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Journal Articles

[J21] Daniel Rammer*, Thilina Buddhika, Matthew Malensek*, Shrideep Pallickara, and Sangmi Lee Pallickara. (To appear) Enabling Fast Exploratory Analyses Over Voluminous Spatiotemporal Data Using Analytical Engines. IEEE Transactions on Big Data. 2021 pdf
[J20] Thilina Buddhika, Matthew Malensek*, Shrideep Pallickara, and Sangmi Lee Pallickara. Living on the Edge: Data Transmission, Storage, and Analytics in Continuous Sensing Environments. ACM Transactions on Internet of Things. Vol. 2 (3), pp 1-31, 2021. . IEEE Transactions on Parallel and Distributed Systems.Vol. 32(8), 2005-2020, 2021. pdf
[J19]
Thilina Buddhika, Sangmi Lee Pallickara, and Shrideep Pallickara. Pebbles: Leveraging Sketches for Processing Voluminous, High Velocity Data Streams. IEEE Transactions on Parallel and Distributed Systems. Vol. 32(8): 2005-2020. 2021.
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[J18] 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. [Impact Factor: 5.67] pdf
[J17] Naman Shah*, Matthew Malensek*, Harshil Shah*, Shrideep Pallickara, and Sangmi Lee Pallickara, Scalable Network Analytics for Characterization of Outbreak Influence in Voluminous Epidemiology Datasets. (To appear) Concurrency and Computation: Practice & Experience. John-Wiley. 2018 pdf
[J16] Matthew Malensek*, Walid Budgaga*, Ryan Stern, Shrideep Pallickara, and Sangmi Lee Pallickara, Trident: Distributed Storage, Analysis, and Exploration of Multidimensional Phenomena. (To appear) IEEE Transactions on Big Data. 2018. pdf
[J15] 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. pdf
[J14] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Hermes: Federating Fog and Cloud Nodes to Support Query Evaluations in Continuous Sensing Environments. IEEE Cloud Computing. Vol. 4(2) pp 54-62. 2017 pdf
[J13] Walid Budgaga*, Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. A Framework for Scalable Real-Time Anomaly Detection over Voluminous, Geospatial Data Streams. Concurrency and Computation: Practice & Experience. John-Wiley. 2017. pdf
[J12] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Fast, Ad Hoc Query Evaluations over Multidimensional Geospatial Datasets. IEEE Transactions on Cloud Computing, Vol. 29(12) pp 1-16. John-Wiley, 2017. pdf
[J11] Cameron Tolooee*, Matthew Malensek*, and Sangmi Lee Pallickara A Scalable Framework for Continuous Query Evaluations over Multidimensional, Scientific Datasets. Concurrency and Computation: Practice and Experience. 28(8): pp. 2546-2563. 2016.
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[J10] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Analytic Queries over Geospatial Time-Series Data using Distributed Hash Tables. IEEE Transactions on Knowledge and Data Engineering. Vol. 28(6): pp.1408-1422. 2016.
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[J9] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Autonomous Data Management and Federation to Support High-throughput Query Evaluations over Voluminous Datasets. IEEE Cloud Computing. Vol. 3 (3). 2016. pdf
[J8] Walid Budgaga*, Matthew Malensek*, Sangmi Lee Pallickara, Neil Harvey, Jay Breidt, and Shrideep Pallickara. Predictive Analytics Using Statistical, Learning, and Ensemble Methods to Support Real- Time Exploration of Discrete Event Simulations. Future Generation Computer Systems. Elsevier. Volume 56, March, Pages 360–374. 2016. pdf
[J7] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Minerva: Proactive Disk Scheduling for QoS in Multi-Tier, Multi-Tenant Cloud Environments. IEEE Internet Computing. Vol. 20 (3). 2016. pdf
[J6] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Geometry and Proximity Constrained Query Evaluations over Large Geospatial Datasets Using Distributed Hash Tables. IEEE Computing in Science and Engineering (CiSE). Special Issue on Extreme Data. Vol. 16(4) pp 53-60. 2014. pdf
[J5] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. “Exploiting Geospatial and Chronological Characteristics in Data Streams to Enable Efficient Storage and Retrievals,” Future Generation Computer Systems. Vol. 29(4), pp. 1049-1061. Elsevier. 2013. pdf
[J4] Sangmi Lee Pallickara, Shrideep Pallickara, and Milija Zupanski, “Enabling Efficient Data Search and Subsetting of Large-scale Atmospheric Datasets,” Future Generation Computer Systems, Vol. 28(1): pp. 112-118. Elsevier. 2012. pdf
[J3] Marlon Pierce, Xiaoming Gao, Sangmi Lee Pallickara, Zhenhua Gau, and Geoffrey Fox, “QuakeSim Portal and Services: New Approaches to Science Gateway Development Techniques,” Concurrency & Computation: Practice & Experience. 22(12): pp.1732- 1749 (2010) pdf
[J2] Beth Plale, Dennis Gannon, Yi Huang, Gopi Kandaswamy, Sangmi Lee Pallickara, and Aleksander Slominski, “Cooperating Services for Managing Data Driven Computational Experimentation,” IEEE Computing in Science and Engineering (CiSE) , (Vol. 7, No. 5) pp. 34-43. 2005. pdf
[J1] Geffrey Fox, Sung-Hoon Ko, Marlon Pierce, Ozgur Balsoy, Jungkee Kim, Sangmi Lee, Kangseok Kim, Sangyoon Oh, Xi Rao, Mustafa Varank, Hasan Bulut, Guruhan Gunduz, Xiahong Qui, Shrideep Pallickara, Ahmet Uyar, “Grid Services for Earthquake Science,” Concurrency and Computation: Practice and Experience in ACES Special Issue, 14(6-7), 371-393, 2002. pdf

 

Refereed Conference Proceedings

[C48] Saptashwa Mitra*, Daniel Rammer*, Shrideep Pallickara, and Sangmi Lee Pallickara. Glance: A Generative Approach to Interactive Visualization of Voluminous Satellite Imagery. (To appear) Proceedings of the IEEE International Conference on Big Data (IEEE BigData). 2021
[C47]

Menuka Warushavithana*, Saptashwa Mitra*, Mazdak Arabi, Jay Breidt, Sangmi Lee Pallickara, and Shrideep Pallickara, A Transfer Learning Scheme for Time Series Forecasting Using Facebook Prophet. (To appear) Proceedings of the 2021 IEEE International Conference on Cluster Computing (CLUSTER). 2021.

[C46] Saptashwa Mitra*, Daniel Rammer*, Shrideep Pallickara, and Sangmi Lee Pallickara. A Generative Approach to Visualizing Satellite Data. (To appear) Proceedings of the 2021 IEEE International Conference on Cluster Computing (CLUSTER). 2021.
[C45] Paahuni Khandelwal*, Daniel Rammer*, Shrideep Pallickara, and Sangmi Lee Pallickara. Mind the Gap: Generating Imputations for Satellite Data Collections at Myriad Spatiotemporal Scopes. (To appear) Proceedings of the 21st IEEE/ACM international Symposium on Cluster, Cloud and Internet Computing (CCGrid). 2021. Melbourne, Australia [26% acceptance rate] pdf
[C44] 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. [15.5% acceptance rate] pdf
[C43] 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. [31% acceptance rate] pdf
[C42] Daniel Rammer*, Kevin Bruhwiler*, Paahuni Khandelwal*, Samuel Armstrong*, Shrideep Pallickara, and Sangmi Lee 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 [31% Acceptance Rate] pdf
[C41] 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. Leicester, UK. 2020. pdf
[C40] 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. Leicester, UK. 2020. pdf
[C39] 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, Auckland, New Zealand, 2019. [27.7 % acceptance rate] ** Best Paper Award pdf
[C38] 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. 2019. [29% acceptance rate] pdf
[C37] Saptashwa Mitra*, Paahuni Khandelwal*, Shrideep Pallickara, and Sangmi Lee Pallickara, STASH: Fast Hierarchical Aggregation Queries for Effective Visual Spatiotemporal Explorations, Proceedings of the IEEE International Conference on Cluster Computing (CLUSTER), Albuquerque, New Mexico, 2019. [27% acceptance rate] ** Best Paper Award pdf
[C36] Bibek Shrestha*, Saptashwa Mitra*, and Sangmi Lee Pallickara, STRETCH: In-memory Storage With Autoscaling For Cluster Computing, Proceedings of the IEEE International Conference on Cloud Computing (IEEE CLOUD), Milan, Italy, 2019. [20.8% acceptance rate] pdf
[C35] 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] pdf
[C34] Saptashwa Mitra*, and Sangmi Lee Pallickara, Confluence: Adaptive Spatiotemporal Data Integration Using Distributed Query Relaxation Over Heterogeneous Observational Datasets, Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing (UCC), Zurich, Switzerland 2018 pdf
[C33] Max Roselius* and Sangmi Lee Pallickara, Enabling High-throughput Georeferencing for Phenotype Monitoring over Voluminous Observational Data, Proceedings of the IEEE International Conference on Big Data and Cloud Computing (BDCloud2018), Melbourne, Australia, 2018. [27% acceptance rate] ** Finalist for Best Paper Award pdf
[C32] Saptashwa Mitra*, Yu Qiu*, Haley Moss, Kaigang Li, and Sangmi Lee Pallickara. Effective Integration of Geotagged, Ancillary Longitudinal Survey Datasets to Improve Adulthood Obesity Predictive Models.Proceedings of the IEEE Big Data Science and Engineering (IEEE BigDataSE). New York, USA, 2018. pdf
[C31] Johnson Charles Kachikaran Arulswamy*, and Sangmi Lee Pallickara. Columbus: Enabling Scalable Scientific Workflows for Fast Evolving Spatio-Temporal Sensor Data.Proceedings of the the 14th IEEE International Conference of Service Computing (IEEE SCC). pp.9-18. Honolulu, Hawaii, USA, 2017 [20% acceptance rate] pdf
[C30] Naman Shah*, Harshil Shah*, Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Network Analysis for Identifying and Characterizing Disease Outbreak Influence from Voluminous Epidemiology Data. (To appear) Proceedings of the IEEE International Conference on Big Data (IEEE BigData). Washington D.C., USA. 2016.    [18.68% acceptance rate] pdf
[C29] Cameron Tolooee*, Sangmi Lee Pallickara and Asa Ben-Hur. Mendel: A Distributed Storage Framework for Similarity Searching over Sequencing Data. Proceedings of the 30th IEEE International Parallel & Distributed Processing Symposium (IPDPS). pp. 790-799. Chicago, USA, 2016.    [23% acceptance rate] pdf
[C28] Matthew Malensek*, Sangmi Lee Pallickara and Shrideep Pallickara. Alleviation of Disk I/O Contention in Virtualized Settings for Data-Intensive Computing.IEEE/ACM International Symposium on Big Data Computing. Cyprus. 2015. [16% acceptance rate] pdf
[C27] Jared Koontz*, Matthew Malensek*, and Sangmi Lee Pallickara. GeoLens: Enabling Interactive Visual Analytics over Large-scale, Multidimensional Geospatial Datasets. Proceedings of the IEEE/ACM Symposium on Big Data Computing. London, UK. 2014. [22% acceptance rate] ** Best Paper Award pdf
[C26] Matthew Malensek*, Walid Budgaga*, Sangmi Lee Pallickara, Neil Harvey and Shrideep Pallickara, Using Distributed Analytics to Enable Real-Time Exploration of Discrete Event Simulations. Proceedings of the IEEE/ACM International Conference on Utility and Cloud Computing. pp. 49-58, London, UK. 2014. [19% acceptance rate] pdf
[C25] Cameron Tolooee*, Matthew Malensek*, and Sangmi Lee Pallickara. A Framework for Managing Continuous Query Evaluations over Voluminous, Multidimensional Datasets. Proceedings of the IEEE Cloud and Autonomic Computing Conference. London, UK. 2014 pdf
[C24] Matthew Malensek*, Sangmi Lee Pallickara and Shrideep Pallickara. Polygon-Based Query Evaluation over Geospatial Data Using Distributed Hash Tables. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing, Dresden, Germany. 2013. [24% acceptance rate] pdf
[C23] Matthew Malensek*, Sangmi Lee Pallickara and Shrideep Pallickara. “Autonomously Improving Query Evaluations over Multidimensional Data in Distributed Hash Tables.” Proceedings of the ACM Cloud and Autonomic Computing Conference. Miami, USA. 2013. [35% acceptance rate] pdf
[C22] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. Expressive Query Support for Multidimensional Data in Distributed Hash Tables. Proceedings of the IEEE/ACM Conference on Utility and Cloud Computing. Chicago, USA. 2012. [27% acceptance rate] ** Best Paper Award pdf
[C21] Matthew Malensek*, Sangmi Lee Pallickara, and Shrideep Pallickara. “Galileo: A Framework for Distributed Storage of High-Throughput Data Streams,” Proceedings of the IEEE/ACM Conference On Utility and Cloud Computing. Melbourne, Australia. 2011. [26.7% acceptance rate] pdf
[C20] Sangmi Lee Pallickara, Matthew Malensek* and Shrideep Pallickara. “Enabling Access to Time- Series, Geospatial Data for On Demand Visualization,” Proceedings of the IEEE Symposium on Large-Scale Data Analysis and Visualization, Providence, Rhode Island. 2011. pdf
[C19] Sangmi Lee Pallickara, Shrideep Pallickara, Milija Zupanski, and Stephen Sullivan, “Efficient Metadata Generation to Enable Interactive Data Discovery over Large-scale Scientific Data Collections,” Proceedings of the IEEE International Conference on Cloud Computing Technology and Science, Indianapolis. November 2010. [24.9% acceptance rate] pdf
[C18] Sangmi Lee Pallickara, Marlon Pierce, Chin Hua Kong, and Qunfeng Dong, “Enabling Large Scale Scientific Computations for Expressed Sequence Tag Sequencing over Grid and Cloud Computing Clusters,” Proceedings of the PPAM 2009 Eighth International Conference on Parallel Processing and Applied Mathematics, Wroclaw, Portland. September 13-16, 2009. pdf
[C17] Sangmi Lee Pallickara and Marlon Pierce, “SWARM: Scheduling Large-scale Jobs over the Loosely-Coupled HPC Clusters,” Proceedings of the IEEE International Conference on e-Science. Indianapolis, USA. December 2008. [29.1% acceptance rate] pdf
[C16] Marlon Pierce, Sangmi Lee Pallickara, Yu Ma, Mike Lowe, Qunfeng Dong and Samy Meroueh, “Indiana University TeraGrid Gateway Support,” Proceedings of The International Conference for High Performance Computing, Networking, Storage and Analysis (collocated with SuperComputing ’08). November 2008.  
[C15] Yogesh Simmhan, Sangmi Lee Pallickara, Nithya N. Vijayakumar, and Beth Plale, “Data Management in Dynamic Environment Driven Computational Science,” Proceedings of The IFIP International Federation for Information Processing, Vol. 239, Grid-Based Problem Solving Environments, P.W. Gaffney and J.C.T. Pool. Eds. Spring Boston. pp.317-333, 2007 pdf
[C14] Sangmi Lee Pallickara, Beth Plale, Liang Fang, Dennis Gannon, “End-to-End Trustworthy Data Access in Data-Oriented Scientific Computing,” Proceedings of The IEEE Cluster Computing and Grid (CCGRID) 2006: 395-400. [23.7% acceptance rate] pdf
[C13] Yiming Sun, Scott Jensen, Sangmi Lee Pallickara, and Beth Plale, “Personal Workspace for Large-scale Data-driven Computational Experimentation,” Proceedings of the 7th IEEE/ACM International Conference on Grid Computing (Grid'06), Barcelona. 2006. [20.2% acceptance rate] pdf
[C12] Dennis Gannon, Beth Plale, Marcus Christie, Liang Fang, Yi Huang, Scott Jensen, Gopi Kandaswamy, Suresh Marru, Sangmi Lee Pallickara, Satoshi Shirasuna, Yogesh Simmhan, Alex Slominski, and Yiming. Sun, “Service Oriented Architectures for Science Gateways on Grid Systems,” Proceedings of The International Conference on Service Oriented Computing 2005, B. Benatallah, F. Casati, P. Traverso (Eds.), LNCS 3826, pp. 21-32, 2005. Springer-Verlag Berlin Heidelberg 2005. pdf
[C11] Sangmi Lee Pallickara, Beth Plale, Scott Jensen, Yiming Sun, Short Paper: “Monitoring Access to Stateful Resources in Grid Environments,” Proceedings of the IEEE International Conference on Services Computing, Orlando, Florida, pp. 343-346. 2005. pdf
[C10] Shrideep Pallickara, Geoffrey Fox, Beytullah Yildiz, Sangmi Lee Pallickara, Sima Patel and Damodar Yemme, “On the Costs for Reliable Messaging in Web/Grid Service Environments,” Proceedings of the IEEE International Conference on e-Science & Grid Computing, Melbourne, Australia. 2005. [31.6% acceptance rate] pdf
[C9] Shrideep Pallickara, Geoffrey Fox, and Sangmi Lee Pallickara, “An Analysis of Reliable Delivery Specifications for Web Services,” Proceedings of the IEEE ITCC Conference on Information Technology. Las Vegas. 2005. pdf
[C8] Sangmi Lee and Geoffrey Fox, “Wireless Reliable Messaging Protocol for Web Services (WS - WRM),” Proceedings of the IEEE 2nd International Conference on Web Services (ICWS 2004), pp.350-357, San Diego. 2004. [28.7% acceptance rate] pdf
[C7] Geoffrey Fox, Sunghoon Ko, Kangseok Kim, Sangmi Lee, Sangyoon Oh, “Universally Accessible Collaboration Frameworks for Ubiquitous Computing Environments,” Proceedings of the International Conference on Ubiquitous Computing (ICUC2003), Seoul Korea, 2003. pdf
[C6] Sangmi Lee, Sunghoon Ko, Geoffrey Fox, “Adapting Content for Mobile Devices in Heterogeneous Collaboration Environments,” Proceedings of the International Conference on Wireless Networks(ICWN '03), 00. 211-217, 2003. pdf
[C5] Geoffrey Fox, Hasan Bulut, Kangseok Kim, Sung-Hoon Ko, Sangmi Lee, Sangyoon Oh, Shrideep Pallickara, Xiaohong Qiu, Ahmet Uyar, Minjun Wang, Wenjun Wu “Collaborative Web Services and Peer-to-Peer Grids,” Proceedings of the IEEE Collaborative Technologies Symposium (CTS'03), 2003. pdf
[C4] Sangmi Lee, Sunghoon Ko, Geoffrey Fox, Kangseok Kim, Sangyoon Oh, “A Web Service Approach to Universal Accessibility in Collaboration Services,” Proceedings of the International Conference on Web Services (ICWS’03), pp. 333-339, USA. 2003. [29.8% acceptance rate] pdf
[C3] Geoffrey Fox, Sung-Hoon Ko, Kangseok Kim, Sangyoon Oh, Sangmi Lee, “Integration of Hand- Held Devices into Collaborative Environments,” Proceedings of the International Conference on Internet Computing (IC'02) pp.231-250, 2002. USA. pdf
[C2] Sangmi Lee, Geoffrey Fox , Sunghoon Ko, Minjun Wang, Xiaohong Qiu ,”Ubiquitous Access for Collaborative Information System Using SVG,” Proceedings of the SVG OPEN Conference. 2002, Zurich, Switzerland. pdf
[C1] Hasan Bulut, Geoffrey Fox, Dennis Gannon, Kangseok Kim, Sung-Hoon Ko, Sangmi Lee, Sangyoon Oh, Xi Rao, Shrideep Pallickara, Quinlin Pei, Marlon Pierce, Aleksander Slominski, Ahmet Uyar, Wenjun Wu, Choonhan Youn, “An Architecture for e-Science and its Implications,” Proceedings of the IEEE International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS 2002) July 2002. pdf