Papers

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

[16]Kevin Bruhwiler, Paahuni Khandelwal, Daniel Rammer, Samuel Armstrong, Sangmi Lee Pallickara, and Shrideep Pallickara. Lightweight, Embeddings Based Storage and Model Construction Over Satellite Data Collections. Proceedings of the IEEE International Conference on Big Data (IEEE BigData). Atlanta, USA. 2020.
[15]H. Homayouni, S. Ghosh, I. Ray, S. Gondalia, J. Duggan, M. G. Kahn. An Autocorrelation-based LSTM-Autoencoder for Anomaly Detection on Time-Series Data . IEEE International Conference on Big Data. Special Session on Machine Learning on Big Data. 2020.
[14]Daniel Rammer, Kevin Bruhwiler, Paahuni Khandelwal, Sam Armstrong, Shrideep Pallickara and Sangmi Pallickara. Small is Beautiful: Distributed Orchestration of Spatial Deep Learning Workloads. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. Leicester, UK. 2020.
[13]Daniel Rammer, Sangmi Lee Pallickara, and Shrideep Pallickara. Towards Timely, Resource-Efficient Analyses Through Spatially-Aware Constructs within Spark. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. Leicester, UK. 2020.
[12]Kevin Bruhwiler, Thilina Buddhika, Shrideep Pallickara and Sangmi Lee Pallickara. Iris: Amortized, Resource Efficient Visualizations of Voluminous Spatiotemporal Datasets. Proceedings of the IEEE/ACM International Conference on Big Data Computing, Applications and Technologies. 2020.
[11]Walid Budgaga, Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara. Concerto: Leveraging Ensembles for Timely, Accurate Model Training Over Voluminous Datasets. Proceedings of the IEEE/ACM International Conference on Big Data Computing, Applications and Technologies. 2020.
[10]Laurie S. and AghaKouchak A., Global snow drought hot spots and characteristics, Proceedings of the National Academy of Sciences of the United States of America. 2020.
[9]A Synthetic Water Distribution Network Model for Urban Resilience. Nasir Ahmad, Mikhail Chester, Emily Bondank, Mazdak Arabi, Nathan Johnson, and Benjamin Ruddell. (To appear) Journal of Sustainable and Resilient Infrastructure. 2020.
[8]Hajar Homayouni, Sudipto Ghosh, Indrakshi Ray, and Michael G. Kahn. An Interactive Data Quality Test Approach for Constraint Discovery and Fault Detection. Proceedings of the IEEE International Conference on Big Data (BigData) pp. 200-205. 2019. DOI: 10.1109/BigData47090.2019.9006446
[7]Sam Armstrong, Kevin Bruhwiler, and Sangmi Lee Pallickara, Rapid, Progressive Sub-Graph Explorations for Interactive Visual Analytics over Large-Scale Graph Datasets, Proceedings of the IEEE/ACM International Conference on Big Data Computing, Application, and Technology. 2019.
** Best Paper Award
[6]Daniel Rammer, Thilina Buddhika, Matthew Malensek, Shrideep Pallickara, and Sangmi Lee Pallickara. Enabling Fast Exploratory Analyses Over Voluminous Spatiotemporal Data Using Analytical Engines. (To appear) IEEE Transactions on Big Data. 2020.
[5]Kevin Bruhwiler and Shrideep Pallickara. Aperture: Fast Visualizations Over Spatiotemporal Datasets. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. Auckland, New Zealand. pp 31-40. 2019.
[4]Daniel Rammer, Sangmi Lee Pallickara, and Shrideep Pallickara. ATLAS: A Distributed File System for Spatiotemporal Data. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. Auckland, New Zealand. pp 11-20. 2019.
[3]Saptashwa Mitra, Paahuni Khandelwal, Shrideep Pallickara, and Sangmi Lee Pallickara. STASH: Fast Hierarchical Aggregation Queries for Effective Visual Spatiotemporal Explorations. IEEE International Conference on Cluster Computing (CLUSTER). Albuquerque, NM, USA. pp 1-11. 2019.
** Best Paper Award
[2]Matthew Malensek*, Walid Budgaga*, Ryan Stern*, Shrideep Pallickara, and Sangmi Lee Pallickara. Trident: Distributed Storage, Analysis, and Exploration of Multidimensional Phenomena. IEEE Transactions on Big Data. Vol. 5 (2) pp 252 265. 2019.
[1]Thilina Buddhika*, Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Synopsis: A Distributed Sketch over Voluminous Spatiotemporal Observational Streams. IEEE Transactions on Knowledge and Data Engineering. Vol. 29(11) pp 2552-2566. 2017.