Chair of Business Informatics
Saarland University

The goal of ESCADE (Energy-Efficient Large-Scale Artificial Intelligence for Sustainable Data Centers) is to significantly improve the sustainability of AI applications by reducing data center energy consumption.

The goal of the project “QC-Enhanced Service Ecosystem for Simulation in Manufacturing" (QUASIM) is to develop and test algorithms and technologies of quantum computing for critical simulation challenges in manufacturing. This involves integrating QC into Industry 4.0 frameworks as “Quantum-as-a-Service" (QaaS) and facilitating knowledge transfer for production-oriented simulation based on QC.

Anti-doping analysis is vital for combating cheating in sports, with the Athlete Biological Passport monitoring haematological and steroidal markers. WADA's (World Anti-Doping Agency) recent findings highlight the risk of urine sample swapping, where athletes substitute their sample with a clean one to evade detection. To address this, DNA analysis is used to confirm suspicious cases, guided by factors like sport demands, past violations, and athlete intelligence. However, identifying swapped samples requires an adaptive model to flag mismatched samples based on steroid profile similarities. This project aims to develop an AI-driven pattern recognition tool to analyze steroid profiles, identify key indicators, and deploy advanced deep learning algorithms, creating a robust pipeline to detect sample substitution efficiently.

Adaptive and personalized AI systems in healthcare rely on user and situational data to provide optimal support. However, patients facing illness, pain, or complex therapeutic decisions often experience cognitive impairments, leading to incomplete or biased data that hinder informed decision-making. The FEDWELL project explores artificial mental models (AMMs) in adaptive AI systems to address these challenges, focusing on rehabilitation after knee/hip surgeries and therapy decisions for cognitively impaired patients (e.g., MS, dementia). By integrating AMMs, structured surveys, contextual data, and machine learning, FEDWELL aims to align AI recommendations with patient needs and preferences.

The CircularSaar project supports Saarland's transition towards a sustainable circular economy in industries like automotive, machinery, and steel. With €33 million in funding, this initiative is led by researchers from Saarland University, Fraunhofer IZFP, and IZES. The project develops AI-driven strategies for optimizing material reuse, repair, recycling, and energy recovery while ensuring economic and ecological sustainability.

The PAIRS project, initiated by Advaneo and funded with €10 million, is developing an AI-driven crisis management data space. Its hybrid AI technology anticipates crisis events and reactions to generate targeted recommendations for action, supporting decision-making during emergencies.

Disruptions in production range from material quality issues and machine damage to power outages and workforce shortages. The SPAICER research project develops AI-driven resilience management tools to help production systems anticipate and adapt to these disruptions. By leveraging advanced AI technologies and Industry 4.0 standards, SPAICER enables improved production planning and response strategies through a modular, agent-based ecosystem for data, software, and model sharing.

EVAREST aims to optimize food production by leveraging comprehensive data analysis and integration. By enabling food producers to view themselves as data providers, the project supports a global ecosystem that includes industries like fertilizers, finance, and meteorology. These data products allow farmers, wholesalers, and processors to make informed decisions on crop conditions, pricing, and future planning, benefiting stakeholders across the supply chain.

SmaPron leverages IoT and AI technologies to enable intelligent, self-optimizing production systems for the manufacturing industry, increasing efficiency and adaptability in dynamic environments.

INTElligente GRüne MobilitAeT im Saarland: Ein Servicekonzept

AI-based Detection of Steroid Sample Swapping in the Anti-Doping Area and Analysis of the Associated Decision-Making Processes

Development of AI-based Screening Tool to Detect Identical Urine Samples within the Athlete Biological Passport

Energie-Flexibilität für Industrie und Gewerbe durch Digitale Zwillinge

Personalized Cardiovascular Risk Prediction through AI-Driven Genomic Analysis