Hello! I am a researcher and PhD student working in (artificial) intelligence. My principal interests lie in bridging the gap between the performance of current deep learning systems and the abilities and behaviours shown by biological systems, in particular in improving the ability to learn continually and rapidly from small amounts of data. I am also interested in how information available at the unit/neuron level can be used to understand how rapid learning emerges and how to endow artificial neural networks with such behaviours.
I am currently in the final year of my PhD in CGVU at the University of Edinburgh where I am supervised by Dr. Taku Komura. During my studies I first developed methods in deep learning applications with a focus on data efficient modelling of style and content in 3D humanoid animation data, that is rapidly adapting to new domains in time-series data. More recently I have focussed on more general rapid adaptation methods in neural networks and the direct initial study of how unit level information may be used to facilitate this. Prior to this I completed an MSc in AI an the University of Edinburgh and a BSc in Mathematics at Imperial College London.
You can contact me at any of the social links on the sidebar or email me at ianxmasonsite at gmail dot com.