Paahuni Khandelwal

According to our database, Paahuni Khandelwal authored at least 10 papers between 2019 and 2023.

Collaborative distances:

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

2023

Deep Learning based Approach for Fast, Effective Visualization of Voluminous Gridded Spatial Observations.

Paahuni Khandelwal, Menuka Warushavithana, Sangmi Lee Pallickara, Shrideep Pallickara

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

Enabling Fast, Effective Visualization of Voluminous Gridded Spatial Datasets.

Paahuni Khandelwal, Menuka Warushavithana, Sangmi Lee Pallickara, Shrideep Pallickara

Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

DISCERN: Leveraging Knowledge Distillation to Generate High Resolution Soil Moisture Estimation from Coarse Satellite Data.

Abdul Matin, Paahuni Khandelwal, Shrideep Pallickara, Sangmi Lee Pallickara

Proceedings of the IEEE International Conference on Big Data, 2023

ARGUS: Rapid Wildfire Tracking Using Satellite Data Collections.

Saptashwa Mitra, Paahuni Khandelwal, Shrideep Pallickara, Sangmi Lee Pallickara

Proceedings of the 16th IEEE International Conference on Cloud Computing, 2023

2022

Attention-based convolutional capsules for evapotranspiration estimation at scale.

Samuel Armstrong, Paahuni Khandelwal, Dhruv Padalia, Gabriel B. Senay, Darin Schulte, Allan A. Andales, F. Jay Breidt, Shrideep Pallickara, Sangmi Lee Pallickara

Environ. Model. Softw., 2022

CloudNet: A Deep Learning Approach for Mitigating Occlusions in Landsat-8 Imagery using Data Coalescence.

Paahuni Khandelwal, Samuel Armstrong, Abdul Matin, Shrideep Pallickara, Sangmi Lee Pallickara

Proceedings of the 18th IEEE International Conference on e-Science, 2022

2021

Mind the Gap: Generating Imputations for Satellite Data Collections at Myriad Spatiotemporal Scopes.

Paahuni Khandelwal, Daniel Rammer, Shrideep Pallickara, Sangmi Lee Pallickara

Proceedings of the 21st IEEE/ACM International Symposium on Cluster, 2021

2020

Small is Beautiful: Distributed Orchestration of Spatial Deep Learning Workloads.

Daniel Rammer, Kevin Bruhwiler, Paahuni Khandelwal, Samuel Armstrong, Shrideep Pallickara, Sangmi Lee Pallickara

Proceedings of the 13th IEEE/ACM International Conference on Utility and Cloud Computing, 2020

Lightweight, Embeddings Based Storage and Model Construction Over Satellite Data Collections.

Kevin Bruhwiler, Paahuni Khandelwal, Daniel Rammer, Samuel Armstrong, Sangmi Lee Pallickara, Shrideep Pallickara

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

STASH : Fast Hierarchical Aggregation Queries for Effective Visual Spatiotemporal Explorations.

Saptashwa Mitra, Paahuni Khandelwal, Shrideep Pallickara, Sangmi Lee Pallickara

Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019