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J16 |
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
8.1
(February 2022),
pp. 213–228.
DOI: 10.1109/tbdata.2019.2939834
|
J15 |
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
2.3
(August 2021),
pp. 1–31.
DOI: 10.1145/3450767
|
J14 |
Naman Shah, Matthew Malensek, Harshil Shah, Shrideep Pallickara, and Sangmi Lee Pallickara.
Scalable Network Analytics for Characterization of Outbreak Influence in Voluminous Epidemiology Datasets.
Concurrency and Computation: Practice and Experience
31.7
(October 2019),
pp. e4998.
DOI: 10.1002/cpe.4998
|
J13 |
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
5.2
(June 2019),
pp. 252-265.
DOI: 10.1109/TBDATA.2018.2817505
|
J12 |
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
29.11
(Nov 2017),
pp. 2552-2566.
DOI: 10.1109/TKDE.2017.2734661
|
J11 |
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 and Experience
29.12
(Mar 2017),
DOI: 10.1002/cpe.4106
|
J10 |
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
4.2
(Mar 2017),
pp. 54–62.
DOI: 10.1109/MCC.2017.26
|
J9 |
Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara.
Fast, Ad Hoc Query Evaluations over Multidimensional Geospatial Datasets.
IEEE Transactions on Cloud Computing
5.1
(Jan 2017),
pp. 28–42.
DOI: 10.1109/TCC.2015.2398437
|
J8 |
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
28.6
(Jun 2016),
pp. 1408-1422.
DOI: 10.1109/TKDE.2016.2520475
|
J7 |
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
(Jun 2016),
pp. 2546–2563.
DOI: 10.1002/cpe.3651
|
J6 |
Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara.
Autonomous Cloud Federation for High-Throughput Queries over Voluminous Datasets.
IEEE Cloud Computing
3.3
(May 2016),
pp. 40–49.
DOI: 10.1109/MCC.2016.65
|
J5 |
Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara.
Minerva: Proactive Disk Scheduling for QoS in Multitier, Multitenant Cloud Environments.
IEEE Internet Computing
20.3
(May 2016),
pp. 19–27.
DOI: 10.1109/MIC.2016.48
|
J4 |
Walid Budgaga, Matthew Malensek, Sangmi Pallickara, Neil Harvey, F. 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
56.C
(Mar 2016),
pp. 360–374.
DOI: 10.1016/j.future.2015.06.013
|
J3 |
Zhiquan Sui, Matthew Malensek, Neil Harvey, and Shrideep Pallickara.
Autonomous Orchestration of Distributed Discrete Event Simulations in the Presence of Resource Uncertainty.
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
10.3
(Sep 2015),
pp. 18:1–18:20.
DOI: 10.1145/2746345
|
J2 |
Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara.
Evaluating Geospatial Geometry and Proximity Queries Using Distributed Hash Tables.
IEEE Computing in Science Engineering (CiSE)
16.4
(Jul 2014),
pp. 53-61.
DOI: 10.1109/MCSE.2014.48
|
J1 |
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
29.4
(Jun 2013),
pp. 1049–1061.
DOI: 10.1016/j.future.2012.05.024
|
C15 |
Sami N. Rollins, Alark Joshi, Xornam Apedoe, Sophie Engle, Matthew Malensek, and Gian Bruno.
Understanding Professional Identity Development Among Computer Science Students.
2021 ASEE Virtual Annual Conference Content Access.
Virtual Conference,
July
2021,
|
C14 |
Walid Budgaga, Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara.
Concerto: Leveraging Ensembles for Timely, Accurate Model Training Over Voluminous Datasets.
2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT).
2020,
pp. 106-115.
DOI: 10.1109/BDCAT50828.2020.00024
|
C13 |
Mingxin Lu, Edmund Wong, Daniel Barajas, Xiaochen Li, Mosopefoluwa Ogundipe, Nate Wilson, Pragya Garg, Alark Joshi, and Matthew Malensek.
AGAMI: Scalable Visual Analytics over Multidimensional Data Streams.
2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT).
2020,
pp. 57-66.
DOI: 10.1109/BDCAT50828.2020.00020
|
C12 |
Alark Joshi, Gian Bruno, Xornam Apedoe, Sophie Engle, Sami Rollins, and Matthew Malensek.
Engendering Community to Computer Science Freshmen through an Early Arrival Program.
2020 ASEE Virtual Annual Conference Content Access.
Virtual On line ,
June
2020,
DOI: 10.18260/1-2--34545
|
C11 |
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.
Proceedings of the 2016 IEEE International Conference on Big Data.
Washington, D.C., USA,
Dec
2016,
pp. 1222–1231.
DOI: 10.1109/BigData.2016.7840726
18.68% Acceptance Rate.
|
C10 |
Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara.
Alleviation of Disk I/O Contention in Virtualized Settings for Data-Intensive Computing.
Proceedings of the 2015 IEEE/ACM 2nd International Symposium on Big Data Computing (BDC).
Limassol, Cyprus,
Dec
2015,
pp. 1-10.
DOI: 10.1109/BDC.2015.32
16% Acceptance Rate.
|
C9 |
Jared Koontz, Matthew Malensek, and Sangmi Lee Pallickara.
GeoLens: Enabling Interactive Visual Analytics over Large-Scale, Multidimensional Geospatial Datasets.
Proceedings of the 2014 IEEE/ACM International Symposium on Big Data Computing (BDC).
London, UK,
Dec
2014,
pp. 35-44.
DOI: 10.1109/BDC.2014.12
22% Acceptance Rate.
Best Paper Award.
|
C8 |
Matthew Malensek, Walid Budgaga, Sangmi Pallickara, Neil Harvey, F. Jay Breidt, and Shrideep Pallickara.
Using Distributed Analytics to Enable Real-Time Exploration of Discrete Event Simulations.
Proceedings of the 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing.
London, UK,
Dec
2014,
pp. 49–58.
DOI: 10.1109/UCC.2014.13
19% Acceptance Rate.
|
C7 |
Cameron Tolooee, Matthew Malensek, and Sangmi Lee Pallickara.
A Framework for Managing Continuous Query Evaluations over Voluminous, Multidimensional Datasets.
Proceedings of the 2014 IEEE International Cloud and Autonomic Computing Conference (ICCAC).
London, UK,
Sep
2014,
pp. 73-82.
DOI: 10.1109/ICCAC.2014.25
|
C6 |
Matthew Malensek, Sangmi Pallickara, and Shrideep Pallickara.
Polygon-Based Query Evaluation over Geospatial Data Using Distributed Hash Tables.
Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing (UCC).
Dresden, Germany,
Dec
2013,
pp. 219–226.
DOI: 10.1109/UCC.2013.46
24% Acceptance Rate.
|
C5 |
Matthew Malensek, Sangmi Pallickara, and Shrideep Pallickara.
Autonomously Improving Query Evaluations over Multidimensional Data in Distributed Hash Tables.
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference (CAC).
Miami, Florida, USA,
Sep
2013,
pp. 15:1–15:10.
DOI: 10.1145/2494621.2494638
35% Acceptance Rate.
|
C4 |
Matthew Malensek, Zhiquan Sui, Neil Harvey, and Shrideep Pallickara.
Autonomous, Failure-resilient Orchestration of Distributed Discrete Event Simulations.
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference (CAC).
Miami, Florida, USA,
Sep
2013,
pp. 3:1–3:10.
DOI: 10.1145/2494621.2494625
35% Acceptance Rate.
|
C3 |
Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara.
Expressive Query Support for Multidimensional Data in Distributed Hash Tables.
Proceedings of the 2012 IEEE/ACM 5th International Conference on Utility and Cloud Computing (UCC).
Chicago, Illinois, USA,
Nov
2012,
pp. 31–38.
DOI: 10.1109/UCC.2012.41
27% Acceptance Rate.
Best Paper Award.
|
C2 |
Matthew Malensek, Sangmi Lee Pallickara, and Shrideep Pallickara.
Galileo: A Framework for Distributed Storage of High-Throughput Data Streams.
Proceedings of the 2011 IEEE/ACM 4th International Conference on Utility and Cloud Computing (UCC).
Melbourne, Australia,
Dec
2011,
pp. 17-24.
DOI: 10.1109/UCC.2011.13
26.7% Acceptance Rate.
|
C1 |
Sangmi Lee Pallickara, Matthew Malensek, and Shrideep Pallickara.
Enabling access to timeseries, geospatial data for on-demand visualization.
IEEE Symposium on Large Data Analysis and Visualization, (LDAV).
Providence, Rhode Island, USA,
Oct
2011,
pp. 141–142.
DOI: 10.1109/LDAV.2011.6092339
|