Lakitha O. H. Wijeratne

The University of Texas at Dallas

Papers

4

Total Citations

21

H-Index

3

About

Lakitha O. H. Wijeratne is a researcher working at the intersection of autonomous robotics, remote sensing, and machine learning, with a particular focus on environmental monitoring and characterization. His work centers on developing intelligent robotic systems capable of rapidly learning and adapting to previously unseen environments, combining hyperspectral imaging, comprehensive in-situ sensing, and advanced machine learning techniques into cohesive, scalable frameworks. Among his most significant contributions is the development of autonomous robotic team paradigms that address real-world challenges in satellite calibration and validation — work that has garnered over ten citations and demonstrated practical relevance to large-scale environmental sensing operations. More recently, Wijeratne has applied these methods to the pressing problem of inland water quality monitoring, where traditional remote sensing struggles with spectral complexity and small-scale variability. His innovative integration of conformal prediction with hyperspectral imaging and in-situ data collection offers a promising solution to the costly and time-intensive nature of reference data collection, accumulating citations across multiple publications on the topic. Wijeratne's research represents a meaningful step forward in making autonomous environmental sensing systems both scientifically rigorous and operationally practical.

Research Focus

Key Achievements

3
H-Index
4
Papers
21
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Autonomous Learning of New Environments With a Robotic Team Employing Hyper-Spectral Remote Sensing, Comprehensive In-Situ Sensing and Machine Learning
8 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: The University of Texas at Dallas

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago