I am a member of the Enterprise Systems group, which specialises in software engineering, model driven engineering, open source, and large-scale enterprise systems.
Topics that I am specifically interested in are:
I am also interested in applications for doctoral study in aspects of model driven engineering for non-OO models (state charts, Petri nets, activity diagrams, etc.) and for process-oriented target languages. In addition, the wider software engineering of complex simulations is of interest, including testing, fitness-for-purpose, reuse and maintenance of complex simulations.
Applicants who do not have their own funding should consider the open positions in Computer Science: https://www.cs.york.ac.uk/postgraduate/research-degrees/phd/#tab-3
In complex systems simulation, I developed an argumentation approach to record simulation rationale, and to establish the fitness for purpose (validation) of agent simulations for biological systems. I work with the York Computational Immunology Lab, and with the Maitland Cancer Research Lab , on collaborations between laboratory scientists and computer scientists. I aim to extend this work, and would consider supervision of collaborative simulation research using any modelling approach, and potentially in any area of complex systems research.
The York Computational Immunology Lab (YCIL) collaboration between Computer Science, Electronics, and Biology has had significant success in integrating domain modelling and computer simulation into biological lab research. PhD projects and postdocs produced case studies on important diseases such as Leishmaniasis, Inflammatory Bowel Disease, and immune tissue development, that exemplify the use of modelling and simulation to derive robust biological predictions. Impact: 20 high-impact journal articles since 2012; 3 simulation analysis and documentation tools with over 3000 downloads; significant research income (e.g. NC3Rs Crack-IT award) and industrial collaboration.
The proposed PhD will focus on software engineering practices needed to support and popularise robust modelling and simulation of the biological systems. The project will develop a model-driven engineering (MDE) approach that extends the current state of the art with novel contributions to the validation of model management operations and behaviour based MDE.
The YCIL approach to exploring complex emergent behaviours in biological systems requires the creation of dynamic simulations, programmed via the behaviour of a very large number of heterogeneous agents (e.g. cells or molecules). Our previous research resulted in a transparent and traceable standard for specification and validation of models of complex domains prior to simulation implementation. However, the behavioural models that we produce do not directly align to tool-supported software engineering, which generally uses models of system structure as its base. To date, our simulation code is not directly derived from the design diagrams, and the quality of simulators depends on highly-skilled programmers and extensive software testing. There is no direct means to ensure that code is kept consistent with model modifications. The simulators are developed and used by researchers across disciplines, so tool support for implementation and code validation is critical to the future use of simulation-derived prediction in the lab -- an approach that is also important in reducing animal experimentation. Well-founded software engineering support also facilitates reuse and extension of simulators.
This PhD will create and evaluate a MDE approach to biological simulation that can guarantee correct implementation of modelled system behaviours and simplify modification of simulators if models change to reflect new understanding or variant scenarios. In the rapidly-evolving biological context, such support for simulation is critical to further adoption of trustworthy research simulations. The PhD will contribute to MDE research, through MDE support for behaviour-based system modelling, novel contributions to validation of model management, and MDE for large software systems and high-performance computing.
Dr. Alden will support initial understanding of the approach and case studies. The tools developed by the PhD will be evaluated on other YCIL case studies, and will used to roll out the YCIL approach to other biology domains (e.g. York Cancer labs, with we already collaborate).
Publications relating to simulation can be found on the CoSMoS project website, http://www.cosmos-research.org/
Publications relating to YCIL simulation can be found on the YCIL website, https://www.york.ac.uk/computational-immunology/
A fairly complete list of my publications is available at http://www.cs.york.ac.uk/~fiona/PUBS/recent.html