Faculty/School

Faculty of Science

School of Information Systems

Topic status

We're looking for students to study this topic.

Research centre

Primary Supervisor

Dr Andrzej Janusz
Position
Lecturer in Information Systems
Division / Faculty
Faculty of Science

Other QUT supervisors

Dr Adam Burke
Position
Research Fellow
Division / Faculty
Faculty of Science

Overview

The advent of language-competent machine agents is already transforming many forms of work. Such agents can both be receivers of work, and the orchestrators of work, including work by human and machine agents. Furthermore, the work they do leaves digital traces that are a rich source of data for analysis and optimisation.

This project is a systematic, hands-on, experimental investigation into self-improving orchestras of intelligent agents using explicit, explainable process models. It investigates agents which organise work in process models within workflow engines, and improve the performance of that work through insights from process mining. There is potential to investigate both hands-off and centaur models of design and intervention in these automated environments.

Research engagement

Students will work with software agents, statistical and process models. Software laboratory environments will be used for experimental work.

Research activities

Students working on this project would contribute to literature review, data science analysis, and software research tools.

Research skills

Students will gain skills in agent-based work, data science, software development, and literature search

Outcomes

Tools, techniques, algorithms, and experimental results, leading to publication in high quality IS and CS venues.

Skills and experience

Data science, programming and business process management skills are all desirable.

Start date

2 November, 2026

End date

19 February, 2027

Location

Gardens Point

Additional information

Related Work

Calvanese, D., Casciani, A., De Giacomo, G., Dumas, M., Fournier, F., Kampik, T., La Malfa, E., Limonad, L., Marrella, A., Metzger, A., & others. (2026). Agentic business process management: A research manifesto. Information Systems, 140, 102738.

Vu, H., Körner, M., Rebmann, A., Kevorkian, G., Perscheid, M., Berg, G., & Kampik, T. (2026). Agent Behavior Mining: Generative AI Agent Governance in Business Processes. arXiv Preprint arXiv:2606.20669. Business Process Management.

Keywords

Contact

Adam Burke

+61 7 3138 1761

at.burke@qut.edu.au