RELIANT Industrial graduate school: Reliable, Safe and Secure Intelligent Autonomous Systems

The industrial research school RELIANT targets reliable, safe and secure intelligent autonomous Cyber-Physical Systems (CPS) and aims to be instrumental in development and deployment of the latest research results regarding intelligent autonomous systems in Swedish industry. Our partners are found within vehicle solutions in transportation and construction, autonomous and intelligent systems, as well as electronics and software for autonomous systems. The results of RELIANT will support all business sectors where next generation products are assumed to have autonomous functionality with maintained or increased reliability, safety and security.

RELIANT aims to make significant advances in technology and methodology for development of intelligent autonomous high-performance CPS and use of such systems in modern industries. The results should be able to use COTS (Commercial-of-The-Shelf) components and development tools, making our results directly applicable to industry. RELIANT will target the conjunction of autonomy and reliability in combination with safety and security, with the goal to integrate all this into CPS. A key aspect of RELIANT is to address such problems through the collective experience facilitated by the virtual use-case concept.

RELIANT is an integral part of the strategic research area of Mälardalen University (MDU) affiliated with the School of Innovation, Design and Engineering (IDT) and comprising three complementary activities:

• Research, organized in the form of PhD research projects in real industrial contexts. The PhD students will work in close cooperation with senior researchers at MDU, industrial specialists, and international researchers and experts.
• Networking activities, with the goal of establishing strong networks between PhD students, industrial specialists and managers, as well as with prominent international and national researchers.
• Courses, seminars, and activities related to interdisciplinary competence, especially targeting engineering of the next generation of reliable, safe and secure intelligent autonomous CPS.

RELIANT spins off, and complements, the ongoing KKS research profile DPAC (http://www.es.mdh.se/dpac/) at MDU. In RELIANT we further extend the network of participating companies in the DPAC ecosystem, and we draw upon the existing research results we gained on dependable and safe CPS.

• RELIANT industrial research school 2023-3.pdf

[Show all publications]

Machine Learning-Based Prognostic Approaches for Construction Equipment Powertrain Systems (Jun 2025)
Zafer Yigit, Håkan Forsberg, Masoud Daneshtalab
36th IEEE Intelligent Vehicles Symposium (IEEE IV2025)

Learning single and compound-protocol automata and checking behavioral equivalences (Apr 2025)
Stefan Marksteiner, David Schögler , Marjan Sirjani, Mikael Sjödin
International Journal on Software Tools for Technology Transfer (STTT)

Black-box protocol testing using Rebeca and Automata Learning (Mar 2025)
Stefan Marksteiner, Mikael Sjödin
Marjan Festschrift (part of FSEN 2025) (MarjanFest)

The Importance of a System-Level Approach when Bringing in New Technologies in Avionics (Oct 2024)
Håkan Forsberg, Kristina Forsberg, Joakim Lindén
43rd Digital Avionics Systems Conference (DASC) (DASC'43)

Enhancing Drone Surveillance with NeRF: Real-World Applications and Simulated Environments (Oct 2024)
Joakim Lindén, Giovanni Burresi , Håkan Forsberg, Masoud Daneshtalab, Ingemar Söderquist
43rd Digital Avionics Systems Conference (DASC) (DASC'43)

Automated Passport Control: Mining and Checking Models of Machine Readable Travel Documents (Jul 2024)
Stefan Marksteiner, Marjan Sirjani, Mikael Sjödin
The 19th International Conference on Availability, Reliability and Security (ARES 2024) (ARES 2024)