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] ircn.jp

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.

経歴

職歴

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.

学歴

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

受賞歴

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