School of Informatics

Research Directory

A listing of researchers by institute and their main areas of interest.

Artificial Intelligence and its Applications Institute

Artificial Intelligence and its Applications Institute (AIAI) is a community of researchers working on the foundations of artificial intelligence and autonomous systems, and their application to real-world problems.

Institute Web Site

  • Vaishak Belle - machine learning, knowledge representation, artificial intelligence, scalable probabilistic inference and learning, probabilistic programming, statistical relational learning, automated planning, reasoning about knowledge and uncertainty, cognitive robotics, and logic and probability more generally
  • Alan Bundy - Understanding the processes of mathematical reasoning and discovery, including the processes of: forming and evolving formal representations; planning proofs; learning proof methods; and the use of analogy. In particular, the automated detection and repair of faulty representations.
  • Jacques Fleuriot - Artificial Intelligence and its use in modelling and reasoning about complex systems, safe and trustworthy AI, healthcare modelling, formal verification and interactive theorem proving, computer-based investigation of historical mathematics.
  • Kobi Gal - Artificial Intelligence, multi-agent systems, human-computer decision-making, educational data mining, AI in education, learning analytics
  • Igor Goryanin - Systems biology and systems medicine including human biochemical network reconstruction, modelling of complex biological systems, microbial fuel cells and other biotechnology and bioinformatics applications
  • Fengxiang He - Trustworthy AI, particularly deep learning theory and explainability, theory of decentralised learning, privacy in machine learning, symmetry in machine learning, learning theory in game-theoretical problems, and their applications in economics and finance.
  • Paul Jackson - Formal verification of hardware, software and cyber-physical systems. Formalised mathematics. Automation of formal reasoning.
  • Nadin Kokciyan
  • Wenda Li
  • Tiejun Ma
  • Siddharth N
  • Valerio Restocchi
  • David Robertson
  • Michael Rovatsos - Multiagent systems, ethical AI, social computation, automated planning, game-theoretic AI.

Institute for Adaptive and Neural Computation

The Institute studies brain processes and artificial learning systems, theoretically and empirically, drawing on the disciplines of neuroscience, cognitive science, computer science, computational science, mathematics and statistics.

Institute Web Site

  • Douglas Armstrong - Bioinformatics, Neuroinformatics, Behaviour Genetics and Astrobiology and Gravitational Biology
  • Angus Chadwick - Computational/theoretical neuroscience and machine learning.
  • Nigel Goddard - Applications of datascience methods in energy, social care, economic modelling and ecology
  • Henry Gouk - I undertake machine learning research that bridges the gap between theory and practice, with the goal of making systems that depend on machine learning more reliable.
  • Michael Gutmann - Bayesian inference, Bayesian experimental design, representation learning, machine learning, machine learning/AI for science
  • Matthias Hennig
  • Ava Khamseh - Semi-parametric probabilistic modelling, targeted learning, machine learning, causal inference and its applications to population biomedicine, cancer modelling, experimental molecular biology (genomics and transcriptomics)
  • Oisin Mac Aodha - Machine Learning, Computer Vision, Deep Learning, Human-in-the-Loop Machine Learning
  • Nikolay Malkin
  • Iain Murray - Bayesian inference, Machine Learning, hierarchical probabilistic models, density estimation
  • Kia Nazarpour - Digital Health and Care, Neural Systems and Rehabilitation Engineering
  • Arno Onken - Machine learning applications in computational neuroscience
  • Diego Oyarzun
  • Peggy Series - computational psychiatry, computational neuroscience, cognitive science.
  • Ian Simpson - Biomedical Informatics Group (BIG@Informatics)

    Computational Biology, Statistics and Machine Learning approaches to Biomedical data.

    Methodological Areas: - Graph Based Approaches to Data Integration & Analysis - Biomedical Natural Language Processing - Genomics & Proteomics Analysis

    Projects in: - Developmental Gene Expression - Clinical & LiteratureText-Mining & Processing - Embedded Graph-Learning - Regulatory & Evolutionary Genomics - Neurological Disease Modelling & Understanding (e.g. Autism & Intellectual Disability)

  • Amos Storkey - Deep learning, machine learning, machine learning markets, Bayesian inference, probabilistic graphical models, stochastic systems and sampling, Gaussian process models, probabilistic image models, image processing/computer vision techniques, medical imaging.
  • Antonio Vergari - Reliable and efficient probabilistic models. Equipping deep neural networks with complex probabilistic reasoning capabilities. Automating learning and inference.
  • Sethu Vijayakumar - Statistical Machine Learning, Robotics, Motor Control, Multimodal Sensory-Motor Integration and Computational Neuroscience.
  • Andrea Weisse
  • Christopher Williams - Theoretical and practical issues in machine learning, neural networks, probabilistic graphical models and computer vision. Time series understanding, image understandng, prediction with Gaussian processes.
  • Michael Yates

Institute for Computing Systems Architecture

The ICSA is primarily concerned with the architecture and engineering of future computing systems. Its fundamental research aims are: to extend the understanding of the performance and scalability of existing computational systems; to improve the characteristics of current systems through innovations in algorithms, architectures, compilers, languages and protocols; to develop new and novel architectures and to develop new engineering methods by which future systems can be created and maintained.

Institute Web Site

  • D K Arvind - Integration of Asynchronous Concurrent Systems, Parallel and Distributed Computation.
  • Antonio Barbalace - Operating systems, virtualization environment, compiler, linker, runtime systems for parallel, distributed, and heterogeneous computer architectures (including near data processing platforms).

    Real-time and general-purpose scheduling, targeting large deployments (data-center) as well as small-devices (embedded/IoT).

  • Jianyi Cheng
  • Murray Cole - Parallel algorithms, skeletal parallel programming.
  • Bjoern Franke - Automatic parallelisation, dynamic binary translation, code optimisation, parallel programming, instruction set simulation, dynamic analysis.
  • Boris Grot - Computer architecture, memory systems and interconnection networks. Architectural support for large-scale data processing. Systems with quality-of-service guarantees.
  • Michio Honda - Computer networks, Operating Systems, Internet architecture and datacenter systems.
  • Jingjie Li
  • Luo Mai
  • Mahesh Marina - Wireless networks, mobile systems, machine learning applications in wireless networks and mobile systems, mobile privacy, network security.
  • Vijay Nagarajan - General research interests: Software/hardware collaborative techniques for enhancing performance, programmability, reliability and security of parallel architectures. Current research topics: Memory consistency, cache coherence and synchronization for scalable parallel architectures.
  • Michael O'Boyle - Auto-parallelisation, machine learning based compilation, optimising for heterogeneous multi-cores, GPU optimisation, design space exploration, robotics/vision/deep learning application drivers
  • Yuvraj Patel - I am a Systems researcher and interested in building systems. My work spans several areas: Concurrency, Operating Systems, Security, Storage & File Systems, and Distributed Systems.
  • Paul Patras - mobile intelligence, performance optimisation in mobile networks, security and privacy
  • Adriana Sejfia
  • Amir Shaikhha - Domain-Specific Languages, Compilers, Databases, Programming Languages
  • Perdita Stevens - Mathematics of software engineering, especially model-driven development.
  • Nigel Topham - Design and analysis of high-performance computing systems, architecture simulation tools.

Institute for Language, Cognition and Computation

The Institute is dedicated to the computational study of language, communication, and cognition, in both humans and machines. Research areas include automatic speech and language processing, dialogue systems, models of human communication and language processing, information retrieval and presentation, and assistive technology.

Institute Web Site

  • Youssef Al Hariri
  • Bea Alex - natural language processing, text mining, information extraction
  • Emily Allaway
  • Benjamin Bach - Information Visualization, Augmented Reality, Human-Computer Interaction, Networks
  • Peter Bell - Speech technology, particularly machine learning methods for automatic speech recognition spoken language understanding
  • Alexandra Birch-Mayne
  • Tara Capel
  • Shay Cohen
  • Jeff Dalton
  • Tj Elmas
  • Sharon Goldwater - Unsupervised learning of language (human language acquisition and machine learning), Bayesian models, cognitive modeling, morphological and phonological processing.
  • Uta Hinrichs - Data visualization, Human-Computer Interaction, Interaction Design. Special interest in digital humanities, visualizing cultural collections, visualization for public knowledge institutions, and visualization teaching and learning.
  • Frank Keller - Cognitive modeling, language processing, language and vision, parsing, unsupervised learning, eye-tracking
  • Simon King - new acoustic models such as Linear Dynamical Systems for speech recognition and automatically finding suitable units to model with them; integrating speech recognition with other tasks like information extraction or dialogue move detection; the use of articulatory information for both recognition and synthesis, including applications such as join cost calculation and join smoothing for unit selection synthesis;extending my earlier work on the use of phonological/accoustic/articulatory features for ASR; applying methodsdeveloped for speech processing to the singing voice.
  • Maithilee Kunda
  • Catherine Lai
  • Mirella Lapata
  • Alex Lascarides - Computational semantics, particularly embodied conversation; learning strategies in complex games; learning to adapt to unforeseen possibilities; interactive task learning
  • Susan Lechelt
  • John Lee - Rich media in learning, graphics in reasoning and learning, computing and cognition in design, multimodal dialogue, informal data.
  • Adam Lopez
  • Christopher Lucas
  • Walid Magdy - Computational social science, Data Science, Social media, Data mining, and Arabic NLP
  • Fiona Mcneill
  • Pasquale Minervini
  • Brian Mitchell
  • Jeff Pan - Knowledge representation and artificial intelligence, knowledge based reasoning and learning, knowledge based natural language understanding and generation
  • Benjamin Peters
  • Edoardo Ponti
  • Korin Richmond
  • Judy Robertson
  • Bjorn Ross
  • Paul Schweizer - Philosophical logic, the computational paradigm and conceptual foundations of cognitive science and AI, philosophy of mind and language
  • Hiroshi Shimodaira - Trainable lifelike conversational agents, Acoustic models for automatic speech recognition, Handwriting recognition.
  • Mark Steedman - Computational linguistics, artificial intelligence, formal grammar, spoken intonation, statistical parsing, spoken language processing, animated conversational agents, computational musical analysis.
  • Hao Tang - Speech and language processing
  • Alex Taylor
  • Henry Thompson - Markup languages (XML, SGML) and architectures (Standoff markup, Schema languages, pipelines); Web Architecture; Philosophy of the Web.
  • Ivan Titov
  • John Vines - human-computer interaction; interaction design; participatory design / co-creation; responsible and trustworthy innovation / design / AI; data-driven systems for: ageing / finance / civic and community-led action.

Institute of Perception, Action and Behaviour

Linking computational action, perception, representation, transformation and generation processes to real or virtual worlds: statistical machine learning, computer vision, mobile and humanoid robotics, motor control, graphics and visualization.

Institute Web Site

  • Stefano Albrecht - Autonomous systems, multi-agent interaction, deep reinforcement learning, multi-agent reinforcement learning
  • Hakan Bilen - Computer vision and machine learning
  • Bob Fisher - Automatic acquisition of 3D models of: architecture, industrial parts, and people, using 3D data. Range data acquisition, fusion, and interpretation. Analysis of 3D video. Use of 3D data in robot control. Visual attention and search. Visual detection, tracking and behavior analysis of animals, humans, and other biological objects.
  • Michael Herrmann - Autonomous Robots, Human-Robot Interaction, Robot Swarms, Biorobotics, Prosthetics, Computational Neuroscience, Self-Organised Criticality, Neural Avalanches, Metaheuristic Optimisation, Cognitive Psychology, Biomedical Data Processing
  • Timothy Hospedales - Computer vision. Deep learning. Lifelong machine learning. Transfer and multi-task learning. Learning to Learn. Domain adaptation. Language and vision. Reinforcement Learning for control. Active Learning. Weakly supervised learning.
  • Craig Innes
  • Mohsen Khadem - Surgical Robotics and Image-guided Therapies, Continuum and Flexible Robots, Mechanics-based Modeling and Simulation, Applications of Control Theory in Robotics.
  • Taku Komura - Computer Animation, Computer Graphics, Character Control, Physically-based Animation, Human Modeling
  • Zhibin (Alex) Li - Create intelligent behaviors for robots with human-comparable abilities to move and operate using control theories, optimization and machine learning; translate robotics and AI technologies to healthcare for better quality of life and public well being, and tackle waste recycling/cleaning to protect environments and sustain a green planet.
  • Changjian Li - Computer Graphics and 3D Vision, 3D Shape Creation and Analysis with applications in Sketch-based Modeling, Shape Reconstruction and Analysis from Point Clouds, and Medical Image Processing and Modeling
  • Michael Mistry
  • Ram Ramamoorthy - Robot Learning, Decision Making under Uncertainty, Autonomous Systems, Dexterous Manipulation and Control, Human-Robot Interaction, Safe and Trustworthy Artificial Intelligence
  • Laura Sevilla-Lara - Computer Vision, Deep Learning, Video Understanding, Active Vision
  • Mohan Sridharan - Knowledge representation and reasoning, cognitive systems, and interactive learning in the context of human-robot and human-agent collaboration.
  • Kartic Subr - Rapid approximate simulation of physically-based systems: Applications to computer graphics, robotics, protein design, biological systems.
  • Steve Tonneau
  • Amir Vaxman - Geometry processing, discrete differential geometry, computer graphics, medical imaging, scientific computation, finite-element analysis, architectural and industrial geometric design.
  • Barbara Webb - Perceptual systems for the control of behaviour, Robot models of animals. Simulation of neural circuits.

Laboratory for Foundations of Computer Science

Achieving a foundational understanding of problems and issues arising in computation and communication through the development of appropriate and applicable formal models and mathematical theories.

Institute Web Site

  • Stuart Anderson - Design and analysis of dependable systems, formal proof in systems development.
  • Myrto Arapinis - Cyber security with a particular focus on provable security, formal models for verification and design of cryptographic protocols, and the problem of secure composition.
  • David Aspinall - Computer security (particularly proof-carrying code), type systems for specification and programming languages, and proof development environments.
  • Julian Bradfield - Modal and temporal logics, concurrency, independence logics, descriptive complexity and set theory, formal phonology, computational models of phonology, Khoisan languages.
  • Peter Buneman - Databases: data models, query languages, semistructured data, data provenance, databases and programming languages. Programming languages: functional programming and type systems. Bioinformatics and scientific databases. Mathematical phylogeny.
  • Yang Cao - Database systems: transaction processing; data-driving query optimization; graph computations
  • James Cheney - Programming languages, logic, scientific databases, provenance, security, verification.
  • Michele Ciampi
  • Alexandru Cojocaru
  • Mary Cryan - Randomized algorithms, especially algorithms for sampling and counting; learning theory; algorithms for computational biology.
  • Mina Doosti - Quantum information and computing, quantum cryptography, quantum learning theory
  • Tariq Elahi - I research computer and network security and privacy enhancing technologies (PETs) with an emphasis on effective, efficient, and robust deployments. My research has, and continues to, span the systematization and the game-theoretic analysis of censorship resistance and circumvention systems, security analysis and designs of anonymous communication systems, and privacy-preserving data collection in privacy-sensitive scenarios. I am interested in novel applications and enhancements to PETs techniques and strategies to exotic environments, such as Smart Cities where standard trust and availability assumptions need not apply.
  • Kousha Etessami - In general, theoretical computer science. More specifically: automated verification, logic, algorithms and computational complexity theory, algorithmic game theory, equilibrium computation, analysis of probabilistic systems, Markov decision processes, stochastic games, automata theory, model checking, analysis of infinite-state systems, finite model theory and descriptive complexity.
  • Wenfei Fan - Database theory and systems: big data, data quality, data integration, distributed query processing, query languages, recommender systems, social networks and Web services.
  • Aris Filos-Ratsikas
  • Raul Garcia-Patron Sanchez
  • Stephen Gilmore - Formal methods of program development, formal specifications, software engineering, concurrent systems.
  • Paolo Guagliardo - My research work lies at the intersection of database theory and practice, with a strong emphasis on making theoretical results applicable in real-life systems. My current focus is on devising and implementing principled and practical solutions for dealing with incomplete information in relational database systems, and on the analysis of concrete query languages for graph databases.
  • Heng Guo - Theoretical Computer Science, especially algorithms that count.
  • Chris Heunen - Quantum computing, programming languages, category theory.
  • Jane Hillston - Quantitative analysis and verification of dynamic system supported by formal methods. Formal methods such as stochastic process algebras and stochastic logics; mathematical models based on Markov processes, continuous approximations; applications such as performance modelling, collective adaptive systems, activities of daily life, systems biology. Research culture.
  • Paul Jackson - Formal verification of hardware, software and cyber-physical systems. Formalised mathematics. Automation of formal reasoning.
  • Marc Juarez Miro - privacy, security, networks, machine learning, algorithmic bias
  • Elham Kashefi - Models of quantum computing and their structural relations, exploring new applications, algorithms and cryptographic protocols for quantum information processing device.
  • Aggelos Kiayias
  • Markulf Kohlweiss - My research lie at the intersection of, formal verification, foundations of cryptography and applied cryptography, especially with regard to privacy-enhancing protocols, blockchains, and crypto currencies and the formal verification of protocol implementations.
  • Leonid Libkin - Databases and Applications of logic in computer science.
  • Sam Lindley
  • John Longley - Higher type computability, semantics of programming languages, program verification.
  • Richard Mayr - Automated verification, automata theory, temporal logic, model-checking and semantic equivalence checking, formal verification of real-time and probabilistic systems, infinite-state Markov chains, Markov decision processes and stochastic games.
  • Milos Nikolic - Databases and large-scale data management systems: in-database learning, stream processing, incremental computation, query compilation
  • Liam O'Connor - Programming languages for Trustworthy Systems
  • Andreas Pieris
  • Gordon Plotkin - Applications of logic, especially: the denotational and operational semantics of programming languages; type-theory; domain-theoretic and categorical analyses of computation; general proof theory; the semantics of natural language; process calculi and computational biology.
  • Elizabeth Polgreen - Program synthesis and verification
  • Ajitha Rajan - My research is in the field of software engineering and strives to address challenges in software validation and verification. I am especially interested in - Defining quality metrics for cloud applications and GPU programs. I am interested in coverage metrics for code, design, and requirements (functional, non-functional, security). - Automated test case generation, reduction and execution. - Optimising energy consumed by software. We investigated the energy consumed by software design patterns and proposed compiler optimisations for a couple fo the patterns in recent work. - Economic models for incremental software and software on the cloud. - Compiler optimisations for software test executions .
  • Don Sannella - Algebraic specification and formal software development; correctness of modular systems; types and functional programming; resource certification for mobile code.
  • Rik Sarkar - Datascience and Machine learning, network analysis, geometry, topology, Biomedical AI, distributed algorithms.
  • Ian Stark - Mathematical models and machine-assisted proof for reasoning about programming languages, processor architectures, and biochemical systems.
  • He Sun - Spectral graph theory, matrix analysis, applied probability
  • Philip Wadler - Programming languages, functional programming, type systems, dependent types, web programming, gradual typing, Agda, Haskell, Erlang, Go, Java, XML.
  • Petros Wallden - Quantum algorithms, quantum cyber security, quantum verification and benchmarking, quantum foundations
  • Daniel Woods - I research the economics of cybersecurity and privacy. Typically, this involves applying economic theory to understand the incentive and information structures behind how firms make cybersecurity and privacy decisions. To do this, I use a variety of quantitative and qualitative methodologies.
  • Rob van Glabbeek - Concurrency theory. Mathematical models and formal languages for the representation of distributed systems and the verification of statements about them; in particular foundational work investigating the possibilities of such models and languages.