Malte Neuss
Papers
1
Total Citations
9
H-Index
1
About
Malte Neuss is a researcher at the forefront of self-adaptive cyber-physical systems (CPSs), focusing on how autonomous agents like robots, drones, and self-driving cars can make reliable decisions under uncertainty. His work centers on run-time reasoning, multi-agent coordination, and the application of subjective logic to model uncertain observations in decentralized systems. Neuss’s most-cited paper, "Run-Time Reasoning from Uncertain Observations with Subjective Logic in Multi-Agent Self-Adaptive Cyber-Physical Systems" (2021, 9 citations), addresses a critical challenge in modern society: ensuring that autonomous CPSs act dependably despite exposure to dynamic, unpredictable environments. By integrating subjective logic into multi-agent self-adaptation, he provides a formal framework for reasoning about conflicting or incomplete sensor data at run-time, enabling more robust and trustworthy system behavior. This contribution is particularly significant for safety-critical applications, where uncertainty can lead to catastrophic failures. Neuss’s work bridges theoretical foundations with practical engineering, offering actionable insights for developing resilient, decentralized autonomous systems. His research continues to shape how next-generation CPSs manage uncertainty, making him a key voice in the evolution of self-adaptive and autonomous technologies.
Research Focus
Key Achievements
Top Papers
- 1