Study level

  • Honours

Faculty/School

Faculty of Science

School of Information Systems

Topic status

We're looking for students to study this topic.

Research centre

Supervisors

Dr Adam Burke
Position
Research Fellow
Division / Faculty
Faculty of Science
Professor Moe Thandar Wynn
Position
Professor
Division / Faculty
Faculty of Science

Overview

In process mining, sequence analysis algorithms are used to discover computational models of process data, and to analyse them. The insights from these models and analysis then improve the processes in organisations in many real-life domains - from manufacturing, to government, to healthcare. Haskell is a powerful functional programming language well suited to problems involving formal reasoning and pattern matching. This project would advance process mining research by building high-quality, high performance libraries in Haskell for fundamental process mining activities such as parsing event logs and traversing Petri nets.

Research activities

  • Review existing research literature on process mining algorithms and tools.
  • Understand existing data formats and standards such as the XES format for event logs.
  • Develop and extend libraries in the Haskell programming language.
  • Work closely with researchers from the Process Science research group in Information Systems.

Outcomes

  • New releases of open source libraries for process mining.
  • Tools paper describing the work, as appropriate.

Skills and experience

  • Strong programming skills and algorithms and data structure knowledge essential.
  • Haskell experience not required.

Keywords

Contact

Contact the supervisor for more information.