The Chair of Information Systems for the Service Industry at Saarland University focuses on the development and management of data-driven services as well as the use of artificial intelligence methods in areas such as industrial manufacturing, healthcare, wellness, and sports, among others. Under the leadership of Prof. Dr.-Ing. Wolfgang Maaß, the chair investigates how the application of experimental design methods in combination with distributed data analytic approaches leads to adaptive service designs and innovative business solutions. In cooperation with leading research and industry partners, this research is conducted in both fundamental and applied research projects. The research results are applied and validated in industrial projects of the Smart Service Engineering (SSE) research department at the German Research Center for Artificial Intelligence (DFKI).
AI at Any Cost? How Sustainability in and with AI Can Succeed
We are excited to announce that Prof. Wolfgang Maaß will be presenting at Hannover Messe. Under the title “AI at Any Cost? How Sustainability in and with AI Can Succeed,” Prof. Maaß will offer deep insights into the sustainable use of AI on Wednesday, April 24, 2024, from 1:10 PM to 1:55 PM, at the Tech Transfer Conference Stage in Hall 2 and online.
For more information check our DFKI website:
Picture: Oliver Dietze
Project: QUASIM
QUASIM, PAIRS & ESCADE @Hannover Messe 2024
We are happy to inform you that we will be presenting three of our research projects, all funded by Federeal Ministry for Economics and Climate Action (BMWK) from April 22 – 26 at the prestigious Hannover Messe. Find us at booth B10 in hall 2.
For more information about our exhibits check our DFKI website: https://www.dfki.de/en/web/news-media/events/hm2024
As well as the QUASIM press release: https://www.uni-saarland.de/aktuell/hannover-messe-quasim-31008.html
Wolfgang Maaß is professor in Business Informatics at Saarland University, scientific director at Deutsche Forschungszentrum für Künstliche Intelligenz (DFKI), and adjunct professor Stony Brook University Health Sciences Center School of Medicine, NY.
Incorporating Metabolic Information into LLMs for Anomaly Detection in Clinical Time-Series (2024). In NeurIPS 2024 Workshop on Time Series in the Age of Large Models. NeurIPS, Vancouver, Canada. pdf
Semantic Priming via Knowledge graphs to analyze and treat language model’s Honest lies. Proc. International Conference on Information Systems (ICIS), Bangkok, Thailand. link
Quantum Computing Enhanced Service Ecosystem for Simulation in Manufacturing. arXiv preprint arXiv:2401.10623. published in: Künstl Intell (2024). pdf