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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

121 - 121 of 121 works

1995

Journal Article

Efficient Syntheses of the Marine Alkaloiss Makaluvamine D and Discorhabdnn C: The 4,6,7-Trimethoxyindole Approach

Sadanandan, Eyyani V., Pillai, Sasi K., Lakshmikantham, M. V., Billimoria, Adil D., Culpepper, J. Shane and Cava, Michael P. (1995). Efficient Syntheses of the Marine Alkaloiss Makaluvamine D and Discorhabdnn C: The 4,6,7-Trimethoxyindole Approach. Journal of Organic Chemistry, 60 (6), 1800-1805. doi: 10.1021/jo00111a043

Efficient Syntheses of the Marine Alkaloiss Makaluvamine D and Discorhabdnn C: The 4,6,7-Trimethoxyindole Approach

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