Shane Culpepper
Adjunct Professor
Details
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College: STEM College
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Department: STEM College
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Campus: City Campus Australia
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shane.culpepper@rmit.edu.au
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ORCID: 0000-0002-1902-9087
Open to
- Masters Research or PhD student supervision
About
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.
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.
Supervisor projects
- New Perspectives on Query Performance Prediction
- 13 Sep 2019
- Inferential Risk Measures in Information Retrieval
- 1 Mar 2018
- Generating Natural Language Queries for More Effective Ranking
- 1 Mar 2018
- Efficient Cascade Ranking for Information Retrieval
- 1 Mar 2017
- Managing Tail Latency in Large Scale Information Retrieval Systems
- 22 Feb 2016
- Topic Difficulty and Order of Document Presentation in Relevance Assessments
- 27 Feb 2015
- Efficient and Effective Retrieval Using Higher-Order Proximity Models
- 21 Jul 2014
- Efficient query processing on spatial and textual data: beyond individual queries
- 3 Mar 2014
Teaching interests
Space-efficient data structures, data compression and coding, data streams, bioinformatics, information storage and retrieval, natural language processing, statistical machine learning, and combinatorics on words.
Research interests
Library and Information Studies, Information Systems, Data Format, Artificial Intelligence and Image Processing, Computation Theory and Mathematics, Computer Software
