STAFF PROFILE
Associate Professor Shane Culpepper
Position:
Principal Research Fellow
College / Portfolio:
School of Science Cluster
School / Department:
Computer Science and Information Tech
Phone:
99255224
Email:
shane.culpepper@rmit.edu.au
Campus:
Melbourne City Campus
Contact me about:
Research supervision
Associate Professor Shane Culpepper is the Director of the Centre for Information Discovery and Data Analytics and a Vice-Chancellor's Principal Research Fellow.
His current research focuses on building search systems to effectively and efficiently search massive data collections, and understanding how to measure the quality of the answers found. More broadly, he is interested in Human-driven Data Science and Analytics, which focuses on devising new approaches to transform heterogeneous data collections into knowledge. This might be accomplished through algorithms, data structures, machine learning, distributed computing, statistical modelling, or some combination of all the above. For further information, please visit the Centre Website or his personal homepage.Ph.D. University of Melbourne (2008)
- Roitero, K.,Culpepper, S.,Sanderson, M.,Scholer, F.,Mizzaro, S. (2020). Fewer topics? A million topics? Both?! On topics subsets in test collections In: Information Retrieval Journal, 23, 49 - 85
- Wang, S.,Bao, Z.,Culpepper, S.,Sellis, T.,Qin, X. (2020). (In Press) Fast Large-Scale Trajectory Clustering In: Proceedings of the VLDB Endowment, 13, 29 - 42
- Luo, H.,Bao, Z.,Choudhury, F.,Culpepper, S. (2020). (In Press) Dynamic Ridesharing in Peak Travel Periods In: IEEE Transactions on Knowledge and Data Engineering, , 1 - 14
- Huang, S.,Bao, Z.,Li, G.,Zhou, Y.,Culpepper, S. (2020). Temporal Network Representation Learning via Historical Neighborhoods Aggregation In: Proceedings of the IEEE 36th International Conference on Data Engineering (ICDE 2020), Dallas, United States, 20-24 April 2020
- Gallagher, L.,Blanco, R.,Chen, R.,Culpepper, J. (2019). Joint Optimization of Cascade Ranking Models In: Proceedings of the Twelfth ACM�International Conference on Web Search and Data Mining (WSDM 2019), Melbourne, Australia, 11-15 February 2019
- Zampieri, F.,Roitero, K.,Culpepper, J.,Kurland, O.,Mizzaro, S. (2019). On Topic Difficulty in IR Evaluation: The Effect of Systems, Corpora, and System Components In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), Paris, France, 21-25 July 2019
- Zendel, O.,Shtok, A.,Rabier, F.,Kurland, O.,Culpepper, J. (2019). Information Needs, Queries, and Query Performance Prediction In: Proceedings of the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, Paris, France, 21-25 July 2019
- Lu, X.,Kurland, O.,Culpepper, J.,Craswell, N.,Rom, O. (2019). Relevance Modeling with Multiple Query Variations In: Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR 2019), Santa Clara, United States, 2 - 5 October 2019
- Liu, B.,Craswell, N.,Lu, X.,Kurland, O.,Culpepper, J. (2019). A Comparative Analysis of Human and Automatic Query Variants In: Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR 2019), Santa Clara, United States, 2 - 5 October 2019
- Benham, R.,Mackenzie, J.,Moffat, A.,Culpepper, S. (2019). Boosting search performance using query variations In: ACM Transactions on Information Systems, 37, 1 - 25
Note: Supervision projects since 2004
7 PhD Current Supervisions8 PhD Completions
Information Retrieval, Algorithms and Data Structures, Machine Learning, Spatial Computing
- New approaches to interactive sessional search for complex tasks. Funded by: ARC Discovery Projects 2019 from (2019 to 2022)
- Efficient and Effective Cascaded Ranking for Large Scale Search. Funded by: The Amazon Research Awards (Gift / Donation) from (2019 to 2023)
- Archistar Innovation Connection Grant. Funded by: Archistar Pty Ltd Contract from (2019 to 2020)
- Optimising Efficiency and Effectiveness Trade-offs in Cascaded Learning-to-Rank. Funded by: Google Faculty Research Award 2016 onwards from (2019 to 2023)
- Trajectory Data Processing - Spatial Computing meets Information Retrieval - Administered by Swinburne University of Technology. Funded by: 010-ARC Discovery Projects 2017 from (2017 to 2019)