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

  • Modular robots for sorting 

    McKenzie, Ross Malcolm (The University of Edinburgh, 2020-06-25)
    Current industrial sorting systems allow for low error, high throughput sorts with tightly constrained properties. These sorters, however, are often hardware limited to certain items and criteria. There is a need for ...
  • Deep learning for compilers 

    Cummins, Christopher Edward (The University of Edinburgh, 2020-06-25)
    Constructing compilers is hard. Optimising compilers are multi-million dollar projects spanning years of development, yet remain unable to fully exploit the available performance, and are prone to bugs. The rapid transition ...
  • Modelling and measurement in synthetic biology 

    Waites, William (The University of Edinburgh, 2020-02-10)
    Synthetic biology applies engineering principles to make progress in the study of complex biological phenomena. The aim is to develop understanding through the praxis of construction and design. The computational branch ...
  • Low-resource speech translation 

    Bansal, Sameer (The University of Edinburgh, 2019-12-17)
    We explore the task of speech-to-text translation (ST), where speech in one language (source) is converted to text in a different one (target). Traditional ST systems go through an intermediate step where the source ...
  • On understanding character-level models for representing morphology 

    Vania, Clara (The University of Edinburgh, 2020-01-20)
    Morphology is the study of how words are composed of smaller units of meaning (morphemes). It allows humans to create, memorize, and understand words in their language. To process and understand human languages, we expect ...
  • Understanding and generating language with abstract meaning representation 

    Damonte, Marco (The University of Edinburgh, 2020-01-08)
    Abstract Meaning Representation (AMR) is a semantic representation for natural language that encompasses annotations related to traditional tasks such as Named Entity Recognition (NER), Semantic Role Labeling (SRL), word ...
  • Design and evaluation of contracts for gradual typing 

    Williams, Jack (The University of Edinburgh, 2019-11-25)
    Gradual typing aims to improve the correctness of dynamically typed programs by incrementally adding type information. Sound gradual typing performs static type checking and inserts run-time checks when a type cannot be ...
  • Automatic performance optimisation of parallel programs for GPUs via rewrite rules 

    Remmelg, Toomas (The University of Edinburgh, 2019-12-11)
    Graphics Processing Units (GPUs) are now commonplace in computing systems and are the most successful parallel accelerators. Their performance is orders of magnitude higher than traditional Central Processing Units (CPUs) ...
  • Towards efficient support for massive Internet of Things over cellular networks 

    Tsoukaneri, Galini (The University of Edinburgh, 2019-12-12)
    The usage of Internet of Things (IoT) devices over cellular networks is seeing tremendous growth in recent years, and that growth in only expected to increase in the near future. While existing 4G and 5G cellular networks ...
  • 3D data fusion by depth refinement and pose recovery 

    Pu, Can (The University of Edinburgh, 2019-11-23)
    Refining depth maps from different sources to obtain a refined depth map, and aligning the rigid point clouds from different views, are two core techniques. Existing depth fusion algorithms do not provide a general ...
  • Test time cost sensitivity in machine learning 

    Gray, Gavin Douglas Buchanan (The University of Edinburgh, 2019-11-23)
    The use of deep neural networks has enabled machines to classify images, translate between languages and compete with humans in games. These achievements have been enabled by the large and expensive computational resources ...
  • Prosody generation for text-to-speech synthesis 

    Ronanki, Srikanth (The University of Edinburgh, 2019-09-30)
    The absence of convincing intonation makes current parametric speech synthesis systems sound dull and lifeless, even when trained on expressive speech data. Typically, these systems use regression techniques to predict ...
  • Social media in health and care co-production 

    Daneshvar Farzanegan, Sayed Hadi (The University of Edinburgh, 2019-11-23)
    The future of health and care services in the EU faces the three challenges of the aging population, fiscal restriction, and social inclusion. Co-production offers ways to manage informal care resources to enable them ...
  • Neural density estimation and likelihood-free inference 

    Papamakarios, Georgios (The University of Edinburgh, 2019-11-23)
    I consider two problems in machine learning and statistics: the problem of estimating the joint probability density of a collection of random variables, known as density estimation, and the problem of inferring model ...
  • Semantics and provenance of configuration programming language μPuppet 

    Fu, Weili (The University of Edinburgh, 2019-11-23)
    Nowadays computing infrastructures have grown bigger in scale and more complex. Automated configuration management tools have taken the place of traditional approaches of configuration tasks, such as manual configuration ...
  • Machine learning for inductive theorem proving 

    Jiang, Yaqing (The University of Edinburgh, 2019-11-23)
    Over the past few years, machine learning has been successfully combined with automated theorem provers (ATPs) to prove conjectures from various proof assistants. However, such approaches do not usually focus on inductive ...
  • Usability evaluation of spoken humanoid embodied conversational agents in mobile serious games 

    Korre, Danai (The University of Edinburgh, 2019-11-23)
    The use of embodied conversational agents (ECAs) and spoken dialogue systems in serious games offers theoretical advantages such as a more natural interaction with an agent displaying characteristics like personality, ...
  • Wide-coverage statistical parsing with minimalist grammars 

    Torr, John Philip (The University of Edinburgh, 2019-11-23)
    Syntactic parsing is the process of automatically assigning a structure to a string of words, and is arguably a necessary prerequisite for obtaining a detailed and precise representation of sentence meaning. For many NLP ...
  • Moving beyond parallel data for neutral machine translation 

    Currey, Anna (The University of Edinburgh, 2019-11-23)
    The goal of neural machine translation (NMT) is to build an end-to-end system that automatically translates sentences from the source language to the target language. Neural machine translation has become the dominant ...
  • Machine learning and privacy preserving algorithms for spatial and temporal sensing 

    Ghosh, Abhirup (The University of Edinburgh, 2019-11-23)
    Sensing physical and social environments are ubiquitous in modern mobile phones, IoT devices, and infrastructure-based settings. Information engraved in such data, especially the time and location attributes have ...

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