Dimitri Perrin

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Building upon a modelling framework introduced and validated for the investigation of the immune response to HIV infection using network-constrained intelligent agents, this project focuses on the application of advanced computational techniques to two specific biomedical systems, respectively considering (i) mechanisms of gene expression, and (ii) the evaluation of possible intervention policies to control disease progression within a large human population.

Large-scale agent-based and network-based aspects are hybridised and advanced models are developed for both systems and use cutting-edge parallel computing facilities.

For both systems, physical experiments are technically difficult, frequently pose ethical issues, and are limited by time and cost constraints. Computer-based models therefore offer a unique complement and alternative, as well as a means to integrate and analyse the results of partial experiments.

The proposed framework has very strong translational aspects and, in addition to the two systems above, will also be applied to several other biomedical or sociomedical systems.

This position is funded by an IRCSET-Marie Curie International Mobility Fellowship in Science, Engineering and Technology.

Development of large-scale multi-approach computational models for complex systems, with a particular focus on biomedical and social ones.
These include, but are not limited to, epidemic outbreaks in densely populated areas, epigenetic regulation of gene expression, advanced formalisms for the prisoner's dilemma, etc.

The principal aim of this study was to try to understand why the range of experience with respect to HIV infection is so diverse. Hence, why does one individual experience a long latency period (or relatively low success of antipathetic mutation) compared to another. To investigate these questions an agent-based approach was used.
Integration of additional model layers was also considered.

Development of the local model (lymph node), as a first step for the PhD study.

The aim of the study was to model the flow around the top of a typical meteorological tower and to investigate the relationship between the speed-up at the top of the tower and the free-stream wind-speed. We used the computational fluid dynamics commercial code FLUENT, consisting of the FLUENT solver and the GAMBIT meshing tool. Our simulations account for hollow towers and towers situated on slopes.
This study was a collaboration between Airtricity, DCU and INCA funded by SEI. Some results were presented at DEWEK and EWEC, and the complete study was published in Applied Energy.