
Overview
Background
Shane Culpepper is Professor of Artificial Intelligence at the University of Queensland in St. Lucia, Australia. Before joining the University of Queensland in 2023, Professor Culpeper held a continuing academic position at RMIT University in Melbourne, Australia. He received his PhD in Computer Science from the University of Melbourn in 2008. His research focuses primarily on building better Search and Recommendation Systems. Over his 16 year career, Professor Culpepper has supervised 19 PhD students and co-authored more than 120 peer reviewed papers with 127 different research collaborators on problems such as algorithm efficiency and scalability, new machine learning algorithms for search and recommendation systems, and evaluating search and recommendation engine quality. Professor Culpepper is also an active member in the international research community. In the last 5 years, he has been a program co-chair for international conferences such as SIGIR and CIKM, and co-organized conferences such as WSDM and SWIRL. Professor Culpepper previously held an ARC DECRA fellowship in 2013 as well as an RMIT Vice-Chancellor's Princpal Researcher fellowship in 2017. Before joining the University of Queensland. Professor Culpepper was the founding director of the Centre for Information Discovery and Data Analytics at RMIT University. In total, he has been a chief investigator on 11 reseach grants totalling ~$3.5 Million AUD. For more information, see his personal hoomepage.
Availability
- Professor Shane Culpepper is:
- Available for supervision
- Media expert
Fields of research
Qualifications
- Doctor of Philosophy of Computer Science, University of Melbourne
- Member, Association for Computing Machinery, Association for Computing Machinery
- Honorary Fellow, RMIT University, RMIT University
Works
Search Professor Shane Culpepper’s works on UQ eSpace
2021
Conference Publication
Do hard topics exist? A statistical analysis
Culpepper, J. Shane, Faggioli, Guglielmo, Ferro, Nicola and Kurland, Oren (2021). Do hard topics exist? A statistical analysis. IIR 2021: 11th Italian Information Retrieval Workshop 2021, Bari, Italy, 13-15 September 2021. Aachen, Germany: Rheinisch-Westfaelische Technische Hochschule Aachen.
2020
Conference Publication
CC-News-En : A large English news corpus
Mackenzie, Joel, Benham, Rodger, Petri, Matthias, Trippas, Johanne R., Culpepper, J. Shane and Moffat, Alistair (2020). CC-News-En : A large English news corpus. CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, Online, 19 - 23 October 2020. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3340531.3412762
2020
Conference Publication
Feature extraction for large-scale text collections
Gallagher, Luke, Mallia, Antonio, Culpepper, J. Shane, Suel, Torsten and Cambazoglu, B. Barla (2020). Feature extraction for large-scale text collections. 29th ACM International Conference on Information and Knowledge Management (CIKM), Virtual, 19-23 October 2020. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3340531.3412773
2020
Conference Publication
Cluster-based document retrieval with multiple queries
Bernstein, Kfir, Raiber, Fiana, Kurland, Oren and Shane Culpepper, J. (2020). Cluster-based document retrieval with multiple queries. ICTIR '20: The 2020 ACM SIGIR International Conference on the Theory of Information Retrieval, Virtual, 14-17 September 2020. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3409256.3409825
2020
Journal Article
Fewer topics? A million topics? Both?! On topics subsets in test collections
Roitero, Kevin, Culpepper, J. Shane, Sanderson, Mark, Scholer, Falk and Mizzaro, Stefano (2020). Fewer topics? A million topics? Both?! On topics subsets in test collections. Information Retrieval, 23 (1), 49-85. doi: 10.1007/s10791-019-09357-w
2020
Conference Publication
Spatial object recommendation with hints: when spatial granularity matters
Luo, Hui, Zhou, Jingbo, Bao, Zhifeng, Li, Shuangli, Culpepper, J. Shane, Ying, Haochao, Liu, Hao and Xiong, Hui (2020). Spatial object recommendation with hints: when spatial granularity matters. 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Virtual, 25-30 July 2020. New York, NY, United States: ACM. doi: 10.1145/3397271.3401090
2020
Conference Publication
Bayesian inferential risk evaluation on multiple IR systems
Benham, Rodger, Carterette, Ben, Culpepper, J. Shane and Moffat, Alistair (2020). Bayesian inferential risk evaluation on multiple IR systems. 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Virtual, 25-30 July 2020. New York, NY, United States: ACM. doi: 10.1145/3397271.3401033
2020
Conference Publication
Temporal network representation learning via historical neighborhoods aggregation
Huang, Shixun, Bao, Zhifeng, Li, Guoliang, Zhou, Yanghao and Culpepper, J. Shane (2020). Temporal network representation learning via historical neighborhoods aggregation. IEEE 36th International Conference on Data Engineering (ICDE), Dallas, TX, United States, 20-24 April 2020. Los Alamitos, CA, United States: IEEE Computer Society. doi: 10.1109/icde48307.2020.00101
2020
Book Chapter
On the Pluses and Minuses of Risk
Benham, Rodger, Moffat, Alistair and Culpepper, J. Shane (2020). On the Pluses and Minuses of Risk. Information Retrieval Technology. (pp. 81-93) Cham: Springer International Publishing. doi: 10.1007/978-3-030-42835-8_8
2019
Journal Article
Boosting search performance using query variations
Benham, Rodger, Mackenzie, Joel, Moffat, Alistair and Culpepper, J. Shane (2019). Boosting search performance using query variations. ACM Transactions On Information Systems, 37 (4) 41, 1-25. doi: 10.1145/3345001
2019
Conference Publication
A comparative analysis of human and automatic query variants
Liu, Binsheng, Craswell, Nick, Lu, Xiaolu, Kurland, Oren and Culpepper, J. Shane (2019). A comparative analysis of human and automatic query variants. ACM SIGIR 9th International Conference on the Theory of Information Retrieval (ICTIR), Santa Clara, CA USA, 2-5 October 2019. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3341981.3344223
2019
Conference Publication
Relevance modeling with multiple query variations
Lu, Xiaolu, Kurland, Oren, Culpepper, J. Shane, Craswell, Nick and Rom, Ofri (2019). Relevance modeling with multiple query variations. ACM SIGIR 9th International Conference on the Theory of Information Retrieval (ICTIR), Santa Clara, CA USA, 2-5 October 2019. New York, NY USA: Association for Computing Machinery. doi: 10.1145/3341981.3344224
2019
Journal Article
Fast Large-Scale Trajectory Clustering
Wang, Sheng, Bao, Zhifeng, Culpepper, J. Shane, Sellis, Timos and Qin, Xiaolin (2019). Fast Large-Scale Trajectory Clustering. Proceedings of the Vldb Endowment, 13 (1), 29-42. doi: 10.14778/3357377.3357380
2019
Conference Publication
Information needs, queries, and query performance prediction
Zendel, Oleg, Shtok, Anna, Raiber, Fiana, Kurland, Oren and Culpepper, J. Shane (2019). Information needs, queries, and query performance prediction. 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Paris, France, 21-25 July 2019. New York, NY, United States: ACM. doi: 10.1145/3331184.3331253
2019
Conference Publication
Accelerated query processing via similarity score prediction
Petri, Matthias, Moffat, Alistair, Mackenzie, Joel, Culpepper, J. Shane and Beck, Daniel (2019). Accelerated query processing via similarity score prediction. 42nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Paris, France, 21-25 July 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3331184.3331207
2019
Conference Publication
Compressing inverted indexes with recursive graph bisection: A reproducibility study
Mackenzie, Joel, Mallia, Antonio, Petri, Matthias, Culpepper, J. Shane and Suel, Torsten (2019). Compressing inverted indexes with recursive graph bisection: A reproducibility study. 41st European Conference on IR Research, ECIR 2019, Cologne, Germany, 14-18 April 2019. Heidelberg, Germany: Springer. doi: 10.1007/978-3-030-15712-8_22
2019
Journal Article
Top-k trajectories with the best view
Tripto, Nafis Irtiza, Nahar, Mahjabin, Ali, Mohammed Eunus, Choudhury, Farhana Murtaza, Culpepper, J. Shane and Sellis, Timos (2019). Top-k trajectories with the best view. Geoinformatica, 23 (4), 621-661. doi: 10.1007/s10707-019-00343-4
2019
Conference Publication
On topic difficulty in IR evaluation: the effect of systems, corpora, and system components
Zampieri, Fabio, Roitero, Kevin, Culpepper, J. Shane, Kurland, Oren and Mizzaro, Stefano (2019). On topic difficulty in IR evaluation: the effect of systems, corpora, and system components. 42nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Paris, France, 21-25 July 2019. New York, NY, United States: ACM. doi: 10.1145/3331184.3331279
2019
Conference Publication
Finding temporal influential users over evolving social networks
Huang, Shixun, Bao, Zhifeng, Culpepper, J. Shane and Zhang, Bang (2019). Finding temporal influential users over evolving social networks. IEEE 35th International Conference on Data Engineering (ICDE), Macau, China, 8 - 11 April 2019. Washington, DC, United States: I E E E Computer Society. doi: 10.1109/icde.2019.00043
2019
Conference Publication
Taking Risks with Confidence
Benham, Rodger, Carterette, Ben, Moffat, Alistair and Culpepper, J. Shane (2019). Taking Risks with Confidence. 24th Australasian Document Computing Symposium (ADCS), Sydney, NSW Australia, 5-6 December 2019. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3372124.3372125
Supervision
Availability
- Professor Shane Culpepper is:
- Available for supervision
Before you email them, read our advice on how to contact a supervisor.
Available projects
-
Large Language Models for Search and Recommendation
Large Language Models such as ChatGPT offer enormous promise to users completing everyday tasks. However, these models confidently provide misinformation which can be very convincing. This project aims to explore new techniques to improve the effectiveness of LLMs.
Supervision history
Current supervision
-
Master Philosophy
Search and Recommendation using Large Language Models
Principal Advisor
Other advisors: Dr Joel Mackenzie
-
Doctor Philosophy
Efficient Next-Generation Information Retrieval Systems
Associate Advisor
Other advisors: Dr Joel Mackenzie
Media
Enquiries
Contact Professor Shane Culpepper directly for media enquiries about:
- Generative AI
- Large Language Models
- Search and Recommendation
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