Jelena Pesic
Papers
1
Total Citations
8
H-Index
1
About
Jelena Pesic is a leading researcher in optical communications and fiber-optic sensing, with a focus on polarization-based event detection and classification. Her most-cited work, "Efficient Classification of Polarization Events Based on Field Measurements" (2020, 8 citations), introduces a novel approach to rare-event classification of polarization transients in optical networks. By combining field measurements with robot-generated fiber-disturbance data for data augmentation, Pesic's research addresses the critical challenge of detecting and classifying subtle polarization events that can disrupt network performance. Her comparative analysis of machine learning methods for accuracy and training sample efficiency provides practical guidance for implementing robust, real-time monitoring systems. This work has significant implications for improving the reliability and security of modern optical communication infrastructure, particularly in detecting physical disturbances to fiber cables. Pesic's contributions bridge the gap between theoretical machine learning and real-world field applications, offering scalable solutions for network operators. Her research continues to advance the field of intelligent optical network management, making her a valuable voice in the development of next-generation, self-healing communication systems.
Research Focus
Key Achievements
Top Papers
- 1