The School of Informatics brings together research in Computer Science, Cognitive Science, Computational Linguistics and Artificial Intelligence. It provides a fertile environment for a wide range of interdisciplinary studies, leading to this new science of Informatics.

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Recent Submissions

  • Towards efficient universal neural machine translation 

    Zhang, Biao (The University of Edinburgh, 2022-08-03)
    Humans benefit from communication but suffer from language barriers. Machine translation (MT) aims to overcome such barriers by automatically transforming information from one language to another. With the rapid development ...
  • Generalization challenges in semantic parsing 

    Wang, Bailin (The University of Edinburgh, 2022-07-29)
    Semantic parsing is the task of translating natural language utterances onto machine-interpretable programs, which can be executed against a real-world environment to obtain desired responses (e.g., a SQL query against a ...
  • Dependable virtualised systems 

    Thalheim, Jörg (The University of Edinburgh, 2022-06-28)
    Virtual machines and containers are widely used in data centres and in the cloud for software deployment and management. Their popularity is based on higher capacity utilisation, lower maintenance costs, and better ...
  • Opinion summarization of multiple reviews: data synthesis and modeling 

    Amplayo, Reinald Kim (The University of Edinburgh, 2022-06-28)
    The proliferation of online reviews has accelerated research on opinion mining, where the ultimate goal is to glean information from reviews which help users make decisions more efficiently. While opinion mining has ...
  • Expression and perception of identity through skin-toned emoji 

    Robertson, Alexander (The University of Edinburgh, 2022-06-28)
    The introduction of emoji skin tone modifiers to the Unicode Standard in 2015 was met with considerable debate on the extent to which these emoji would be used, who would actually use them, and what they would actually be ...
  • Analysing privacy in online social media 

    Kekulluoglu, Dilara (The University of Edinburgh, 2022-06-28)
    People share a wide variety of information on social media, including personal and sensitive information, without understanding the size of their audience which may cause privacy complications. The networked nature of the ...
  • Accurate and reliable probabilistic modeling with high-dimensional data 

    Bekasov, Artur (The University of Edinburgh, 2022-06-23)
    Machine learning studies algorithms for learning from data. Probabilistic modeling and reasoning define a principled framework for machine learning, where probability theory is used to represent and manipulate knowledge. ...
  • On the volume and veracity of big and shared data 

    Wang, Yanghao (The University of Edinburgh, 2022-06-22)
    Big data is not new to us. Many efforts are devoted to efficient and parallel query processing of big data. Nevertheless there are still some missing pieces in the technical stack. Existing systems typically assume that ...
  • Great expectations: unsupervised inference of suspense, surprise and salience in storytelling 

    Wilmot, David (The University of Edinburgh, 2022-06-22)
    Stories interest us not because they are a sequence of mundane and predictable events but because they have drama and tension. Crucial to creating dramatic and exciting stories are surprise and suspense. Likewise, certain ...
  • Reclaiming scalability and privacy in the decentralized setting 

    Thyfronitis Litos, Orfeas Stefanos; Litos, Orfeas (The University of Edinburgh, 2022-07-11)
    The advent of blockchains has expanded the horizon of possibilities to novel decentralised applications and protocols that were not possible before. Designing and building such applications, be it for offering new ways for ...
  • Automated Testing for Solidity smart contracts 

    Akca, Sefa (The University of Edinburgh, 2022-06-21)
    Blockchains are the underlying technology for making secure online transactions using cryptocurrencies such as Bitcoins and Ethers. Executing, verifying, and enforcing credible transactions on permissionless blockchains ...
  • Tackling the veracity and variety of big data 

    Jin, Ruochun (The University of Edinburgh, 2022-06-21)
    This thesis tackles the veracity and variety challenges of big data, especially focusing on graphs and relational data. We start with proposing a class of graph association rules (GARs) to specify regularities between ...
  • Secure authentication and key agreement via abstract multi-agent interaction 

    Ahmed, Ibrahim Hassan (The University of Edinburgh, 2022-06-17)
    Authentication and key agreement are the foundation for secure communication over the Internet. Authenticated Key Exchange (AKE) protocols provide methods for communicating parties to authenticate each other, and establish ...
  • Hotscotch: exploiting workload characteristics to improve read-throughput 

    Pugh, Matthew (The University of Edinburgh, 2022-06-14)
    Key-value stores are ubiquitous at all layers of the computational stack; offering constant average lookup, insertion, and deletion time. This dissertation looks at how we can exploit skew in the workloads to improve the ...
  • Architectures for online simulation-based inference applied to robot motion planning 

    Asenov, Martin Andreev (The University of Edinburgh, 2022-06-13)
    Robotic systems have enjoyed significant adoption in industrial and field applications in structured environments, where clear specifications of the task and observations are available. Deploying robots in unstructured ...
  • Pronunciation modelling in end-to-end text-to-speech synthesis 

    Taylor, Jason (The University of Edinburgh, 2022-06-13)
    Sequence-to-sequence (S2S) models in text-to-speech synthesis (TTS) can achieve high-quality naturalness scores without extensive processing of text-input. Since S2S models have been proposed in multiple aspects of the ...
  • Practical synthesis from real-world oracles 

    Collie, Bruce (The University of Edinburgh, 2022-06-13)
    As software systems become increasingly heterogeneous, the ability of compilers to reason about an entire system has decreased. When components of a system are not implemented as traditional programs, but rather as specialised ...
  • Online dynamics model learning and control for robotics 

    Smith, Joshua (The University of Edinburgh, 2022-06-10)
    Robotic systems, of various sizes and types, are not only becoming more prominent in the research communities but have been further pushed into industrial and business uses. With the advent of more capable hardware able ...
  • Embodied agents in real-world robots: integrated control and machine learning for intelligent behaviours 

    Yuan, Kai (The University of Edinburgh, 2022-06-09)
    The central contribution of this thesis is providing a reliable framework and algorithms to make robots move as versatile and reliable as biological systems. To this end, this work proposes a hierarchical control framework ...
  • Robust and efficient inference and learning algorithms for generative models 

    Xu, Kai (The University of Edinburgh, 2022-06-09)
    Generative modelling is a popular paradigm in machine learning due to its natural ability to describe uncertainty in data and models and for its applications including data compression (Ho et al., 2020), missing data ...

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