Artificial Intelligence

Competences

Our research department specialises in the areas of decentralised information processing, edge computing and the integration of cyber-physical systems (CPS) and Internet of Things (IoT) technologies. We focus on the design and implementation of algorithms that facilitate the efficient processing and analysis of the data generated by these systems, with the aim of improving their interoperability, responsiveness and usability in real-world applications.

By broadening our horizons, we are delving into semantic AI to enable machines to not only ‘read’ data, but to ‘understand’ it in the context of human cognition. This endeavour involves creating algorithms to interpret complex data structures and the meanings behind human language, improving human-machine interaction through more intuitive and effective systems.

Open invitation to collaborate: We are interested in exploring new projects and collaborations that leverage our expertise to create innovative solutions. Whether it's applying semantic AI in new areas, advancing sustainable technology or tackling societal challenges, we invite partners from academia, industry and the start-up ecosystem to join us on this journey to create transformative technological solutions.

Head of Research Department

Dr. Lejla Begic Fazlic
Dr. Lejla Begic Fazlic
Beschäftigte FB Umweltplanung/Umwelttechnik - FR Informatik

Contact

+49 6782 17-1731

Location

Birkenfeld | Building 9925 | Room 111

Publications

2022
  • L. Begic Fazlic, A. Halawa, A. Schmeink, R. Lipp, L. Martin, A. Peine, M. Morgen, T. Vollmer, S. Winter, and G. Dartmann. A novel hybrid methodology for anomaly detection in time series. International Journal of Computational Intelligence Systems, 15(1):1-16, 2022,  highlighting our expertise in handling complex data analysis challenges.
2021
  • Peine, A. Hallawa, J. Bickenbach, G. Dartmann, L. B. Fazlic, A. Schmeink, G. Ascheid, C. Thiemermann, A. Schuppert, R. Kindle, L. Celi, G. Marx, and L. Martin. Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care. https://www.nature.com/articles/s41746-021-00388-6.pdf  npj Digit. Med., 2021, showcasing our commitment to impactful healthcare innovations.

Current Projects

Completed Projects

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