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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. 

Publications

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Conference paper
2022

OntoJob: Automated Ontology Learning from Labor Market Data

Conference paper
2022

Adding Context to Industry 4.0 Analytics: A New Document Driven Knowledge Graph Construction and Contextualization Approach

Conference paper
2022

KIRETT - A wearable device to support rescue operations using artificial intelligence to improve first aid

Journal article
2022

Transferrable Framework Based on Knowledge Graphs for Generating Explainable Results in Domain-Specific, Intelligent Information Retrieval

Conference paper
2021

Enhancing Design-relevant Document Search and Visibility through Fusion of Multi-sourced Data in Knowledge Graphs

Conference paper
2021

Branch selection and data optimization for selecting machines for processes in semiconductor manufacturing using AI-based predictions

Journal article
2021

Knowledge Integration in Smart Factories

Conference paper
2021

Explainable Job-Posting Recommendations Using Knowledge Graphs and Named Entity Recognition

Conference paper
2021

Clustering Wafer Defect Patterns Within the Semiconductor Industry Based on Wafer Maps, Using an Agile Unsupervised Deep Learning Approach

Other
2021

A text extraction-based smart knowledge graph composition for integrating lessons learned during the microchip design

Other
2021

Explainable graph-based search for lessons-learned documents in the semiconductor industry

Conference paper
2020

Yield prediction in semiconductor manufacturing using an AI-based cascading classification system