Students

Antreas Antoniou - 2016 intake

Antreas Antoniou Mainly interested in innovative applications to deep learning, especially vision related ones and expanding unsupervised learning via research in Variational Autoencoders and Generative Adversarial networks. Also, very interested in the area of explorative reinforcement learning, which can provide general purpose models that can then be applied to more specific areas.

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Ivana Balazevic - 2016 intake

Ivana Balazevic Machine learning, natural language understanding, natural language generation, deep learning

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Artur Bekasov - 2016 intake

Artur Bekasov Machine learning, deep neural networks, representation learning, image and natural language understanding, unsupervised learning.

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Juan Casanova - 2016 intake

Juan Casanova Theoretical notions behind computer science. In particular, automated reasoning and its relation to ontological management of data. Additionally, the mathematical and theoretical study of software modularity and other more general notions of modularity and elasticity.

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Ryan Davies - 2015 intake

Ryan Davies Machine learning, neural networks and natural language processing, particularly for information extraction.

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Conor Durkan - 2016 intake

Conor Durkan Methods, tools, and applications for machine learning, including deep learning and content-based recommendation.

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Simão Eduardo - 2015 intake

Simão Eduardo Machine Learning, Unsupervised Learning, Graphical Models, (Deep) Neural Networks, Large-Scale/ Distributed Machine Learning and Optimisation. Applications in Text Mining, Computer Vision, Econometrics and Networks (Energy and Communications).

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Harrison Edwards - 2014 intake

Harrison Edwards Representation learning using deep neural networks. Representing sets, with applications to information retrieval, content-based recommendation and generative models. Adversarial learning for fair decision making.

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Sona Galovicova - 2015 intake

Sona Galovicova Machine learning, optimization algorithms and statistical theory.

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Sorcha Gilroy - 2014 intake

Sorcha Gilroy Machine translation and natural language processing. Particular interest in semantic representations of sentences and formal languages of graphs.

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Maria Gorinova - 2016 intake

Maria Gorinova Probabilistic Programming Languages. Machine Learning for Source Code. Software Verification and Synthesis.

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Zack Hodari - 2016 intake

Zack Hodari Machine learning, neural networks, generative models, unsupervised learning, sentiment/emotion analysis in speech.

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Borislav Ikonomov - 2015 intake

Borislav Ikonomov Machine learning, Statistics, Natural language processing, Computer vision, Neuroinformatics, Quantum computing

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Andreas Kapourani - 2014 intake

Andreas Kapourani Machine learning, Bayesian statistics, probabilistic modelling of biological systems, computational epigenetics

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Rafael-Michael Karampatsis - 2014 intake

Rafael-Michael Karampatsis Sentiment analysis and opinion mining for social media, multilingual sentiment analysis, text mining, topic modeling and deep learning for social media, building an NLP pipeline for social media.

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Jonathan Mallinson - 2015 intake

Jonathan Mallinson Computational linguistics, Compositional distributional semantics, sentiment analysis, semantic role labeling and paraphrase detection.

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Jozef Mokry - 2015 intake

Jozef Mokry Deep learning methods applied to machine translation.

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Charlie Nash - 2014 intake

Charlie Nash Probabilistic modelling, approximate inference, deep learning, vision as inverse graphics.

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James Owers - 2015 intake

James Owers Machine learning, in particular random forest and neural networks with applications to online education and energy. Previous experience with fraud and image data.

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George Papamakarios - 2014 intake

George Papamakarios Probabilistic machine learning, approximate methods for Bayesian inference. Past interests have included optimization, computer vision, and parallel computing.

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Theo Pavlakou - 2014 intake

Theo Pavlakou Machine Learning, Density Estimation, Graphical Models, Representation Learning and Optimisation.

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Matt Pugh - 2014 intake

Matt Pugh High performance & distributed computing, data-representation & storage, non-volatile memory, computer vision, object recognition & classification, and machine learning.

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Alexander Robertson - 2016 intake

Alexander Robertson Computational modeling of historical spelling variation which involves natural language processing, unsupervised machine learning and psycholinguistic experimentation.

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Matt Rounds - 2015 intake

Matt Rounds Machine learning, deep neural networks, human-like computing, applications to computer vision, applications to neuroinformatics.

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Benedek Rózemberczki - 2016 intake

Benedek Rózemberczki Graph clustering algorithms, homophily, combinatorial optimization, diffuson processes, semi-supervised learning.

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Philippa Shoemark - 2014 intake

Philippa Shoemark Computational linguistics, natural language processing, cognitive modelling, complex networks. Currently focused on linguistic alignment & spreading phenomena in social media, & agent-based models of language change.

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Clara Vania - 2014 intake

Clara Vania Machine Translation, Natural Language Understanding, Low-resource NLP, Unsupervised Learning and Representation Learning for NLP.

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Yanghao Wang

Yanghao Wang Database theory and systems, big data processing and data mining.

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