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Thore Graepel

Thore Graepel

I am a Principal Researcher in Machine Learning at Microsoft Research Cambridge coordinating research in the areas of Online Services and Advertising and Applied Games. Our work is focused on the application of large scale machine learning and probabilistic modelling techniques to a wide range of problems including online advertising, web search, and games. More recently, I have been investigating crowdsourcing, collective intelligence and social networking data.

I also hold a part-time position in the Computer Science Department at University College London (UCL) as Professor of Machine Learning.

Currently, I am thinking about what it would take to implement a truly intelligent artificial agent in a bottom-up fashion. The human cerebral cortex proves that physical matter can be arranged so as to produce intelligence, and I think we need to take inspiration from the only known implementation of true intelligence.

Here is a selection of projects I am or have been involved in:

  • TrueSkill: A Bayesian Skill Rating and Matchmaking System for Xbox Live.
  • AdPredictor: A large-scale Bayesian click-through rate prediction system deployed in Bing.
  • Matchbox: A Bayesian recommendation system that combines aspects of content based and collaborative filtering.
  • Human Manifold: Predicting human attributes from digital traces.
  • Tabular: A probabilistic programming language based on relational data schemata.
  • Research Games: A number of Facebook based games for studying strategic behaviour.