The velocity of digital information being produced everyday
continues to outpace efficient storage and processing capacities.
The volume of data that must be manipulated presents unique challenges
in algorithm design, and makes efficiently computing statistics, finding
interesting patterns, or answering queries difficult in many practical
settings. Our group focuses on developing new models to help reason
about complex data representations, and discovering algorithms and
data structures of both theoretical and practical interest that are
capable of efficiently supporting modern data processing tasks.
We are also interested in understanding how to evaluate the quality
of results returned in a variety of search and data analytics scenarios,
and ensure that users' information needs are satisfied.
Our specific areas of focus include text indexing, data compression,
pattern search, system evaluation, and information discovery. Many
computational domains that are heavily reliant on the processing of
massive data sets, such as information retrieval, natural language
processing, machine learning, data mining, data science, bioinformatics,
and data streams benefit from this line of research.
Information Storage and Retrieval
Evaluating Search Quality
Machine-based Learning in Information Retrieval
Scalable Algorithm Design
String Processing and Indexing
Distributed and Parallel Computing
Stream Processing Algorithms
RMIT Vice-Chancellor's Senior Research Fellowship : J. S. Culpepper
2017H1 Mozilla Research Grant : J. S. Culpepper:
"Efficient and Effective Multi-Stage Retrieval in Rust."
2017 ($50,000 USD).
ARC Discovery Grant DP170102231: T. Sellis, J. S. Culpepper, C. L. A. Clarke,
and J. Lin:
"Trajectory Data Processing - Spatial Computing meets Information Retrieval."
ARC Discovery Early Career Research Award DE140100275: J. S. Culpepper:
"Beyond keyword search for ranked document retrieval."
2014-2016 ($392,979) + ($150,000 RMIT Support).
ARC Discovery Grant DP140101587: T. Sellis, J. S. Culpepper, N. Mamoulis,
and C. S. Jensen:
"Efficient and effective ad-hoc retrieval using structured and unstructured
2014-2016 ($422,000) + ($75,000 RMIT Support).
ARC Discovery Grant DP110101743: A. Moffat, A. Wirth, J. S. Culpepper,
and A. Turpin: "Efficient and effective algorithms for searching
strings in secondary storage." 2011-2013 ($360,000).
RMIT Seed Grant: J. S. Culpepper: "Novel ranking algorithms for unrestricted
text indexing." 2010 ($20,000).
Can be found here.