Anura P. Jayasumana
Papers
4
Total Citations
26
H-Index
3
About
Anura P. Jayasumana is a leading researcher in wireless sensor networks, with a focus on topology mapping and localization in complex, resource-constrained environments. His major contributions center on developing maximum likelihood estimation (MLE) techniques for constructing topology maps—abstract representations of node layout and connectivity—in both 2D and 3D sensor networks. Notably, his work addresses the challenge of mapping when physical distance measurements (e.g., via signal strength) are unreliable or unavailable, a common issue in real-world deployments. His 2016 and 2017 papers on MLE-based topology mapping for wireless sensor networks, each garnering 8 citations, are foundational in this area. He has also advanced the field by extending these techniques to millimeter wave (mmWave) sensor networks with directional antennas, crucial for next-generation, high-bandwidth applications. Additionally, his work on robust Kalman filter-based decentralized target search and prediction demonstrates practical applications for tracking in connectivity-only environments. Jayasumana’s research bridges theoretical estimation algorithms with practical sensor network challenges, making his work highly relevant for students and engineers working on IoT, autonomous systems, and spatial intelligence in constrained wireless environments.
Research Focus
Key Achievements
Top Papers
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