Discovering pathways from large databases

Research areas

Temporary Supervisor

Dr Huidong Jin


The term “pathway” is used in several different fields to denote a course taken by an entity or a person through a series of experiences. The time-span of a pathway may be a substantial portion of an individual’s life, or may be as short as a day or less. An operational definition of a pathway depends on the application context, which determines the types of experience that may comprise a pathway; for example, a pathway defining a course of medical treatment may exclude all or most nonmedical experiences, or defining a trace through a network of service nodes. So, a pathway is not merely a record of one person’s history, but defines histories that are likely to be shared among several, and perhaps many entities. Pathways are very useful for modelling and improve service delivery systems.


This project aims at implementing (or developing) efficient temporal data mining/machine learning techniques to discover useful pathways from large databases. The project may exploit or establish new techniques based on Bayesian networks, Markov chains, graph/tree mining, and interestingness measurement.


Applicants are expected to have a major in computer science, information technology, computer engineering, or applied mathematics/statistics; Preferably with excellent programming skills (C/C++, Java, R, and/or Python); Preferably with strong background in data mining, algorithm, or statistical machine learning.

Background Literature

Please have a look of data mining papers linked in the supervisor's staff page (following the links below). Further details please contact the supervisor Warren Jin [Warren.Jin(at)] directly. CSIRO (, as Australia’s national science agency is one of the largest and most diverse research agencies in the world. It operates large multi-disciplinary research teams. By doing a project with CSIRO you will have access to world class facilities and be able to work alongside CSIRO scientists while you are enjoying generous personal development and learning opportunities.


A student working in this project can expect

  • to learn state-of-art of data mining techniques;
  • to be involved in developing cutting-edge data mining techniques;
  • to gain experiences on solving real-world challenges while working with a research group delivering great science and innovative solutions for Australian society and economy.

Updated:  1 June 2019/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing