Dr Aaron Harwood

  • Room: Level: 07 Room: 7.18
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Parallel and Distributed Computing (Peer-to-Peer, GPU Computing)
  • Smart Mobile Systems (Streaming Data, Mobility Analysis)
  • Social Networking (Event Detection, Topic Tracking, Influence)

Personal webpage

http://people.eng.unimelb.edu.au/aharwood

Biography

Dr Aaron Harwood is a Senior Lecturer in the Department of Computer Science and Software Engineering at The University of Melbourne.

Recent publications

  1. Jayasekara, S.; Liu, X.; Karunasekera, S.; Harwood, A. Communication Model for Parallel Iterative Stream Processing. 2018 IEEE International Conference on Big Data (Big Data). IEEE. 2019, pp. 313-320. DOI: 10.1109/BigData.2018.8622312
  2. Truong, TM.; Harwood, A.; Sinnott, RO.; Chen, S. Cost-efficient stream processing on the cloud. 2019 IEEE 12th International Conference on Cloud Computing (CLOUD). IEEE. 2019, Vol. 2019-July, pp. 209-213. DOI: 10.1109/CLOUD.2019.00044
  3. Jayasekara, S.; Karunasekera, S.; Harwood, A. Enhancing the Scalability and Performance of Iterative Graph Algorithms on Apache Storm. 2018 IEEE International Conference on Big Data (Big Data). IEEE. 2019, pp. 3863-3872. DOI: 10.1109/BigData.2018.8622147
  4. Lim, KH.; Karunasekera, S.; Harwood, A.; George, Y. Geotagging tweets to landmarks using convolutional neural networks with text and posting time. Proceedings of the 24th International Conference on Intelligent User Interfaces. ACM Press. 2019, pp. 61-62. DOI: 10.1145/3308557.3308691
  5. Lim, KH.; Jayasekara, S.; Karunasekera, S.; Harwood, A.; Falzon, L.; Dunn, J.; Burgess, G. Rapid: Real-time analytics platform for interactive data mining. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer International Publishing. 2019, Vol. 11053 LNAI, pp. 649-653. DOI: 10.1007/978-3-030-10997-4_44
  6. Amarasinghe, G.; De Assuncao, MD.; Harwood, A.; Karunasekera, S. A data stream processing optimisation framework for edge computing applications. 2018 IEEE 21st International Symposium on Real-Time Distributed Computing (ISORC). IEEE. 2018, pp. 91-98. DOI: 10.1109/ISORC.2018.00020
  7. Mousavi, SM.; Harwood, A.; Karunasekera, S.; Maghrebi, M. Enhancing the quality of geometries of interest (GOIs) extracted from GPS trajectory data using spatio-temporal data aggregation and outlier detection. Journal of Ambient Intelligence and Humanized Computing. SPRINGER HEIDELBERG. 2018, Vol. 9, Issue 1, pp. 173-186. DOI: 10.1007/s12652-016-0426-8
  8. Mohan, LJ.; Caneleo, PIS.; Parampalli, U.; Harwood, A. Geo-aware erasure coding for high-performance erasure-coded storage clusters. Annals of Telecommunications. SPRINGER INTERNATIONAL PUBLISHING AG. 2018, Vol. 73, Issue 1-2, pp. 139-152. DOI: 10.1007/s12243-017-0623-2
  9. Bukhari, I.; Harwood, A.; Karunasekera, S. Handling churn in similarity based clustering overlays using weighted benefit. 2017 18th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT). IEEE. 2018, Vol. 2017-December, pp. 384-391. DOI: 10.1109/PDCAT.2017.00069
  10. Tri, MT.; Harwood, A.; Sinnott, RO.; Chen, S. Performance Analysis of Large-scale Distributed Stream Processing Systems on the Cloud. 2018 IEEE 11th International Conference on Cloud Computing (CLOUD). IEEE. 2018, Vol. 2018-July, pp. 754-761. DOI: 10.1109/CLOUD.2018.00103
  11. Karunaratne, P.; Moshtaghi, M.; Karunasekera, S.; Harwood, A. PSF+-Fast and improved electricity consumption prediction in campus environments. 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm). IEEE. 2018, Vol. 2018-January, pp. 241-246. DOI: 10.1109/SmartGridComm.2017.8340660
  12. Kannangara, S.; Tanin, E.; Harwood, A.; Karunasekera, S. Stepping stone graph for public movement analysis. Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - SIGSPATIAL '18. ACM Press. 2018, pp. 149-158. DOI: 10.1145/3274895.3274913
  13. Jayasekara, S.; Karunasekera, S.; Harwood, A. A Multi-stage Hierarchical Window Model with Application to Real-Time Graph Analysis. 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS). IEEE COMPUTER SOC. 2017, pp. 2561-2564. DOI: 10.1109/ICDCS.2017.225
  14. Lim, KH.; Karunasekera, S.; Harwood, A. ClusTop: A Clustering-based Topic Modelling Algorithm for Twitter using Word Networks. 2017 IEEE International Conference on Big Data (Big Data). IEEE. 2017, Vol. 2018-January, pp. 2009-2018. DOI: 10.1109/BigData.2017.8258147
  15. Karunaratne, P.; Karunasekera, S.; Harwood, A. Distributed stream clustering using micro-clusters on Apache Storm. Journal of Parallel and Distributed Computing. ACADEMIC PRESS INC ELSEVIER SCIENCE. 2017, Vol. 108, pp. 74-84. DOI: 10.1016/j.jpdc.2016.06.004
  16. Liu, X.; Harwood, A.; Karunasekera, S.; Rubinstein, B.; Buyya, R. E-Storm: Replication-based State Management in Distributed Stream Processing Systems. 2017 46th International Conference on Parallel Processing (ICPP). IEEE COMPUTER SOC. 2017, pp. 571-580. DOI: 10.1109/ICPP.2017.66
  17. Mousavi, SM.; Harwood, A.; Karunasekera, S.; Maghrebi, M. Geometry of interest (GOI): spatio-temporal destination extraction and partitioning in GPS trajectory data. Journal of Ambient Intelligence and Humanized Computing. SPRINGER HEIDELBERG. 2017, Vol. 8, Issue 3, pp. 419-434. DOI: 10.1007/s12652-016-0400-5
  18. Karunaratne, P.; Moshtaghi, M.; Karunasekera, S.; Harwood, A.; Cohn, T. Modelling the Working Week for Multi-Step Forecasting using Gaussian Process Regression. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence. 2017, pp. 1994-2000. DOI: 10.24963/ijcai.2017/277
  19. Karunaratne, P.; Moshtaghi, M.; Karunasekera, S.; Harwood, A.; Cohn, T. Multi-step Prediction with Missing Smart Sensor Data using Multi-task Gaussian Processes. 2017 IEEE International Conference on Big Data, BigData 2017, Boston, MA, USA, December 11-14, 2017. IEEE. 2017, Vol. 2018-January, pp. 1183-1192. DOI: 10.1109/BigData.2017.8258044
  20. Bukhari, IF.; Harwood, A.; Karunasekera, S. Optimum Benefit Protocol: A fast converging, bandwidth-efficient decentralized similarity overlay. Journal of Parallel and Distributed Computing. ACADEMIC PRESS INC ELSEVIER SCIENCE. 2017, Vol. 109, pp. 129-141. DOI: 10.1016/j.jpdc.2017.05.013

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile