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  • Prof Matthew Purver

    < Back Prof. Matthew Purver Queen Mary University of London Supervisor Matthew Purver is Professor of Computational Linguistics, and leader of QMUL’s Computational Linguistics Laboratory. His research has covered many aspects of natural language processing (NLP), with a £4m grant portfolio including projects on fundamental techniques like cross-lingual processing and incremental language understanding, and applications to news media, social media analysis and mental health diagnosis. His work has been covered by the Guardian, Telegraph, Independent, LA Times, NBC and Scientific American, among others. He is also a senior researcher at the Jožef Stefan Institute, Slovenia, and in 2011 he co-founded the company Chatterbox Labs Ltd. He is interested in supervising students with a background in NLP, linguistics or machine learning and an interest in analysis or generation of natural language. Research themes: Language in Games Game AI Computational Creativity Email m.purver@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game AI - Previous Next

  • Prof Nick Pears

    < Back Prof. Nick Pears University of York Supervisor Nick Pears is a Professor of Computer Vision in York’s Vision, Graphics and Learning (VGL) research group. He works on statistical modelling of 3D shapes, with an emphasis on the human face and head. The Liverpool-York Head Model and the associated Headspace training set has been downloaded by over 100 research groups internationally, with the Universal Head Model being downloaded by 50 research groups. His most recent work with his PhD students has focused on semantic disentanglement of 3D images and how to make autonomous vehicles safer and more trustworthy when using computer vision systems. He is assessor for many PhDs including construction of generative models for novel video content using adversarial deep learning techniques. Email nick.pears@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Game AI - Previous Next

  • British Broadcasting Corporation BBC

    iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. British Broadcasting Corporation BBC

  • Fusebox

    iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. Fusebox

  • New Moon Studios

    iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. New Moon Studios

  • How does machine learning affect diversity in evolutionary search? | iGGi PhD

    < Back How does machine learning affect diversity in evolutionary search? Procedural content generation of video games levels has greatly benefited from machine learning. In such complex domains, generative models can provide representation spaces for evolutionary search. But how expressive are such learned models? How many different levels would they be able to produce? A new paper, co-authored by IGGI PhD researcher Sebastian Berns and Professor Simon Colton, looks at the limitations of generative models in the context of multi-solution optimisation. The work will be presented at the Genetic and Evolutionary Computation Conference (GECCO) and is nominated for a best paper award . The study shows that quality diversity (QD) search in the latent space of a variational auto-encoder yields a solution set of lower diversity than in a manually-defined genetic parameter space. The authors find that learned latent spaces are useful for the comparison of artefacts and recommend their use for distance and similarity estimation. However, whenever a parametric search space is obtainable, it should be preferred over a learned representation space as it produces a higher diversity of solutions. Alexander Hagg, Sebastian Berns, Alexander Asteroth, Simon Colton & Thomas Bäck. (2021). Expressivity of Parameterized and Data-driven Representations in Quality Diversity Search. In Proceedings of the Genetic and Evolutionary Computation Conference. Pre-print available on arXiv https://arxiv.org/abs/2105.04247Accompanying code repository available on Github https://github.com/alexander-hagg/ExpressivityGECCO2021 Previous 27 Jun 2021 Next

  • Playing with evolution

    < Back Playing with evolution Link Author(s) RD Gaina Abstract More info TBA Link

  • Fnatic Limited

    iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. Fnatic Limited

  • MAP-Elites to Generate a Team of Agents that Elicits Diverse Automated Gameplay

    < Back MAP-Elites to Generate a Team of Agents that Elicits Diverse Automated Gameplay Link Author(s) C Guerrero-Romero, D Perez-Liebana Abstract More info TBA Link

  • King

    iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. King

  • Meaning Machine

    iGGi Partners We are excited to be collaborating with a number of industry partners. IGGI works with industry in some of the following ways: Student Industry Knowledge Transfer - this can take many forms, from what looks like a traditional placement, to a short term consultancy, to an ongoing relationship between the student and their industry partner. Student Sponsorship - for some of our students, their relationship with their industry partner is reinforced by sponsorship from the company. This is an excellent demonstration of the strength of the commitment and the success of the collaborations. In Kind Contributions - IGGI industry partners can contribute by attending and/or featuring in our annual conference, offering their time to give talks and masterclasses for our students, or even taking part in our annual game jam! There are many ways for our industry partners to work with IGGI. If you are interested in becoming involved, please do contact us so we can discuss what might be suitable for you. Meaning Machine

  • University of Essex (UoE) | iGGi PhD

    < Back iGGi Essex is located two miles from the historic city of Colchester and set in over 200 acres of beautiful parkland. iGGi is a consortium of four universities or sites: the University of York (York), Queen Mary University of London (QMUL), Goldsmiths, University of London (Goldsmiths), and the University of Essex (Essex). iGGi received funding in two phases: “iGGi 1” funded the first five cohorts of researchers across York, QMUL, Goldsmiths, and Essex and PGR intake spans from 2014 to 2018; “iGGi 2” started in 2019 with funding for a further five cohorts, this time only at York and QMUL. One of the "Essex iGGis" from the iGGi 1 funding round is still in the process of completing their PhD work. Essex is therefore still listed here as an active iGGi site, even though future iGGi main events such as the iGGi Conference and the iGGi Game Jam will take place at one of the iGGi 2 sites, i.e., either York or QMUL. iGGi Essex is part of the University of Essex's School of Computer Science and Electronic Engineering . You can find the University of Essex campus map in the gallery below. University of Essex (UoE) iGGi Essex Gallery University of Essex Colchester Campus University of Essex Campus Map Colchester Campus, University of Essex Previous Next

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