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

  • Task planning and the Connect-R: explainable AI for real world multi-robot system deployment 

    Roberts, Jamie Owen (The University of Edinburgh, 2023-02-06)
    The Connect-R is a novel Multi-Robot System that is intended to provide maintenance and servicing capabilities in nuclear environments. The Connect-R system is intended to address the problem of mitigating the effects of ...
  • Program synthesis for heterogenous accelerators 

    Collie, Bruce (The University of Edinburgh, 2018-11-29)
    [No Deposit Agreement]
  • Extensions to randomized benchmarking for digital and analogue near-term quantum devices 

    Derbyshire, Ellen (The University of Edinburgh, 2023-02-01)
    The distant promise of a full-scale fault-tolerant universal quantum computer offers a speed-up in run-time for certain problems compared to the best classical algorithms. Inevitably, attention has fallen on the quantum ...
  • Path integration system of insects: there and back again 

    Pisokas, Ioannis (The University of Edinburgh, 2023-01-31)
    Navigation is an essential capability of animate organisms and robots. Among animate organisms of particular interest are insects because they are capable of a variety of navigation competencies solving challenging problems ...
  • Low- and high-resource opinion summarization 

    Bražinskas, Arthur (The University of Edinburgh, 2023-01-25)
    Customer reviews play a vital role in the online purchasing decisions we make. The reviews express user opinions that are useful for setting realistic expectations and uncovering important details about products. However, ...
  • Learning the structure of clusters in graphs 

    Macgregor, Peter (The University of Edinburgh, 2023-01-25)
    Graph clustering is a fundamental problem in unsupervised learning, with numerous applications in computer science and in analysing real-world data. In many real-world applications, we find that the clusters have a significant ...
  • Data-efficient neural network training with dataset condensation 

    Zhao, Bo (The University of Edinburgh, 2023-01-24)
    The state of the art in many data driven fields including computer vision and natural language processing typically relies on training larger models on bigger data. It is reported by OpenAI that the computational cost to ...
  • FluiDB: adaptive storage layout using reversible relational operators 

    Perivolaropoulos, Christos (The University of Edinburgh, 2023-01-20)
    It is a popular practice to use materialized intermediate results to improve the perfor- mance of RDBMSes. Work in this area has focused either optimisers matching existing materialized results in the cache and selecting ...
  • Visual system identification: learning physical parameters and latent spaces from pixels 

    Jaques, Miguel (The University of Edinburgh, 2023-01-20)
    In this thesis, we develop machine learning systems that are able to leverage the knowledge of equations of motion (scene-specific or scene-agnostic) to perform object discovery, physical parameter estimation, position ...
  • Characterising the source of errors for metagenomic taxonomic classification 

    Crespi i Boixader, Alba (The University of Edinburgh, 2023-01-19)
    Characterising microbial communities enables a better understanding of their complexity and the contribution to the environment. Metagenomics has been a rapidly expanding field since the revolution of next generation ...
  • Structured parallelism discovery with hybrid static-dynamic analysis and evaluation technique 

    Vasiladiotis, Christos (The University of Edinburgh, 2023-01-17)
    Parallel computer architectures have dominated the computing landscape for the past two decades; a trend that is only expected to continue and intensify, with increasing specialization and heterogeneity. This creates huge ...
  • Temporality and modality in entailment graph induction 

    Bijl de Vroe, Sander Govert Cornelis (The University of Edinburgh, 2023-01-16)
    The ability to draw inferences is core to semantics and the field of Natural Language Processing. Answering a seemingly simple question like ‘Did Arsenal play Manchester yesterday’ from textual evidence that says ‘Arsenal ...
  • Structure-aware narrative summarization from multiple views 

    Papalampidi, Pinelopi (The University of Edinburgh, 2023-01-13)
    Narratives, such as movies and TV shows, provide a testbed for addressing a variety of challenges in the field of artificial intelligence. They are examples of complex stories where characters and events interact in many ...
  • Unbounded loops in quantum programs: categories and weak while loops 

    Andrés-Martínez, Pablo (The University of Edinburgh, 2023-01-13)
    Control flow of quantum programs is often divided into two different classes: classical and quantum. Quantum programs with classical control flow have their conditional branching determined by the classical outcome of ...
  • Meta-ontology fault detection 

    Casanova Jaquete, Juan (The University of Edinburgh, 2023-01-12)
    Ontology engineering is the field, within knowledge representation, concerned with using logic-based formalisms to represent knowledge, typically moderately sized knowledge bases called ontologies. How to best develop, use ...
  • Structured machine learning models for robustness against different factors of variability in robot control 

    Davchev, Todor Bozhinov (The University of Edinburgh, 2023-01-11)
    An important feature of human sensorimotor skill is our ability to learn to reuse them across different environmental contexts, in part due to our understanding of attributes of variability in these environments. This ...
  • Language integrated relational lenses 

    Horn, Rudi (The University of Edinburgh, 2023-01-10)
    Relational databases are ubiquitous. Such monolithic databases accumulate large amounts of data, yet applications typically only work on small portions of the data at a time. A subset of the database defined as a computation ...
  • Learning universal representations across tasks and domains 

    Li, Wei-Hong (The University of Edinburgh, 2022-12-16)
    A longstanding goal in computer vision research is to produce broad and general-purpose systems that work well on a broad range of vision problems and are capable of learning concepts only from few labelled samples. In ...
  • Document summarization with neural query modeling 

    Xu, Yumo (The University of Edinburgh, 2022-12-16)
    Document summarization is a natural language processing task that aims to produce a short summary that concisely delivers the most important information of a document or multiple documents. Over the last few decades, the ...
  • Network analysis of the post synaptic proteome and its implication for cognition 

    Robertson, Grant (The University of Edinburgh, 2022-12-15)
    The post synaptic proteome is a complex of more than 3,000 proteins that form modular molecular machines that are involved in signal transduction, information processing and learning in the central nervous system. Previous ...

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