Our specific areas of research include data compression, text indexing, pattern search, and information discovery.
Growth in the quantity of publicly available digital information continues to outpace efficient storage and processing capacities of computer systems. These massive data sets present unique challenges for common algorithmic solutions and make computing statistics, finding interesting patterns, or answering queries difficult in many practical settings. Our group focuses on discovering algorithms and data structures of both theoretical and practical interest in modern data processing tasks.
Our specific areas of research include data compression, text indexing, pattern search, and information discovery. Many computational domains that are heavily reliant on processing massive data sets, such as bioinformatics, data streams, information retrieval, machine learning, data mining, data science and natural language processing, benefit from this line of research.
- Chris Hoobin
- Jasbir Dhaliwal
- Matthias Petri
- Gaya Jayasinghe