Students
Information for prospective PhD students can be found in the Study with me section below.
Current students
PhD
Process monitoring and conformance checking under uncertainty
Formal reasoning for data governance rules
Formal reasoning for process composition
2nd supervisor
Explainable AI in healthcare
2nd supervisor
Formalising and verifying voting methods
2nd supervisor
MSc
A Resource-based Checklist Generation Tool
A modern web interface for the WorkflowFM Composer
UG4 & MInf
Business process simulation
Prediction of time to find study space in the Main Library using Wi-Fi data
Workflow execution and management
Web development for business process simulation
Previous students
PhD
Machine learning for interactive theorem proving
2nd supervisor
MSc
Visualizing delays in a timeline of business processes
Generation of checklists from formal workflow models
A web framework for negotiating calendar preferences for meetings
Cultural preferences in meeting negotiation and arrangement
Process Analytics for the Training of Future Doctors
Analysis of Process Miners
Designing a Meeting Assistant Application Based on Microsoft Teams
Delay Analysis in Manufacturing Process
Business Process Modelling of Care Pathways for HIV Patients
2nd supervisor
An Interactive, Web-based Platform for Pulmonary Rehabilitation
2nd supervisor
An Interactive, Web-based Platform for Pulmonary Rehabilitation
2nd supervisor
Developing workflow-based guidelines for burns care in Scotland
A social machine for the Heart Manual Programme
2nd supervisor
A RESTful web service for the WorkflowFM composer
UG4 & MInf
Diagrammatic web-based Interface for process composition
2nd supervisor
Lemma recommendations for mechanical theorem proving
2nd supervisor
Interns
WorkflowFM - business process simulation
3 months
DigiFlow - full stack development
2 months
DigiFlow - dashboard development
2 months
DigiFlow - timeline development
2 months
Study with me
I am accepting PhD students in any of the areas and topics related to my research. Example topics are listed below.
Funding may be available for excellent candidates. Some funding information is provided in this link.
Feel free to contact me with any queries. If you do so, please provide the following information:
- Your background and any relevant previous work.
- The general area or topic of research on which you would like to do a PhD.
- A short abstract or a draft PhD proposal up to 2 pages long.
Workflow management meets the Internet of Things
- Combining workflow management with IoT data. Related challenges are described in a recent paper by Janiesch et al.
- IoT Data-driven insights for process monitoring, optimization and prediction.
- Integration of IoT data streams into different stages of the workflow lifecycle.
- Complex event processing using both symbolic and statistical AI techniques.
- Applications in health and social care, manufacturing, construction, business process, workforce and supply chain management.
Activities of Daily Living
- Process-based and AI modelling techniques for daily routines.
- Activity mapping under uncertainty.
- Detection of short and long term deviations.
- Links to health indicators such as frailty.
- Early detection of deterioration and predictive interventions.
Applied verification of concurrent and distributed systems
- Practical applications of recent developments involving session types, such as from the ABCD project, in the context of process modelling and distributed workflows.
- Exploitation of links between session types and linear logic for correct-by-construction workflow systems.
- Heterogeneous reasoning, e.g. involving dependent types, for the verification of resource flows in a concurrent system.
Process simulation
- Expressive and efficient operational digital twins.
- Seamless transition from workflow execution to simulation.
- Incorporating real data from the physical world, for instance from IoT sensors.
- AI for prioritization, optimization and applications in (project) scheduling.
Logic-based workflow modelling and management
Develop novel symbolic AI and data-driven techniques to innovate across the stages of the workflow lifecycle:
- Intuitive design
- Collaborative modelling
- Rigorous validation
- Automated deployment and distributed enactment
- Discrete event simulation
- Applications in health and social care, manufacturing, business process, workforce and supply chain management, and social machines.