Lakitha O. H. Wijeratne

According to our database, Lakitha O. H. Wijeratne authored at least 6 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Characterizing Water Composition with an Autonomous Robotic Team Employing Comprehensive In Situ Sensing, Hyperspectral Imaging, Machine Learning, and Conformal Prediction.

John Waczak, Adam R. Aker, Lakitha O. H. Wijeratne, Shawhin Talebi, Ashen Fernando, Prabuddha M. H. Dewage, Mazhar Iqbal, Matthew D. Lary, David Schaefer, David John Lary

Remote. Sens., March, 2024

2022

Decoding Physical and Cognitive Impacts of Particulate Matter Concentrations at Ultra-Fine Scales.

Shawhin Talebi, David John Lary, Lakitha O. H. Wijeratne, Bharana Fernando, Tatiana Lary, Matthew D. Lary, John Sadler, Arjun Sridhar, John Waczak, Adam R. Aker, Yichao Zhang

Sensors, 2022

High Spatial-Temporal PM2.5 Modeling Utilizing Next Generation Weather Radar (NEXRAD) as a Supplementary Weather Source.

Xiaohe Yu, David John Lary, Christopher S. Simmons, Lakitha O. H. Wijeratne

Remote. Sens., 2022

2021

Machine Learning for Light Sensor Calibration.

Yichao Zhang, Lakitha O. H. Wijeratne, Shawhin Talebi, David John Lary

Sensors, 2021

Autonomous Learning of New Environments with a Robotic Team Employing Hyper-Spectral Remote Sensing, Comprehensive In-Situ Sensing and Machine Learning.

David John Lary, David Schaefer, John Waczak, Adam R. Aker, Aaron Barbosa, Lakitha O. H. Wijeratne, Shawhin Talebi, Bharana Fernando, John Sadler, Tatiana Lary, Matthew D. Lary

Sensors, 2021

2020

Using Machine Learning for the Calibration of Airborne Particulate Sensors.

Lakitha O. H. Wijeratne, Daniel R. Kiv, Adam R. Aker, Shawhin Talebi, David John Lary

Sensors, 2020