Sara Zermani
Papers
1
Total Citations
18
H-Index
1
About
Sara Zermani is a leading researcher in the fields of autonomous systems, probabilistic modeling, and safe mission planning. Her work centers on integrating Bayesian Networks (BN) into autonomous vehicle architectures to enhance decision-making under uncertainty. In her highly cited 2020 paper, "Embedded Bayesian Network Contribution for a Safe Mission Planning of Autonomous Vehicles," Zermani demonstrates how BN-based intelligent monitors can dynamically assess environmental context, enabling vehicles to anticipate risks and adapt their behavior in real time. This contribution is pivotal for bridging the gap between theoretical AI models and practical, safety-critical deployment in transport and robotics. With over 18 citations on this work alone, her research has influenced subsequent studies in embedded probabilistic reasoning and autonomous navigation. Zermani’s approach stands out for its emphasis on explainability and robustness, offering a framework where vehicles not only react but proactively plan safe missions. Her achievements highlight a commitment to making autonomous systems more reliable and context-aware, a cornerstone for the next generation of intelligent transport.
Research Focus
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Top Papers
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