Simon Keizer studied Applied Mathematics at the University of Twente (NL).  He obtained his master's degree on the subject of knowledge graphs, a special variant of John Sowa's conceptual graphs, for representing natural language.  He then started his PhD research at the Computer Science department of the same university, in the research group Human Media Interaction.  This resulted in the successful defence of a dissertation on dealing with uncertainty in natural language dialogue using Bayesian networks. In particular, the work involved machine learning experiments on dialogue act recognition.

He continued his work on dialogue in the Department of Information and Communication Sciences at Tilburg University (NL).  The PARADIME postdoc project involved a multidimensional approach to dialogue management, in which the generation of dialogue acts is realised through several agents operating in parallel on the system's information state.  An implementation of this dialogue manager was integrated in an interactive question answering system, developed in cooperation with several other projects, specialising in question answering, syntactic & semantic analysis, speech recognition, and multimodal answer presentation.

In the Dialogue Systems Group at Cambridge University, he then worked on statistical approaches to dialogue management, in particular POMDPs (Partially-Observable Markov Decision Processes).  The focus of his work was on user modelling/simulation and dialogue systems evaluation.  He was involved in a EPSRC project as well as the EU FP7 project CLASSiC.

Currently, Simon is research associate in the Interaction Lab at Heriot-Watt University in Edinburgh, and is involved in the EU projects JAMES, SpaceBook, and STAC.

United Kingdom

Email: s<dot>keizer<at>hw<dot>ac<dot>uk