Research interests are an evolving topic. I currently say that my main interests are:
- making mathematical models, particularly of biological systems, and even more particularly of systems which tend to learn or adapt their behaviour over time
- high performance numerical computing
- statistics
I particularly like bottom-up model design, in order to make predictions about system behaviour; as opposed to top-down, explanatory-based approaches which typically use arguments of optimality. And if I can combine a mathematical prediction, especially from the field of stochastic processes, with a highly complex numerical simulation I am particularly happy.
Thoughts on academia
I have followed a deliberately difficult path through academia, not because I love difficulty but perhaps because I mistrust the easy answer. Society and academia have changed multiple times in my life to-date and, as somebody aware of that perspective and perhaps more secure than most in my own abilities, I think it's my responsibility not to take the shortcuts when I fundamentally disagree with them. I have also enjoyed challenging myself to see how far I can get without giving in to the temptations of (i) producing a facile answer or (ii) working on a project which does not interest me. This has led me to combining research topics, already considered independently difficult, together and working on projects which I consider important rather than because they are easy. Of course, this approach is fraught with difficulties and probably leads to lower productivity when compared with alternative career paths.
Academic careers today are blighted by issues of fraud, misbehaviour and inequalities in the system. I have actively aided the development of platforms for a more open science, such as PubPeer, and I consider it my responsibility to respect the privileged position society has given me, to maintain principles of good behaviour rather than giving in to a race to the bottom in terms of false productivity, ethics and accuracy. I would rather work in another field than either produce multiple papers repeating the same discovery, or publish work which I do not believe in.
My main research jobs to date
Postdoc with Henning Sprekeler at TU Berlin - How bias in trifactor rules of synaptic plasticity can lead to failure to learn in a reward learning paradigm.
PhD student with Nicolas Brunel and Boris Barbour at the Ecole Normale Superieure, Paris - A Theoretical and Numerical Study
of Certain Dynamical Models of Synaptic Plasticity (thesis online).
Research Assistant at Institut für Neuro- und Bioinformatik, University of Lübeck - Modelling of thalamacortical learning processes during sleep
Research Assistant in Science Faculty Office at NUI, Galway - Statistics/Survey Data Analysis
Research Assistant in Graduate Studies Office at NUI, Galway - Statistics/Survey Data Analysis
M.Sc. - Mobility measures for credit-risk transition matrices
Research Assistant in Machine Learning group at NUI, Galway - One-sided classification
B.Sc. project - Software for calculating blood lactate endurance markers
Other interests: Complexity theory, genetic algorithms, emergence, complex adaptive systems, mathematical modelling, artificial intelligence, (computational) linguistics, the semantic web.
Suggested Reading
The Mathematics of Behavior by Earl Hunt, Life Itself by Robert Rosen, The Organic Codes by Marcello Barbieri, Emergence by John Holland, Consciousness by Gerald Edelman and Giulio Tononi, The Synaptic Organization of the Brain by Gordon M Shepherd, Laws of Form by G. Spencer-Brown, Complexity by Mitchell Waldrup, AI: A Modern Approach by Russell and Norvig, Travels in Hyperreality by Umberto Eco and What Has Government Done to Our Money? by Murray N. Rothbard.