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Professor Shane Culpepper
Professor

Shane Culpepper

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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

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

115 works between 1995 and 2024

21 - 40 of 115 works

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

CC-News-En : A large English news corpus

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

Feature extraction for large-scale text collections

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

Cluster-based document retrieval with multiple queries

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

Fewer topics? A million topics? Both?! On topics subsets in test collections

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

Temporal network representation learning via historical neighborhoods aggregation

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

On the Pluses and Minuses of Risk

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

Spatial object recommendation with hints: when spatial granularity matters

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

Bayesian inferential risk evaluation on multiple IR systems

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

Boosting search performance using query variations

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

A comparative analysis of human and automatic query variants

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

Relevance modeling with multiple query variations

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

Fast Large-Scale Trajectory Clustering

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

Information needs, queries, and query performance prediction

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

Accelerated query processing via similarity score prediction

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

Compressing inverted indexes with recursive graph bisection: A reproducibility study

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

Top-k trajectories with the best view

2019

Conference Publication

Joint optimization of cascade ranking models

Gallagher, Luke, Chen, Ruey-Cheng, Blanco, Roi and Culpepper, J. Shane (2019). Joint optimization of cascade ranking models. WSDM '19: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, Melbourne, VIC, Australia, 11 - 15 February 2019. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3289600.3290986

Joint optimization of cascade ranking models

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

On topic difficulty in IR evaluation: the effect of systems, corpora, and system components

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

Finding temporal influential users over evolving social networks

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

Taking Risks with Confidence

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

Need help?

For help with finding experts, story ideas and media enquiries, contact our Media team:

communications@uq.edu.au