Tom Diethe
search externally:   Google Scholar,   Springer,   CiteSeer,   Microsoft Academic Search,   Scirus ,   DBlife


Tom received his BSc in Experimental Psychology at the University of Bristol, during which he had year in industry as a Research Assistant at the Defence Evaluation and Research Agency (DERA). He was then employed as a Research Assistant at the University of Bristol between 2000 and 2001.

Between 2001 and 2006 he was employed by QinetiQ as a Senior Software Engineer in the Centre for Human Sciences. He was involved with the development of complex adaptive systems using principles from cognitive science, signal processing, and knowledge engineering. He achieved the QinetiQ Future Systems Technology (FST) division "Star Award" for outstanding achievement.

He then received an MSc in Intelligent Systems at UCL with Distinction. He completed his PhD in the field of Machine Learning applied to multivariate signal processing in the Department of Computer Science at UCL under the supervision of Prof. John Shawe-Taylor. This work included empirical evaluations on real world datasets, namely: the classification of musical genre from polyphonic audio files; a study of how the sampling rate in a digital radar can be reduced through the use of Compressed Sensing; analysis of human perception of different modulations of musical key from Electroencephalography (EEG) recordings; classification of genre of musical pieces to which a listener is attending from Magnetoencephelography (MEG) brain recordings. These applications demonstrated the efficacy of the framework and highlighted interesting directions of future research. From 2010 to 2011 he was employed as Research Manager for the Centre for Computational Statistics and Machine Learning (CSML) at University College London. His responsibilities included coordinating links with other groups across UCL with a view to establishing new collaborative research projects. During this he was involved in a successful bid for EU-FP7 funding worth €4.5M entitled "Composing Learning for Artificial Cognitive Systems" (CompLACS). He joined the Department of Statistical Science in February 2011 as a Postdoctoral Assistant to Prof. Mark Girolami.


flag Large Scale Model-Based Machine Learning
as author at  Large-scale Online Learning and Decision Making (LSOLDM) Workshop, Cumberland Lodge 2013,
flag Large-Scale Mining of Medical Text- a Hybrid Statistical/Semantic Approach
as author at  Large-scale Online Learning and Decision Making (LSOLDM) Workshop, Cumberland Lodge 2012,
invited talk
flag Medical Text Mining
as author at  2nd Workshop on Applications of Pattern Analysis (WAPA), Castro Urdiales 2011,
flag Kernel Polytope Faces Pursuit
as author at  Sessions,
flag Matching Pursuit Kernel Fisher Discriminant Analysis
as author at  Workshop on Sparsity in Machine Learning and Statistics, Cumberland Lodge 2009,
flag Multiview Fisher Discriminant Analysis
as author at  NIPS Workshop on Learning from Multiple Sources, Whistler 2008,
flag Linear Programming Boosting for Classification of Musical Genre
as author at  NIPS Workshop on Music, Brain and Cognition, Whistler 2007 ,