iCoSys
The partner of choice for industrial digitalization
iCoSys leverages artificial intelligence and complex systems to boost industrial innovation. Our solutions draw on the latest developments in informatics, data science, distributed computing, software engineering and mathematical modeling.
Proven experience working with «systems of systems»
A booming field of research and development
Knowledge and technology transfer
Research focus areas
iCoSys projects stand out for their emphasis on responsible development. iCoSys prioritizes sustainability-focused initiatives that contribute to the development of the economy and of the educational system.
Applied artificial intelligence and machine learning
- Artificial intelligence
- Machine learning
- Big data analysis
- Signal processing
- Algorithms, and, more generally, information systems involving complex data processing
Distributed computing
- Architecture and programming of parallel and large-scale distributed systems
- Middleware for programming and monitoring of large-scale distributed systems
- Mobile systems
Sustainable ICT for smart living
- Data management and processing for sensor networks
- Web of Things
- Machine learning applied to smart cities, smart buildings and smart living
- IT for efficiency approaches
ICT for Industry 4.0
- Smart solutions for industries including anomaly detection, simulation of systems, quality assessment and prediction, information indexing and predictive maintenance
Facilities
The iCoSys institute relies on state-of-the-art infrastructure for its advanced research and development projects, including computation clusters, Kubernetes clusters and object storage clusters.
Education
Bachelor in Computer science and communication systems
Custom training programs on the topics of Data Science, Machine Learning, Software Engineering and Agile Team Structures are available at the request of companies and partners.
Contact
Jean Hennebert
Full Professor UAS/Institute Head
Office
HEIA_D20.05
Phone
+41 26 429 65 96
E-mail
jean.hennebert@hefr.ch