Thomas Delaney, Ph.D.

東京大学国際高等研究所ニューロインテリジェンス国際研究機構 特任研究員
Email: thomasjdelaney [AT]

My research interests lie in the use of deep learning to model perception in humans, especially visual perception. Specifically, I am interested in using these models to investigate potential underlying causes for ASD symptoms. I am currently using deep convolutional neural networks to asses the effect of imbalances in excitation and inhibition on visual perception. I also plan to use this Hallucination Machine to manifest the effects of these imbalances in a virtual reality environment.
During my PhD, my research was based around modelling the responses of large populations of neurons. I implemented the ‘Spectral Rejection’ method to detect functional communities in correlation based networks of neurons. I also invented a novel method for modelling the number of active neurons in a population that also captures the association between the neurons in that population. Finally, I created a biophysical model for the fluorescence trace produced by the soma of a neuron containing a fluorescent calcium indicator.



2020年9月−現在 東京大学国際高等研究所ニューロインテリジェンス国際研究機構 特任研究員
2018年 Reseach Intern, CheckRisk Plc.
2015年−2016年 Data Engineer, Edinburgh Airport Plc.
2011年−2014年 Consultant Software Engineer, First Derivatives Plc.


2020年 Ph.D. in Computer Science, University of Bristol
2015年 MSc in Informatics, University of Edinburgh
2011年 BA in Mathematics, Trinity College Dublin


  • University of Edinburgh Informatics UK/EU Master’s Scholarship (2014/2015)
  • University of Bristol studentship, funded by EPSRC
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