Prof. Dr.-Ing. Martin Ruskowski

Organizational unit Innovative Factory Systems

Contact +49 631 20575 3400 (Kaiserslautern)

Address (Kaiserslautern) Trippstadter Straße 122D-67663 KaiserslauternDeutschland

Publications

Alexander Schultheis; Benjamin Alt; Sebastian Bast; Achim Guldner; David Jilg; Darko Katic; Johannes Mundorf; Tobias Schlagenhauf; Sebastian Weber; Ralph Bergmann; Simon Bergweiler; Lars Creutz; Guido Dartmann; Lukas Malburg; Stefan Naumann; Mahdi Rezapour; Martin Ruskowski

In: KI - Künstliche Intelligenz, German Journal on Artificial Intelligence - Organ des Fachbereiches "Künstliche Intelligenz" der Gesellschaft für Informatik e.V. (KI), Springer, 9/2024.

Manuel Reif; Mohammad Hossein Rimaz; Christiane Plociennik; Martin Ruskowski; Alexander David

In: atp - Automatisierungstechnische Praxis, Vol. 66, No. 4, Pages 58-65, Vulkan-Verlag, 4/2024.

Leonhard Kunz; Manuel Reif; Teresa Petzsche; Anne Schmallenbach; Christiane Plociennik; Martin Ruskowski

In: IFAC-PapersOnLine. IFAC Symposium on Information Control Problems in Manufacturing (INCOM-2024), Pages 235-240, Vol. 58, Elsevier, 1/2024.

All publications

Profile

Short Biography

Prof. Dr.-Ing. Martin Ruskowski is Head of the Innovative Factory Systems research department at the German Research Center for Artificial Intelligence (DFKI) and is Chair of the Department of Machine Tools and Control Systems at the University Kaiserslautern-Landau (RPTU) and chairman of the board of the technology initiative SmartFactory KL. His major research focus is on the development of innovative control concepts for automation, artificial intelligence in automation technology and industrial robots as machine tools. Prior to these positions, Ruskowski held several management positions at industrial firms, most recently as Vice President for Global Research and Development at KUKA Industries Group.

STAR
Safe and Trusted Human Centric ARtificial Intelligence in Future Manufacturing Lines
STAR is a joint effort of AI and digital manufacturing experts towards enabling the deployment of standard-based secure, safe and reliable human-centric AI systems in real-life manufacturing…
PHYSICS
Optimized hybrid space-time service continuum in FAAS
PHYSICS’s vision is to address the aforementioned challenges and empower application developers, platform owners and infrastructure providers (e.g. Cloud, Edge etc). For the former, the goal is to…
ReCircE
Digital Lifecycle Record for the Circular Economy
Kunststoffmüll ist ein Problem. Weltweit. Der Grund: Kunststoff ist meist verbaut und Teil eines komplexen Produktes: Auto, Kühlschrank, Lederschuh oder Smartphone. Materialanalyse, -trennung und…
MAS4AI
Multi-Agent Systems for Pervasive Artificial Intelligence for assisting Humans in Modular Production Environments
Development of a multi-agent-based technology for the integration of AI algorithms in autonomous modular production with worker assistance.
Partners
- DMD Med Tech
- InTechCentras
- LMS
- tecnalia
- aimen
- TNO
- …
RACKET
Rare Class Learning and Unknown Events Detection for Flexible Production
The RACKET project addresses the problem of detecting rare and unknown faults by combining model-based and machine learning methods. The approach is based on the assumption that a physical or…