Tim Rumbell joined IBM research as a postdoctoral researcher in 2015.
His research involves biologically detailed neuron modeling at the single cell and neural tissue levels.
- Single cell modeling: multicompartmental models of single neurons
- Neural tissue modeling: integrating detailed single neuron models into simulation of brain regions
Tim graduated with a BSc in Cognitive Science from the University of Leeds, UK in 2005, followed by a MPhil in Artificial Intelligence from the University of Birmingham, UK in 2009.
He then went on to complete his PhD in Computational Neuroscience from Plymouth University, UK in 2013. This work explored how spiking neural networks utilising biologically plausible mechanisms such as spike-timing-dependent plasticity, phasic coding of information, and oscillatory activity could self organise to represent their input, recreating functional properties of the self-organising map.
Next, he undertook post-doctoral research at the Icahn School of Medicine at Mount Sinai in New York between 2013 and 2015, building single cell models of prefrontal cortical L2/3 pyramidal neurons from young and aged rhesus monkeys. Here he developed new methods for searching ion channel parameter space to facilitate tuning of models to target electrophysiological properties.
Since joining IBM in late 2015, he has been working to extend these single cell modeling techniques to develop a population based approach to simulating classes of cells, in particular dopaminergic neurons of the substantia nigra pars compacta, and to integrate multiple complex neuron models of the same class into brain tissue simulations.