Journals
Daniel Rammer, Thilina Buddhika, Matthew Malensek, Shrideep Pallickara, and Sangmi Lee Pallickara. Enabling Fast Exploratory Analyses Over Voluminous Spatiotemporal Data Using Analytical Engines. IEEE Transactions on Big Data. 2019. [5.16 Impact Factor]
Conferences
Paahuni Khandelwal, Daniel Rammer, Shrideep Pallickara and Sangmi Pallickara. Mind the Gap: Generating Imputations for Satellite Data Collections at Myriad Spatiotemporal Scopes. IEEE International Symposium on Cluster Computing and the Grid (IEEE CCGrid). Melbourne, Australia. 2021. [26% Acceptance Rate]
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 13th IEEE/ACM Conference on Utility and Cloud Computing. Leicester, UK. 2020. [31% Acceptance Rate]
Daniel Rammer, Sangmi Lee Pallickara, and Shrideep Pallickara. Towards Timely, Resource-Efficient Analyses Through Spatially-Aware Constructs within Spark. Proceedings of the 13th IEEE/ACM Conference on Utility and Cloud Computing. Leicester, UK. 2020. [31% Acceptance Rate]
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. [15.7% Acceptance Rate]
Daniel Rammer, Sangmi Lee Pallickara, and Shrideep Pallickara. ATLAS: A Distributed File System for Spatiotemporal Data. Proceedings of the 12th IEEE/ACM Conference on Utility and Cloud Computing. Auckland, NZ. 2019. [29.2% Acceptance Rate]
Daniel Rammer, Walid Budgaga, Thilina Buddhika, Shrideep Pallickara, and Sangmi Lee Pallickara. Alleviating I/O Inefficiencies to Enable Effective Model Training Over Voluminous, High-Dimensional Datasets. Proceedings of the IEEE International Conference on Big Data (IEEE BigData). Seattle, USA. 2018. [18.9% Acceptance Rate]
Dissertation
Daniel Rammer. Harnessing Spatiotemporal Data Characteristics to Facilitate Large-Scale Analytics Over Voluminous, High-Dimensional Observational Datasets. PhD Dissertation, Colorado State University. September 2021. Advisors: Shrideep Pallickara and Sangmi Lee Pallickara.