PhD Students

  • Marius Cobzaranco : Natural Language Models and Deep Learning.
  • Thomas Anthony : Games, Monte Carlo Tree Search and Deep Learning.
  • Alex Botev : Optimisation methods for Deep Learning
  • James Townsend : Automatic Differentiation Tools and Variational approaches for Learning
  • Harshil Shah : Generative Natural Language Models
  • Bowen Zheng : Natural Language Models and Deep Learning
  • Zheng Tian : Deep Learning and Markov Decision Processes
  • Raza Habib : TBA
  • Hippolyt Ritter : Optimisation and Bayesian methods for Deep Learning
  • Zhen He (visiting) : Tensorised models for Deep Learning
  • Thomas Bird : TBA
  • Benoit Gaujac : TBA
  • Pau Ching Yap : TBA

Former Students

  • Chris Bracegirdle : Bayesian Time-series models, in particular changepoint models and cointegration.
  • Ed Challis : Large-scale variational inference for Bayesian Machine Learning
  • Tom Furmston : Novel solution methods for Markov Decision Processes
  • Joe Staines : Machine Learning models to extract meaning in joint text and time series data.
  • Bertrand Mesot Graphical models for signal level analyses of speech signals, primarily for noise robust speech extraction and recognition.
  • Mike Perrow -- worked on networked information distribution and text processing. Now with Google.
  • Silvia Chiappa EEG analysis using temporal graphical models. Now with Microsoft Research.
  • Felix Agakov Graphical model approximations and Information Theoretic approaches to machine learning.
  • Machiel Westerdijk Generative Vector Quantization techniques.
  • Pierre van de Laar Model pruning and approximate methods for graphical models.