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Forschungsgruppe .MIGS

Medizinische Informatik und Graphbasierte Systeme

Christian Weber is a lecturer at the University of Siegen, where he heads the Medical Informatics and Graph-Based Systems (.MIGS) research group at the Faculty of Natural Sciences and Technology at the University of Siegen together with Prof. Kai Hahn. From 2022 to 2024, he was the acting professor for the chair of Medical Data Science at the University of Siegen. Since 2017 he has been affiliated with the Institute of Knowledge Based Systems and Knowledge Management, University of Siegen. He acquired his PhD from the Corvinus University Budapest in Hungary, as part of a Marie Skłodowska-Curie Actions Doctoral Network, where he laid new foundations for knowledge intense, individualized learning path recommendations for vocational educational training in medical and industrial applications. His master’s degree (Diplom) he received from the University of Siegen in applied computer science. For the master thesis he was awarded the prize of excellence by his county. He is co-organizer of the International Conference on Integrated Systems, Design and Technology and was part of the ANR evaluation panel “Interfaces: Mathematics, Numerical Sciences – Biology, Health” in 2024 and 2025 and the chair for Research Funding of the 24k member Marie Currie Alumni Association 2018 till 2022. His research focuses on knowledge modelling and especially knowledge graphs, recommender systems, data analysis and practical applications of AI in the fields of medicine and education.

His current funded research projects include: the smart living and ambient assisted living GAiST (SmartLivingNEXT), where the goal is measuring and analyzing vital data with cloud connected medical sensors for sustaining self-sufficient living in elderly care homes; in the project FACE, holder ECG measurements are collected and analyzed on the edge and within the cloud, training machine learning solutions alongside indicators to decide on a flexible reallocation of models and computation; the IGNITE individual learning project aims at semantically representing, extracting and enriching learning pathways in higher education for personalized learning recommendations; in the German-Canadian collaboration CARES, decentralized vital data measurement with sensor kits and AI-based analysis for remote regions is in focus. Furthermore, he coordinates a medical teleconsultation implementation project between the university hospital of Bonn and Klinikum Siegen. 

Dr. Mubaris Nadeem ist wissenschaftlicher Mitarbeiter und Postdoktorand in der Arbeitsgruppe für Medizinische Informatik und Graphbasierte Systeme (.MIGS) an der Universität Siegen. Seine Promotion im Fach Informatik schloss er 2025 an der Universität Siegen am Lehrstuhl für Wissensbasierte Systeme und Wissensmanagement ab. In seiner Dissertation befasste er sich intensiv mit der Entwicklung hybrider Wissensgraphmodelle zur Echtzeit-Entscheidungsunterstützung im Rettungswesen (u. a. im Projekt KIRETT). Aktuell widmet er sich im Forschungsprojekt GAiST der Integration und Analyse von Vitaldaten. 

Jasmin Freudenberg ist wissenschaftliche Mitarbeiterin und Doktorandin in der Arbeitsgruppe für Medizinische Informatik und Graphbasierte Systeme (.MIGS) an der Universität Siegen.
In ihrer Dissertation konzentriert sie sich auf die Entwicklung KI-basierter Algorithmen zur Echtzeitanalyse von Vitalparametern. Derzeit ist sie im Forschungsprojekt FACE tätig, das sich mit der Langzeit-Analyse von Elektrokardiogrammen im Kontext von Edge- und Cloud-Computing befasst.