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.

Recent Submissions

  • Domain-aware ontology matching 

    Quesada Real, Francisco José (The University of Edinburgh, 2021-07-31)
    During the last years, technological advances have created new ways of communication, which have motivated governments, companies and institutions to digitalise the data they have in order to make it accessible and ...
  • Monitoring depressive symptoms using social media data 

    Chen, Lushi (The University of Edinburgh, 2021-07-31)
    Social media data contains rich information about one's emotions and daily life experiences. In the recent decade, researchers have found links between people's behavior on social media platforms and their mental health ...
  • Robust learning of acoustic representations from diverse speech data 

    Fainberg, Joachim (The University of Edinburgh, 2021-07-31)
    Automatic speech recognition is increasingly applied to new domains. A key challenge is to robustly learn, update and maintain representations to cope with transient acoustic conditions. A typical example is broadcast ...
  • Together for change: investigating a socio-technical system approach for supporting miscarriage 

    Alqassim, Mona Yahya M (The University of Edinburgh, 2021-07-31)
    Globally, miscarriage is affecting a substantial number of women: about 1 in 5 women who know they are pregnant miscarry. Importantly, miscarriage can be profoundly distressing, and lack of social support during and after ...
  • Classical secure delegation of quantum computations 

    Cojocaru, Alexandru Dragos (The University of Edinburgh, 2021-07-31)
    The rapid evolution of quantum technologies is likely to cause major shifts in the mainstream computing landscape. In order to fully reach their potential in a wide base accessible to any user, remote access of quantum ...
  • Scalable deep learning for bug detection 

    Karampatsis, Rafael-Michael (The University of Edinburgh, 2021-07-31)
    The application of machine learning (ML) and natural language processing (NLP) methods for creating software engineering (SE) tools is a recent emerging trend. A crucial early decision is how to model software’s vocabulary. ...
  • Facilitating pretend play in children with autism through interactive, augmented narratives 

    Dragomir, Mihaela (The University of Edinburgh, 2021-07-31)
    Pretend play is a key developmental tool, with its early performance being a predictor for later language, social interaction and communication skills. The level of these skills in turn influences an individual’s ability ...
  • Unsupervised Learning of Relational Entailment Graphs from Text 

    Hosseini, Mohammad Javad (The University of Edinburgh, 2021-07-31)
    Recognizing textual entailment and paraphrasing is critical to many core natural language processing applications including question answering and semantic parsing. The surface form of a sentence that answers a question ...
  • Computational and neuroimaging approaches to major depressive disorder 

    Rupprechter, Samuel (The University of Edinburgh, 2020-11-30)
    Major depression is a severely debilitating psychiatric condition with high prevalence and substantial economic impact. However, its aetiology is largely unknown, mechanistic understanding remains limited, and treatment ...
  • Human genome interaction: models for designing DNA sequences 

    Scher, Emily Alice (The University of Edinburgh, 2020-11-30)
    Since the turn of the century, the scope and scale of Synthetic Biology projects have grown dramatically. Instead of limiting themselves to simple genetic circuits, researchers aim for genome-scale organism redesigns, ...
  • Generalisation in deep reinforcement learning with multiple tasks and domains 

    Zhao, Chenyang (The University of Edinburgh, 2020-11-30)
    A long standing vision of robotics research is to build autonomous systems that can adapt to unforeseen environmental perturbations and learn a set of tasks progressively. Reinforcement learning (RL) has shown great ...
  • Analytics of time management strategies in online learning environments: a novel methodological approach 

    Ahmad Uzir, Nora'Ayu Binti (The University of Edinburgh, 2020-11-30)
    The emergence of technology-supported education, e.g., blended and online, has changed the global higher education landscape. Importantly, the new learning modes involve more complex tasks and challenging ways of learning ...
  • Unsupervised learning with neural latent variable models 

    Nash, Charlie (The University of Edinburgh, 2020-11-30)
    Latent variable models assume the existence of unobserved factors that are responsible for generating observed data. Deep latent variable models that make use of neural components are effective at modelling and learning ...
  • On the foundations of proof-of-work based blockchain protocols 

    Panagiotakos, Georgios (The University of Edinburgh, 2020-11-30)
    Proof-of-work (PoW) based blockchain protocols, are protocols that organize data into blocks, connected through the use of a hash function to form chains, and which make use of PoW to reach agreement, i.e., proofs ...
  • Tracing learning strategies in online learning environments: a learning analytics approach 

    Matcha, Wannisa (The University of Edinburgh, 2020-07-28)
    Learning has expanded beyond formal education; yet, students continue to face the challenge of how to effectively direct their learning. Among the processes of learning, the selection and application of learning tactics ...
  • Self-directed learning in new and changing environments: understanding human algorithms for exploration 

    Collignon, Nicolas (The University of Edinburgh, 2020-07-25)
    In order to act, plan, and achieve goals, people must learn about their environment and the outcome of possible actions. One reason for human successes in developing new theories and strategies when confronted with new ...
  • Formal modelling and approximation-based analysis for mode-switching population dynamics 

    Piho, Paul (The University of Edinburgh, 2020-07-25)
    This thesis explores aspects of model specification and analysis for population dynamics which arise when modelling complex interactions and communication structures in agent or component collectives. The motivating ...
  • Relational reasoning for effects and handlers 

    McLaughlin, Craig (The University of Edinburgh, 2020-07-25)
    This thesis studies relational reasoning techniques for FRANK, a strict functional language supporting algebraic effects and their handlers, within a general, formalised approach for completely characterising observational ...
  • Approximating neural machine translation for efficiency 

    Aji, Alham Fikri (The University of Edinburgh, 2020-07-25)
    Neural machine translation (NMT) has been shown to outperform statistical machine translation. However, NMT models typically require a large number of parameters and are expensive to train and deploy. Moreover, its large ...
  • Formalising cryptography using CryptHOL. 

    Butler, David Thomas (The University of Edinburgh, 2020-06-25)
    Security proofs are now a cornerstone of modern cryptography. Provable security has greatly increased the level of rigour of the security statements, however proofs of these statements often present informal or incomplete ...

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