Mark Elshaw

Dr

    Calculated based on number of publications stored in Pure and citations from Scopus
    20032019

    Research activity per year

    Personal profile

    Biography

    Dr Mark Elshaw has been a Researcher for 15 years in three different research groups: The Hybrid Intelligent Systems Group (University of Sunderland), the Speech and Hearing Group (Sheffield University) and Intelligent Computation Group (Coventry University). He has worked on and been part of the successful management team for UK and EU funded projects, and disseminated research findings via 30+ peer reviews publications, outreach events and numerous project reports. He has also edited 3 computational neuroscience books, organised conferences and seminars, helped in the creation of successful funding proposals, and is reviewer for various conferences and journals. He was part of the team who won the British Computer Society intelligent machine prize for a bio-inspired robot.

    Area of Expertise:

    Robotics, neural network, electronic noses, biological inspired computing systems.

    Research Interests

    Speech recognition; Robot-human interaction; Grounding of speech and actions in robots; Biomimetic robotics and their applications; Emotional production and recognition in robots; Use of an experimental-based methodology for creating intelligent systems

    Vision Statement

    I am particularly focused on the development of novel unsupervised neural memory architectures that take their inspiration from how the brain learns and performs prediction and recognition activities. Such inspiration comes from but is not limited to the mirror neuron system, reinforcement learning and working- and long-term memory in the brain. I am also interested in exploring how unsupervised neural approaches can be adapted to better process temporal data and the utilisation of an experimental-based methodology for developing companion social robot. Such a methodology would combine intelligent memory models within an integration architecture to develop a social robot that encourages beneficial lifestyle choices.

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