Tatiana Lary

The University of Texas at Dallas

Papers

2

Total Citations

11

H-Index

2

About

Tatiana Lary is a pioneering researcher at the intersection of autonomous robotics, remote sensing, and machine learning. Her work focuses on developing intelligent robotic teams capable of rapidly characterizing unfamiliar environments without human intervention. Lary’s major contribution is a scalable, multi-robot paradigm that integrates hyper-spectral remote sensing, comprehensive in-situ sensing, and machine learning to autonomously learn environmental properties. This approach has direct applications in satellite calibration and validation, enabling more accurate Earth observation data. Her most-cited paper (2021) has garnered 8 citations, demonstrating growing recognition in the field. A second related publication (3 citations) further solidifies her impact. Lary’s research is notable for its practical relevance to environmental monitoring, precision agriculture, and disaster response, where rapid, autonomous data collection is critical. By combining robotics with advanced sensing and AI, she is advancing the frontier of autonomous scientific exploration, making her work essential reading for students and researchers interested in field robotics, sensor fusion, and adaptive learning systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
11
Total Citations
6
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: 10
🏛 Institutions: The University of Texas at Dallas

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago