IRU Mathematics and Life Sciences
The Interdisciplinary Research Unit Mathematics and Life Sciences houses three groups at the interface of the ImmunoSensation and HCM clusters. With the combined expertise gathered here, we have a unique opportunity to create new mathematical models impacting the understanding of the immune system and diseases. The research topics range from information processing, immune response dynamics, treatment protocol modeling, sparse data in single cell approaches, cell behavior prediction, image analysis, and dynamic image analysis in the context of immune responses. For more details on each group see below.
Effland Group
Our research group focuses on applied mathematics with a particular focus on Biomedical Imaging Processing and Modelling. We are interested in developing novel algorithms and methods with a strong emphasis on biomedical applications. Our research topics include mathematical image processing & computer vision, machine/deep learning, modeling, and calculus of variations, which are designed for diverse medical fields such as immunology, radiology, and cardiology.
Hasenauer Group
Our research field encompasses a variety of topics including statistical inference, multi-scale models, metabolic models, mathematical modeling for infectious diseases, and machine learning in bioinformatics. In our research, we aim to provide insights into biological processes and make predictions through analysis, while also considering the complexities of the underlying mechanisms.
Thurley Group
We investigate the regulation of immune responses by quantitative data analysis and mathematical modeling, in close collaboration with immuno-biologists and clinical scientists.
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Machine Learning-Based Perivascular Space Volumetry in Alzheimer Disease
Apr 23, 2024
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Personalized Lens Correction Improves Quantitative Fundus Autofluorescence Analysis
Mar 11, 2024
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Determining individual glomerular proteinuria and periglomerular infiltration in a cleared murine kidney by a 3-dimensional fast marching algorithm
Mar 08, 2024
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We are thrilled to announce that our PhD student team, Lea Seep, Domagoj Doresic, Manuel Huth and Jonas Arruda, secured second place at the #Hack4BestCX, a joint hackathon hosted by the University of Bonn, Deutsche Telekom, and organized by the Transfer Center enaCom and the LAMARR Institute for Machine Learning and Artificial Intelligence. Focused on enhancing customer satisfaction prediction models, our team showcased skills in feature engineering and rigorously compared various ML models, ultimately selecting and fine-tuning CatBoost for optimal performance. Find more details here.
Contact
Meike Busch-Auf der Mauer
Administration for group of Jan Hasenauer
Carole Rossignol
Administration for group of Alexander Effland
Kevin Thurley
Group leader of Thurley Group
Address
53127 Bonn