Past and Current PhD Students and Postdocs

PhD Students

• Francesco Vivarelli (1999)
  Studies on the Generalisation of Gaussian Processes and Bayesian Neural Networks
• Nicholas Adams (2001)
  Dynamic Trees: A Hierachical Probabilistic Approach to Image Modelling
• Stephen Felderhof (2003)
  Tree-Structured Graphical Models and Image Analysis
• Matthias Seeger (2003)
  Bayesian Gaussian Process Models: PAC-Bayesian Generalisation Error Bounds and Sparse Approximations
• Michalis Titsias (2005)
  Unsupervised Learning of Multiple Objects in Images
• Michael Schouten (2006)
  Modeling Dependencies in Genetic-marker Data and its Application to Haplotype Analysis
• John Quinn (2007)
  Bayesian Condition Monitoring in Neonatal Intensive Care
• Moray Allan (2007)
  Sprite Learning and Object Category Recognition using Invariant Features
• Edwin Bonilla (2008)
  Compilers that Learn to Optimise: A Probabilistic Machine Learning Approach
• Kian Ming Adam Chai (2010)
  Multi-task Learning with Gaussian Processes
• Nicolas Heess (2011)
  Learning Generative Models of Mid-level Structure in Natural Images
• Ondrej Mandula (2013)
  Super-resolution Methods for Fluorescence Microscopy
• Ali Eslami (2013)
  Generative Probabilistic Models for Object Segmentation
• Jyri Kivinen (2013)
  Statistical Models for Natural Scene Data
• Ioan Stanculescu (2015)
  Dynamical Models for Neonatal Intensive Care Monitoring
• Konstantinos Georgatzis (2017)
  Dynamical Probabilistic Graphical Models applied to Physiological Condition Monitoring
• Pol Moreno (2018)
  Vision as Inverse Graphics for Detailed Scene Understanding
• Lukasz Romaszko (2020)
  3D Scene Graph Inference and Refinement for Vision-as-Inverse-Graphics
• Charlie Nash (2020)
  Unsupervised Learning with Neural Latent Variable Models
• Alex Bird (2021)
  Multi-trask Dynamical Systems: Customizing Time Sries Models
• Taha Ceritli (2021)
  Probabilistic Type Inference for the Construction of Data Dictionaries
• Michael Camilleri (2023)
  Automated Identification and Behaviour Classification for Modelling Social Dynamics in Group-Housed Mice
• Cian Eastwood (2023)
  Shift happens: How can machine learning systems be best prepared?

Postdocs

• Xiaojuan Feng
• Amos Storkey
• Marc Toussaint
• Felix Agakov
• Stefan Harmeling
• Edwin Bonilla
• Partha Lal
• Sohan Seth
• Alfredo Nazabal (AIDA project, Alan Turing Institute)
• Gerrit van den Burg (AIDA project, Alan Turing Institute)