Dr. Dipl.-Inform. Christian Weber
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.
Contact
Office address
Appointments by request.
Publications
OSCAR Focus Groups on Knowledge Graph and Graph- based Recommender System Evaluation
OSCAR Focus Groups on Knowledge Graph and Graph- based Recommender System Evaluation
Digit-DM: A Sustainable Data Mining Modell for Continuous Digitization in Manufacturing
Digit-DM: A Sustainable Data Mining Modell for Continuous Digitization in Manufacturing
Building Contextual Knowledge Graphs for Personalized Learning Recommendations Using Text Mining and Semantic Graph Completion
Building Contextual Knowledge Graphs for Personalized Learning Recommendations Using Text Mining and Semantic Graph Completion
OSCAR Knowledge Graph and Contextual, Graph-based Learning Path Recommendation Algorithm for the Personalized Learning Environment eDoer
OSCAR Knowledge Graph and Contextual, Graph-based Learning Path Recommendation Algorithm for the Personalized Learning Environment eDoer
Pedagogically-Informed Implementation of Reinforcement Learning on Knowledge Graphs for Context-Aware Learning Recommendations
Pedagogically-Informed Implementation of Reinforcement Learning on Knowledge Graphs for Context-Aware Learning Recommendations
KIRETT: Knowledge-Graph-Based Smart Treatment Assistant for Intelligent Rescue Operations
KIRETT: Knowledge-Graph-Based Smart Treatment Assistant for Intelligent Rescue Operations
Context based learning: a survey of contextual indicators for personalized and adaptive learning recommendations – a pedagogical and technical perspective
Context based learning: a survey of contextual indicators for personalized and adaptive learning recommendations – a pedagogical and technical perspective
Knowledge Graph Implementation and Contextual, Graph-based Learning Path Recommendation Roadmap for the Personalized Learning Environment in the OSCAR Project
Knowledge Graph Implementation and Contextual, Graph-based Learning Path Recommendation Roadmap for the Personalized Learning Environment in the OSCAR Project
Introducing a Sustainable, Request Driven Data Mining Model for Continuous Semiconductor Manufacturing Digitization
Introducing a Sustainable, Request Driven Data Mining Model for Continuous Semiconductor Manufacturing Digitization
OntoJob: Automated Ontology Learning from Labor Market Data
OntoJob: Automated Ontology Learning from Labor Market Data
OSCAR Conceptual and Technical Framework for Researcher Well-being and Career Development Training and Mentoring
OSCAR Conceptual and Technical Framework for Researcher Well-being and Career Development Training and Mentoring
Transferrable Framework Based on Knowledge Graphs for Generating Explainable Results in Domain-Specific, Intelligent Information Retrieval
Transferrable Framework Based on Knowledge Graphs for Generating Explainable Results in Domain-Specific, Intelligent Information Retrieval