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Professor Shane Culpepper
Professor

Shane Culpepper

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Overview

Background

Shane Culpepper is a Professor of Artificial Intelligence at the University of Queensland in St. Lucia, Australia. Before joining the University of Queensland in 2023, Professor Culpepper held a continuing academic position at RMIT University in Melbourne, Australia. He received his PhD in Computer Science from the University of Melbourne in 2008. His research focuses primarily on building better Search and Recommendation Systems and is primarily interested how to responsibly integrate efficient and scalable generative AI models for search, recommendation, and question answering. Professor Culpepper’s work has applications in a number of downstream applications for Legal, Health, real estate speculation. He has been instrumental in founding the AI Research Network and the Research Center for Enterprise AI at the University of Queensland.

Over his 17 year career, Professor Culpepper has supervised 19 PhD students and co-authored more than 140 peer reviewed papers with 132 different research collaborators on problems that range from core basic research, such as algorithm efficiency and scalability, to practical real world problems on building and deploying new machine learning algorithms for search and recommendation systems. While often technical, his work is always user-driven as humans are the main consumers of this technology. This user-centric research focus has led to several papers on controlled user studies which guide the development of better evaluation techniques which model human behaviour. In the last 5 years, Professor Culpepper 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 Principal 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 research grants totalling ~$3.8 Million AUD.

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

121 works between 1995 and 2025

61 - 80 of 121 works

2018

Conference Publication

Towards efficient and effective query variant generation

Benham, Rodger, Culpepper, J. Shane, Gallagher, Luke, Lu, Xiaolu and Mackenzie, Joel (2018). Towards efficient and effective query variant generation. First Biennial Conference on Design of Experimental Search & Information Retrieval Systems (DESIRES 2018), Bertinoro, Italy, 28-31 August 2018. Aachen, Germany: RWTH Aachen University.

Towards efficient and effective query variant generation

2018

Conference Publication

Reverse k Nearest Neighbor Search over Trajectories (Extended Abstract)

Wang, Sheng, Bao, Zhifeng, Culpepper, J. Shane, Sellis, Timos and Cong, Gao (2018). Reverse k Nearest Neighbor Search over Trajectories (Extended Abstract). 34th IEEE International Conference on Data Engineering Workshops (ICDEW), Paris, France, 16-19 April 2018. Piscataway, NJ United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICDE.2018.00250

Reverse k Nearest Neighbor Search over Trajectories (Extended Abstract)

2018

Conference Publication

MaxBRkNN Queries for Streaming Geo-Data

Luo, Hui, Choudhury, Farhana M., Bao, Zhifeng, Culpepper, J. Shane and Zhang, Bang (2018). MaxBRkNN Queries for Streaming Geo-Data. 23rd International Conference on Database Systems for Advanced Applications (DASFAA), Gold Coast, QLD Australia, 21-24 May 2018. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-91452-7_42

MaxBRkNN Queries for Streaming Geo-Data

2017

Conference Publication

Early termination heuristics for score-at-a-time index traversal

Mackenzie, Joel, Scholer, Falk and Culpepper, J. Shane (2017). Early termination heuristics for score-at-a-time index traversal. ADCS 2017: The 22nd Australasian Document Computing Symposium, Brisbane, QLD Australia, 7-8 December 2017. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3166072.3166073

Early termination heuristics for score-at-a-time index traversal

2017

Conference Publication

Risk-reward trade-offs in rank fusion

Benham, Rodger and Culpepper, J. Shane (2017). Risk-reward trade-offs in rank fusion. 22nd Australasian Document Computing Symposium, ADCS 2017, Brisbane, QLD Australia, 7 - 8 December 2017. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3166072.3166084

Risk-reward trade-offs in rank fusion

2017

Journal Article

Geo-Social Influence Spanning Maximization

Li, Jianxin, Sellis, Timos, Culpepper, J. Shane, He, Zhenying, Liu, Chengfei and Wang, Junhu (2017). Geo-Social Influence Spanning Maximization. IEEE Transactions On Knowledge and Data Engineering, 29 (8) 7890988, 1653-1666. doi: 10.1109/TKDE.2017.2690288

Geo-Social Influence Spanning Maximization

2017

Journal Article

Efficient distributed selective search

Kim, Yubin, Callan, Jamie, Culpepper, J. Shane and Moffat, Alistair (2017). Efficient distributed selective search. Information Retrieval Journal, 20 (3), 221-252. doi: 10.1007/s10791-016-9290-6

Efficient distributed selective search

2017

Conference Publication

Personalized influential topic search via social network summarization

Li, Jianxin, Liu, Chengfei, Yu, Jeffrey Xu, Chen, Yi, Sellis, Timos and Culpepper, J. Shane (2017). Personalized influential topic search via social network summarization. 2017 IEEE 33rd International Conference on Data Engineering (ICDE), San Diego, CA, United States, 19-22 April 2017. Piscataway, NJ United States: IEEE. doi: 10.1109/icde.2017.15

Personalized influential topic search via social network summarization

2017

Conference Publication

Monitoring the top-m rank aggregation of spatial objects in streaming queries

Choudhury, Farhana M., Bao, Zhifeng, Culpepper, J. Shane and Sellis, Timos (2017). Monitoring the top-m rank aggregation of spatial objects in streaming queries. 2017 IEEE 33rd International Conference on Data Engineering (ICDE), San Diego, CA, United States, 19-22 April 2017. Piscataway, NJ United States: IEEE. doi: 10.1109/icde.2017.113

Monitoring the top-m rank aggregation of spatial objects in streaming queries

2017

Conference Publication

Answering top-k exemplar trajectory queries

Wang, Sheng, Bao, Zhifeng, Culpepper, J. Shane, Sellis, Timos, Sanderson, Mark and Qin, Xiaolin (2017). Answering top-k exemplar trajectory queries. 2017 IEEE 33rd International Conference on Data Engineering (ICDE), San Diego, CA, United States, 19-22 April 2017. Piscataway, NJ United States: IEEE. doi: 10.1109/icde.2017.114

Answering top-k exemplar trajectory queries

2017

Conference Publication

A comparison of document-at-a-time and score-at-a-time query evaluation

Crane, Matt, Culpepper, J. Shane, Lin, Jimmy, Mackenzie, Joel and Trotman, Andrew (2017). A comparison of document-at-a-time and score-at-a-time query evaluation. 10th ACM International Conference on Web Search and Data Mining (WSDM), Cambridge, United Kingdom, 6-10 February 2017. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3018661.3018726

A comparison of document-at-a-time and score-at-a-time query evaluation

2017

Conference Publication

Can Deep Effectiveness Metrics Be Evaluated Using Shallow Judgment Pools?

Lu, Xiaolu, Moffat, Alistair and Culpepper, J. Shane (2017). Can Deep Effectiveness Metrics Be Evaluated Using Shallow Judgment Pools?. 40th International ACM SIGIR conference on research and development in Information Retrieval, Shinjuku, Japan, 7-11 August 2017. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3077136.3080793

Can Deep Effectiveness Metrics Be Evaluated Using Shallow Judgment Pools?

2017

Conference Publication

Efficient Cost-Aware Cascade Ranking in Multi-Stage Retrieval

Chen, Ruey-Cheng, Gallagher, Luke, Blanco, Roi and Culpepper, J. Shane (2017). Efficient Cost-Aware Cascade Ranking in Multi-Stage Retrieval. 40th International ACM SIGIR conference on research and development in Information Retrieval, Shinjuku, Japan, 7-11 August 2017. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3077136.3080819

Efficient Cost-Aware Cascade Ranking in Multi-Stage Retrieval

2017

Conference Publication

Gauging the Quality of Relevance Assessments using Inter-Rater Agreement

Damessie, Tadele T., Nghiem, Thao P., Scholer, Falk and Culpepper, J. Shane (2017). Gauging the Quality of Relevance Assessments using Inter-Rater Agreement. 40th International ACM SIGIR conference on research and development in Information Retrieval, Shinjuku, Japan, 7-11 August 2017. New York, NY United States: Association for Computing Machinery. doi: 10.1145/3077136.3080729

Gauging the Quality of Relevance Assessments using Inter-Rater Agreement

2016

Conference Publication

Interactive trip planning using activity trajectories

Wang, Sheng, Bao, Zhifeng, Culpepper, J. Shane, Sellis, Timos, Sanderson, Mark and Yadamjav, Munkh-Erdene (2016). Interactive trip planning using activity trajectories. 21st Australasian Document Computing Symposium, ADCS 2016, Caulfield, VIC Australia, 6 - 7 December 2016. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3015022.3015030

Interactive trip planning using activity trajectories

2016

Conference Publication

Dynamic cutoff prediction in multi-stage retrieval systems

Culpepper, J. Shane, Clarke, Charles L. A. and Lin, Jimmy (2016). Dynamic cutoff prediction in multi-stage retrieval systems. 21st Australasian Document Computing Symposium, ADCS 2016, Caulfield, VIC Australia, 5 - 7 December 2016. New York, NY, United States: ACM. doi: 10.1145/3015022.3015026

Dynamic cutoff prediction in multi-stage retrieval systems

2016

Conference Publication

The influence of topic difficulty, relevance level, and document ordering on relevance judging

Damessie, Tadele T., Scholer, Falk and Culpepper, J. Shane (2016). The influence of topic difficulty, relevance level, and document ordering on relevance judging. ADCS '16: 21st Australasian Document Computing Symposium, Caulfield, VIC Australia, 5 - 7 December 2016. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/3015022.3015033

The influence of topic difficulty, relevance level, and document ordering on relevance judging

2016

Conference Publication

Modeling relevance as a function of retrieval rank

Lu, Xiaolu, Moffat, Alistair and Culpepper, J. Shane (2016). Modeling relevance as a function of retrieval rank. 12th Asia Information Retrieval Societies Conference, AIRS 2016, Beijing, China, 30 November - 2 December 2016. Cham, Switzerland: Springer International Publishing. doi: 10.1007/978-3-319-48051-0_1

Modeling relevance as a function of retrieval rank

2016

Conference Publication

Spatial textual top-k search in mobile peer-to-peer networks

Nghiem, Thao P., Ma, Cong, Culpepper, J. Shane and Sellis, Timos (2016). Spatial textual top-k search in mobile peer-to-peer networks. 27th Australasian Database Conference on Databases Theory and Applications, ADC 2016, Sydney, NSW Australia, 28-29 September 2016. Cham, Switzerland: Springer. doi: 10.1007/978-3-319-46922-5_6

Spatial textual top-k search in mobile peer-to-peer networks

2016

Conference Publication

Efficient and effective higher order proximity modeling

Lu, Xiaolu, Moffat, Alistair and Culpepper, J. Shane (2016). Efficient and effective higher order proximity modeling. 2016 ACM International Conference on the Theory of Information Retrieval, Newark, NJ United States, 12 - 16 September 2016. New York, NY, United States: Association for Computing Machinery. doi: 10.1145/2970398.2970404

Efficient and effective higher order proximity modeling

Funding

Current funding

  • 2024 - 2026
    Scaling Disk-Resident Learned Indexes for Database Systems
    ARC Discovery Projects
    Open grant
  • 2024 - 2026
    Scaling Disk-Resident Learned Indexes For Database Systems (ARC Discovery Project Administered by RMIT)
    Royal Melbourne Institute of Technology University
    Open grant
  • 2023 - 2025
    Advancing Analytical Query Processing with Urban Trajectory Data
    ARC Discovery Projects
    Open grant
  • 2023 - 2025
    Advancing Analytical Query Processing with Urban Trajectory Data (ARC Discovery Project Administered by RMIT)
    Royal Melbourne Institute of Technology University
    Open grant

Supervision

Availability

Professor Shane Culpepper is:
Available for supervision

Looking for a supervisor? Read our advice on how to choose 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

  • Doctor Philosophy

    Using Large Language Models and Knowledge Graphs to Improve Search and Recommendation

    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