Computational Modelling

You might have complex data — datasets and data modules with relationships that are not immediately apparent, but where finding such relationships could speed your workflow or reveal new insights. For example, you have gene expression data and you want to test whether any genes respond differently across environments. Or you want to go further and understand what is driving those changes. We can do that for you.

Alternatively, you understand some of the relationships in your data already. What you want to know is how your variable of interest — genes, network users, or any other component — will respond when you introduce a new variable. To answer that you need to understand the system at a deeper level, and we can help you achieve that insight.

A third scenario: you have developed a model or found a pattern, and now you want to automate and scale it. Say you develop a model that identifies patterns in gene expression data for one patient and makes predictions for new interventions. You then want to run that same pipeline across all patients. We can develop and automate those algorithms for you.

I have extensive experience modelling and deciphering complex systems over the past 20 years. I have analysed networked and embedded systems, gene regulatory networks in the developing brain, and the scaling of different neural network architectures. I have also studied the effects of noise and robustness mechanisms in the developing brain and neural circuits.

My background spans computer science and neuroscience. I have used information theory, computational modelling, and statistical methods to understand and model systems — and I bring that same rigour to your problem.

For the full picture of past projects and research, see our background page.