exemplary candidate for the award, demonstrating SimTech's commitment to innovative research and methodological rigor.