< Back Océane Lissillour University of York iGGi PG Researcher Available for placement I started my journey as an undergrad in psychology specialising in ergonomics. It was then that I realised that I could study video games for a living. This led me to relocate myself to the south of France to, mostly enjoy the sun, but also undertake my dream MSc in Technological Innovation and Cognitive Psychology. As part of my master’s internship I had the pleasure to work in collaboration with researchers from the CLLE, a laboratory branch of the national research centre. This helped me develop my knowledge and awareness of video games and motivational processes and convinced me that if I could survive the bureaucracy of the French Government I could probably do a PhD. Afterwards, I moved on to work in Aeronautics for a brief time but landed back to academia in 2024 to join the wonderful iGGI community as a postgraduate researcher. A description of Océane's research: My research focuses on the act of taking a regular activity and ‘gamifying’ it by applying mechanics commonly found inside video games (such as points). This technique has been widely applied within research but its psychological aspects have seldom been studied. The aim of this thesis is to assess the efficacy and applicability of this technique, particularly the score element mechanic. It focuses on understanding the functionalisation of numerical values in games as this has not been studied previously in the literature. This research hopes to contribute to the better understanding of the impact of the design of points on motivation and behaviour. It has been proposed in precedent literature that the use of gamification will provide a partial solution to the critical decline in learners’ motivation and engagement the schooling system faces today. Email oceane.lissillour@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisors: Dr Abi Evans Prof. Sebastian Deterding Themes Design & Development Player Research - Previous Next

< Back Connor Watts Queen Mary University of London iGGi PG Researcher I am a machine learning research engineer and software developer with commercial experience deploying and maintaining models for start-ups and larger organizations. I have experience researching and developing novel algorithms, as well as designing custom environments for application in domains such as combinatorial optimization, finance and games. Email c.watts@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Dr Paulo Rauber Themes Game AI - Previous Next

< Back Dr Athanasios Vasileios Kokkinakis University of York iGGi Alum Videogame Correlates of Real-Life Cognitive Traits Video-games have been increasingly gaining momentum and popularity, both with the public but also with the scientific world who has seen their usefulness in multiple areas. Researchers have been making bold claims of Videogames increasing Intelligence monopolizing the public’s attention and taking it away from what Videogames are excellent at; serving as diagnostic tools examining constructs such Reaction Times, Memory and fluid Intelligence. The sharp decline of the aforementioned concepts has been linked to multiple diseases such as the prodrome of Schizophrenia, Alzheimer’s and Dementia. Moreover, their measurement has been linked to important life outcomes such as Academic Achievement, Time in Unemployment, Unwanted Pregnancies and Mathematical Achievement among others. In my doctoral thesis I have correlated these constructs with the massively played video-game League of Legends. By cross-validating Psychometric measurements with Video-game metrics we can possibly identify at risk populations and stage Health Interventions or even identify “gifted” children or children that lag behind at an early age and place them in appropriate training curricula. He acquired his BSc in Psychology from the University of Bangor and he then went to complete his MSc in Cognitive Neuroscience at the University of York. In his first experiment he attempted to see whether “expert video-gamers” would show less Attentional Resources when compared to a control group of non-gamers and whether a short training session of approximately a week had any effects on the non-gamer group. His MSc, although not related to gaming, gave him valuable experience with EEG and MEG which he hopes to incorporate into his future experiments. In his most recent experiments he correlated psychometric Intelligence with Videogame Scores, more specifically League of Legends Tiers. He believes that these scores may give us insight on multiple developmental trajectories for instance healthy aging. Email athanasios dot kokkinakis *at* z)!gmail*com Website LinkedIn Mastodon BlueSky GitHub Other Link Prof. Alex Wade Prof. Peter Cowling Featured Publication(s): Data-Driven Audience Experiences in Esports Metagaming and metagames in Esports Videogame Correlates of Real Life Traits and Characteristics. Exploring the relationship between video game expertise and fluid intelligence Temporal and spatial localization of prediction-error signals in the visual brain What's in a name? Ages and names predict the valence of social interactions in a massive online game MEG adaptation resolves the spatiotemporal characteristics of face-sensitive brain responses Predicting skill learning in a large, longitudinal MOBA dataset Automatic Generation of Text for Match Recaps using Esport Caster Commentaries WARDS: Modelling the Worth of Vision in MOBA's DAX: Data-Driven Audience Experiences in Esports Time to die 2: Improved in-game death prediction in dota 2 Themes Esports Game AI Player Research Research Gate Google Scholar Previous Next

< Back Dr Gavin Kearney University of York Supervisor Dr Gavin Kearney is a highly experienced researcher, lecturer and content creator specialising in spatial audio and surround sound. He joined the University of York as Lecturer in Sound Design in January 2011 and was appointed Associate Professor in Audio and Music Technology in 2016. He has written over 60 research articles and patents on different facets of immersive and interactive audio, including real-time audio signal processing, Ambisonics, virtual and augmented reality and recording and audio post-production technique development. He has undertaken innovative projects in collaboration with Mercedes-Benz Grand Prix, BBC, Dolby, Huawei, Abbey Road and Google amongst others. With the latter, he helped define the Google spatial audio pipeline through development of the SADIE binaural filters and decoders used worldwide. He is also an active sound engineer and producer of immersive audio experiences, working to develop new techniques and workflows for immersive music production in collaboration with Abbey Road Studios. He is Vice-Chair of the AES Audio for Games Technical Committee and was Co-Chair of the 2019 AES Immersive and Interactive Audio Conference at York. Gavin is particularly interested in supervising students with an audio background who wish to explore the following areas relating to audio for games Intelligent sound design Virtual Acoustics Spatial Audio Binaural sound Audio for Virtual and Augmented Reality Immersive audio experiences for next gen mobile platforms Ambisonics and spherical acoustics Using audio to enhance player emotional state (as well as projects on health and well-being) Game Audio for therapy Accessibility through Game Audio Email gavin.kearney@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Accessibility Applied Games Game AI Game Audio - Previous Next

< Back Dr Terence Broad Goldsmiths iGGi Alum Terence Broad is an artist and researcher working on developing new techniques and interfaces for the manipulation of generative models. His PhD focusses on how pre-trained generative neural networks can be repurposed and reconfigured for authoring novel multimedia content. He is completing his PhD at Goldsmiths, University of London and is also a visiting researcher at the UAL Creative Computing Institute. His research has been published in international conferences, workshops and journals such as SIGGRAPH, NeurIPS, Leonardo and xCoAx. He was acknowledged as an outstanding peer-reviewer by the journal Leonardo. Terence is a practicing artist and often uses the techniques he has developed in his research in the creation of his artworks. His art has been exhibited and screened internationally at venues such as The Whitney Museum of American Art, Ars Electronica, The Barbican and The Whitechapel Gallery. He won the Grand Prize in the ICCV 2019 Computer Vision Art Gallery. Email t.broad@gold.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Co-Designing Fashion with AI: A Small-Data Approach to Generative Garment Design Expanding the Generative Space: Data-Free Techniques for Active Divergence with Generative Neural Networks XAIxArts Manifesto: Explainable AI for the Arts Using Generative AI as an Artistic Material: A Hacker's Guide Is computational creativity flourishing on the dead internet? Interactive Machine Learning for Generative Models Envisioning Distant Worlds: Fine-Tuning a Latent Diffusion Model with NASA's Exoplanet Data Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities Network Bending: Expressive Manipulation of Generative Models in Multiple Domains Active Divergence with Generative Deep Learning--A Survey and Taxonomy Network Bending: Expressive Manipulation of Deep Generative Models Amplifying The Uncanny Transforming the output of GANs by fine-tuning them with features from different datasets Searching for an (un) stable equilibrium: experiments in training generative models without data Autoencoding Blade Runner: Reconstructing Films with Artificial Neural Networks Light field completion using focal stack propagation Autoencoding video frames IoT and Machine Learning for Next Generation Traffic Systems Themes Creative Computing Design & Development - Previous Next

< Back Dr Jeremy Gow Queen Mary University of London iGGi Training Coordinator & Industry Liaison Supervisor Jeremy Gow is a game AI researcher with a focus on computational game design, exploring ways in which AI can help us understand players and games, enhance the game development process, and contribute to the creation of game content. He has been a lecturer at EECS and a member of the Queen Mary Game AI group since 2018. He has a background in artificial intelligence and human-computer interaction research, and a PhD in AI from the University of Edinburgh. He is particularly interested in supervising students with a game development or AI background on the following topics: Automated playtesting and QA AI-based game development tools Modelling player experience AI for the design of agents and procedural generators Computational creativity in games Research themes: Game AI Game Analytics Game Design Computational Creativity Email jeremy.gow@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Creative Computing Design & Development Game AI Game Data - Previous Next

< Back Peter York University of York iGGi Alum PhD student working in analytics and machine learning for esports broadcast and understanding. In particular working with Weavr on various projects related to broadcast and learning tools for Dota 2. Please note: Updating of profile text in progress Email Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Data-Driven Audience Experiences in Esports Metagaming and metagames in Esports DAX: Data-Driven Audience Experiences in Esports A generalized framework for self-play training Themes Esports Game AI - Previous Next

< Back Tom Wells University of York iGGi PG Researcher Available for placement Tom has an interest in niche alternative and indie games which evoke strong emotions and are narratively immersive. He studied Experimental Psychology as an undergraduate in Oxford, specialising in conscious brightness perception in specific optical pigments. His Masters was in Computational Neuroscience, Cognition and AI from Nottingham, and focused on Computer Vision (specifically facial recognition) and Visual Attention. He enjoys heavy metal, strength sports and literature. A description of Tom's research: With the rise of digital art, Uncanny Valley has emerged from an esoteric robotics concept into an infectious memetic phenomenon, with specific memes such as 'Uncanny/Canny Mr. Incredible', or more generally uncanny faces being used as reaction images for humor. Critics and players will now refer to specific media being 'Uncanny' rather than using more general words as 'off-putting', demonstrating uncanniness cementing itself in the public consciousness as examples increasingly abound; ergo digital artists should be aware of evoking the uncanny even with modern rendering technology, as audiences become increasingly discerning of the Uncanny. This is most pertinent in videogames, where rendering is performed in real-time, meaning rendering constraints must be implemented. This potentially confines characters to the Uncanny Valley, as it may not be possible to increase graphical fidelity, thus artists may be left to either accept the uncanny or demaster their work (both undesirable options). This project aims to learn about the Uncanny Valley pertaining to modern skin rendering techniques, using artificial intelligence (specifically GANs) to directly map skin rendering parameters onto user assessments of uncanniness and realism. This can then be reverse engineered to provide automated tools for generatively rendering realistic non-uncanny skin, and predicting audience responses to skin realism, expediting QA testing. The primary experimental stage is to generate a face database with photorealistic skin to be assessed using psychometrics by participants. This is additionally one of few studies looking into the novel phenomena of training AI's to generate human-oriented psychologically salient content. Email tw1700@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes - Previous Next

< Back Rory Davidson University of York iGGi PG Researcher Available for post-PhD position Learning and Strategy Acquisition in Digital Games Given the success and impact of games and the gaming industry, it is unsurprising that it has become the centre of a significant body of academic research and other literature. However, while the cognitive effects of gameplay have been extensively studied, this has typically been done from a “black-box” perspective – that is, looking at the effects of gameplay as a whole upon some other task or metric, such as ability to strategize or proclivity to violence – leaving the inner mechanisms of cognition during gameplay much less understood. In particular, while the idea of learning from games is an area of continued interest in educational psychology, very little literature exists on the subject of how learning in games actually occurs on a cognitive level. This study aims to fill this knowledge gap by examining the ways in which player learning and strategy acquisition occur within games. This examination will have two main hierarchical goals. In the first phase, the study will use experimental methods inspired by analysis of learning methods used in games as well as literature review of more general theories of learning and cognition, such as the dual-process account or the CLARION model, in order to form a model better specialized for the field of digital gaming. In the second phase, it will analyse how such a theory may be put to practical use to inform the design of games and game-like experiences. These two phases can be summed up in the following main research questions: Phase 1: How can strategy acquisition in digital games most effectively be explained as a cognitive process? Phase 2: How can this understanding be put into practice in the development of games with specific desirable characteristics? By linking a more complete understanding of cognition and learning during games with measurable or observable gameplay characteristics, this study will further research on gameplay experience, such as that on immersion. The first phase of research additionally has relevance to the field of AI, in which human responses to difficult and complex problems such as digital games may be mimicked or otherwise used to inform the design of new techniques, as well as to gamification, which attempts to elicit such responses in non-game contexts. Email rd553@york.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Supervisor: Prof. Paul Cairns Featured Publication(s): Automatic Game Tuning for Strategic Diversity Themes Applied Games Design & Development Player Research - Previous Next

< Back Dr Anne Hsu Queen Mary University of London Supervisor Anne Hsu’s research includes machine learning, artificial agents, natural language processing and learning, human decision making, interaction design, and well-being technology. Her interests include developing interactive systems that use machine learning and understanding of human psychology to improve human behaviour. She is particularly interested in supervising students with a machine learning, design, HCI, or behavioural sciences background on the following topics: understanding and designing for curiosity in games design for behaviour change motivational/educational games Research themes: Game AI Game Design Games with a Purpose Player Experience Gamification Email anne.hsu@qmul.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Themes Applied Games Design & Development Esports Player Research - Previous Next

< Back Janet Gibbs Goldsmiths iGGi Alum Janet is exploring how multi-modal perceptual feedback contributes to a player's sense of presence in the virtual world. Jaron Lanier described Virtual Reality (VR) as the substitution of the interface between a person and their physical environment with an interface to a simulated environment. This interface is of particular significance in understanding how presence depends on the nature, extent and veridicality of our sensorimotor interaction with the virtual environment, and how that relates to our normal engagement with the real world. In practice, only selected parts of the interface are substituted - we are never fully removed from our physical environment. Our perceptual apparatus evolved to make sense of changing sensations in multiple modalities originating naturally and coherently from the same event or percept. By contrast, in VR, individually crafted feedback using different technologies for each modality are coordinated to appear as if from a single source. VR benefits from a long history of visual and audio technologies, developed in harness for virtual experiences from cinema to computer games. Haptics is a relative newcomer that must be blended with them to create coherent multimodal perceptual experiences. Additionally, haptics is closely related to proprioception, and to the wide range of tactile senses—texture, heat, pain etc—that current VR systems do not address. Building on sensorimotor theory of perception, Janet aims to establish how our perceptual system responds to multi-modal feedback that almost, but not quite, matches what we are used to, in making sense of the simulated environment of VR. Email JGIBB016@gold.ac.uk Website LinkedIn Mastodon BlueSky GitHub Other Link Featured Publication(s): Investigating Sensorimotor Contingencies in the Enactive Interface A comparison of the effects of haptic and visual feedback on presence in virtual reality Novel Player Experience with Sensory Substitution and Augmentation Investigating sensorimotor contingencies in the enactive interface Themes - Previous Next

< 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